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An investigation of cognitive style and conservation ability in first-grade boys

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An investigation of cognitive style and conservation ability in first-grade boys
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Rediehs, Glen Howard, 1940-
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viii, 109 leaves. : illus. ; 28 cm.

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Computer programming ( jstor )
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Thesis -- University of Florida.
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Bibliography: leaves 102-107.
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Typescript.
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AN INV\7ESTIGATIJG',: OF COGNITIVE STYLE AND CONSERVATION ABILITY IN FIRST-GRADE BOYS












By

GLEN HOWARD REDIEHS


A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY









UNIVERSITY OF FLORIDA 1973
















ACKNOWLEDGMENTS


Many people have helped in the completion of this study. The School Board of Polk County, Florida, Mrs. Genevieve Curry, Principal of Lime Street Elementary School, Lakeland, Florida, and her first-grade teachers and students made it possible to test the sample used. The testing procedure and data collection were completed with the assistance of Mrs. Betty Mason, Professor of Educational Psychology, Florida Southern College, Lakeland, Florida, and nine of her students. Two of the author's students in a child psychology class at Valencia Community College, Orlando, Florida, helped in scoring the tests.

A class in cognitive development under Dr. Jacqueline Goldman, Professor of Psychology, the University of Florida, Gainesville, Florida, provided the original idea for the research. The author's committee members assisted in writing the original proposal and in revising the full dissertation. Dr. R. Emile Jester, co-chairman, was particularly understanding and helpful in producing this document.

Dr. Irving E. Sigel, Professor of Psychology, State

University of New York at Buffalo, permitted the use of the Sigel Cognitive Style Test (SCST) in this study, He










provided further information relative to the SCST as it was needed.

The help and cooperation of these people is acknowledged and gratefully appreciated by the author of the present study.


iii

















TABLE OF CONTENTS


ACKNOWLEDGMENTS . . . ............. . ..

LIST OF TABLES. . . . . .. . . . .. .. .. . . .

ABSTRACT ............ . . . . . .

CHAPTER

I INTRODUCTION AND REVIEW OF THE LITERATURE


Page
* ii � V

* vi



, 1


Statement of the Problem.


Review of the Literature. . .
Rationale... ........
Hypotheses. . . . . . ....
Summary . . . . . . . . . . .

II METHOD AND PROCEDURES . . ....

Sample. . . . . . . . .. . .
Instrumentation . . . ....
Assistants. . . . . . ....
Procedure . . . . . . .
Data Collection and Analysis,

III RESULTS ..... .............

IV DISCUSSION AND CONCLUSION . ... APPENDICES

A SCORING CATEGORIES FOR SCST . . .

B SIGEL COGNITIVE STYLE TEST ITEM
DESCRIPTIONS .... ............

REFERENCES .........................

BIOGRAPHICAL SKETCH .............


* � . . . .


. . 0 . . 95


101

102 108
















LIST OF TABLES


Table Page

1 Conservation of Number Studies, . . . . . . , 14 2 Conservation of Length Studies. . . . . . . . 20 3 Conservation of Substance Studies . , . ., . 22 4 Conservation of Weight Studies. . . . . . . . 25 5 Extraneous Variables in Conservation Studies. 27 6 Stepwise Discriminant Function Analyses . . . 63 7 Stepwise Multiple Regression Analysis , . , . 67 8 Means and Standard Deviations . . . . . . . . 68










Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment
of the Requirements for the Degree of Doctor of Philosophy

AN INVESTIGATION OF COGNITIVE STYLE AND CONSERVATION ABILITY IN FIRST-GRADE BOYS By

Glen Howard Rediehs

August, 1973

Chairman: Dr. William Watson Purkey Co-chairman: Dr. Robert Emile Jester Major Department: Foundations of Education

The purpose of this study was to investigate the relationship, if any, between cognitive style as measured by the Sigel Cognitive Style Test (SCST) and intellectual maturity as measured by success on Piagetian number, length, substance, and weight conservation tasks. Building a rationale on Halford's (1970) model for conservation training and on experiments by Yeatts and Strag (1971), Peters (1970), Garrettson (1969), and Orpet and Myers (1970), this author hypothesized that there would be a relationship omong cognitive style preference and/or flexibility and conservation ability.

Scores were obtained from 37 first-grade boys for cognitive style preference, flexibility and fluency; conservation ability; Peabody Picture Vocabulary Test (PPVT) IQ; and age in months. Four major categories of style in which the subjects could score were on the SCST: Descriptive partwhole (DPW), Descriptive-global (DG), Relational-contextual

(RC) and Categorical-inferential (CI), The four major










categories contained twenty subcategories. These subcategories were indicated by an abbreviation for the major style plus a number (e.g., DPWI, RC4, etc.).

To screen the independent variables, stepwise discriminant function analyses were completed. The variables which demonstrated predictive ability were then used in a stepwise multiple regression analysis.

Cognitive style was scored according to initial preference (first response for each item on the SCST) and total preference (total frequency of responses in each style category). Statistically significant results (a=.Ol) were obtained. Subjects' scores for their initial preference on two independent variables accurately predicted their conservation score (p<.05). Those two variables were cognitive style categories that used comparison between figures (RC4) and age categories (DG5) as the basis for pairing items on the SCST. The best equation (p<.Ol) used a combination of seven variables. Those variables were cognitive style categories that used comparison between figures (RC4), age categories (DG5), common role or attribute (C12), age and sex (DG7), thematic interaction or interdependent function (RCI&5), family or other relationship (RC6) and physical attributes (DPWI) as the basis for sorting. The Descriptive part-whole and Categorical-inferential style categories were positively related to conservation scores. Descriptive-global style was negatively related to the dependent variable.


vii









Interpreting these results as they apply to the hypothesized relationship between cognitive style preference and conservation ability was difficult. The research cited in the literature review did not provide an explanation for these results. An explanation of the findings was offered on the basis of the nature of the correlations between the independent and dependent variables and the fact that subjects who scored high on conservation ability tended to use more style categories than the subjects who scored low. This suggested that subjects who obtained higher conservation scores used the Descriptive-global style infrequently and simultaneously enlarged their use of the other style categories. Subjects who scored lower on conservation preferred the Descriptive-global style and exhibited a more limited repertoire of cognitive style,

The results gave a clear answer to the hypothesized relationship between cognitive style flexibility and conservation. Flexibility of style, fluency of response, PPVT IQ and age in months did not relate.

In summary, this study produced evidence establishing

the role of cognitive style in conservation ability--a general expansion in the use of part-whole (analytical) and inferential styles and a decreased use of global style. It did not, though, indicate that one particular style preference related to conservation ability. Nor did it find flexbility of style to relate to conservation.


viii
















CHAPTER I


INTRODUCTION AND REVIEW
OF THE LITERATURE


Statement of the Problem

Jean Piaget, a Swiss psychologist, has proposed a theory of intellectual development. His theory has described changes in cognitive functioning, as they emerge, one after another, during the life of a child. Many researchers have tried to move children through the stages of intellectual development at an accelerated pace. To do this, they have attempted to discover what abilities or knowledge were necessary for a child to possess in order to proceed from one stage to the next. Then they trained children in those abilities or that knowledge.

Most studies that have sought to discover the abilities or knowledge necessary for stage transition have focused on change from the "preoperational" stage to the "operational" stage. Basically, this change is distinguished by a child's emerging ability to make logical or "operational" judgments about problems rather than perceptual or "preoperational" ones. An example of this is found in "conservation" ability. A "conserving" child knows that the amount, weight, length,









number, etc., of an item or set of items remains the same even if the shape of the item is changed or if the set of items is moved around. As long as nothing is added or subtracted, it must, logically, still be the same. A nonconserver is deceived by the change in shape or arrangement and concludes that the amount, weight, length, number, etc., have changed because the item or set of items looks different.

The question is, "What helps a child become a conserver?" Despite many experiments which have identified one or another ability or knowledge or a combination of abilites and knowledge, no one has provided a complete answer to the question. Piaget has offered some explanations and other researchers have provided others. The nature of transition from one stage to another and the experiences that help induce conservation ability have remained elusive.

Individual differences among children have been shown

to have a role in the emergence of operational thought. The present study was designed to determine the degree of relationship, if any, between cognitive style and conservation ability. "Cognitive style" has been used to refer to the manner in which children have perceived the elements of a stimulus or problem. In some cases children have concentrated on the details of the stimulus or problem. In other cases, children perceived things as a whole. Or, they may have seen the relationships between the elements in the stimulus or problem. There have been a number of ways of









describing and measuring cognitive style. Some examples have been Kagan's Analytical--Non-analytical (or Relational) (Kagan, Rosman, Day, Albert and Phillips, 1964); Witkin's Field-dependent--Field-independent (Witkin, Dyk, Faterson, Goodenough and Karp, 1962); and Sigel's Descriptive, Relational and Inferential dimensions (Sigel, Jarman and Hanesian, 1967).

On the basis of research evidence, there was reason to believe that individual differences in cognitive style affected the ability to acquire conservation ability and an operational level of thought (Garrettson, 1969; Orpet and Myers, 1970; and Peters, 1970). The purpose of this study was to investigate the relationship, if any, between preference and flexibility of cognitive style as measure( by the Sigel Cognitive Style Test (SCST) and intellectual maturity as measured by a composite score on number, length, substance, and weight conservation ability. If such a relationship could be shown, this would contribute to a better understanding of antecedents to conservation ability and the nature of the child's transition to conservation ability. Such knowledge could aid in the development cf learning situations designed to induce conservation ability and promote overall intellectual functioning as Piaget has described it (Piaget, 1966).










Review of the Literature

There are five portions to the review of the literature. First, conservation is briefly explained. Research dealing with the same question as the present study, "What helps a child become a conserver?" is then cited, Theoretical models and experimental methods of training for conservation are included in this research. The models and the methods have identified factors that researchers claim have helped children become conservers. Cognitive style is explained in the next section. Finally, literature linking cognitive style and conservation is reviewed. This last portion of the literature review concerns those experiments that are most important for the rationale behind the hypotheses of the present study.

There are, therefore, five sections to the literature review: (a) a brief summary of Piaget's theory as it relates to conservation, (b) short explanations of ten theoretical models that have attempted to account for transition between Piaget's stages, (c) studies of attempts to train conservation, (d) theories and studies of cognitive style, and (e) literature linking cognitive style and conservation. Piaget's Theory as it Relates to Conservation

Intelligence has been described by Piaget as being dependent on the process of growing by interacting with the environment (Piaget, 1966). Intellectual growth has been









set forth by the same theorist as a number of stages through which a child must necessarily and sequentially pass. Each stage has been characterized by an organized set of ways in which a child interacts with the environment, Piaget has identified ten such stages children encounter between birth and sixteen years of age. These stages have been conceptualized as the smaller steps within three larger periods:

(a) Sensorimotor Period (birth to 2 years), (b) Preoperational Period (2 to 7 years), and (c) Operational Period (7 to 16 years).

The present study was concerned with the movement of

the child from the Preoperational Period to the Operational Period. Piaget has maintained that the ability to conserve was evidence that a child was moving into the Operational Period. Conservation ability has not appeared in an all or none fashion; it has emerged gradually. Children have demonstrated partial and vacillating success before they exhibited consistently correct conservation judgments.

Piaget has shown that at about seven years of age the average child is capable of keeping track of two characteristics of an item or a set of items simultaneously while those characteristics are changed. As a result of this ability, a child can recognize that a given property of an item or a set of items, such as mass or number,remains the same, or is "conserved," even though it is reshaped or moved. The same principle applies to conservation of number,









length, height, substance, weight, volume, density, etc.-some of which appear later than others in the child's life. Conservation of substance, for example, indicates the ability to see the equality of mass between two equal substances, such as two balls of Play-Doh, even after the shape of one has been altered. In conservation of substance, a conserving child can see that changes in one dimension, such as height, of an item are offset by compensating changes in another dimension, such as width. Conservation of weight would assert a like equality, this time of weight, in spite of other changes in the object. A number conserver identifies equality in the number of items in two initially equal sets, such as two rows of pennies, despite changes in their arrangement. This same principle applies through all kinds of conservation.

In a typical test for conservation, the experimenter

establishes, to the satisfaction of the subject, initial--equivalence of substance, weight, number, etc., between two items or sets of items, transforms one of them, and then asks if the transformed item or set is "more," "less," or "the same" as the nontransformed item or set of items, A conserver would assert that they are still "the same" and offer a logical reason for his judgment. A logical reason would be, "because you didn't add or subtract anythng,'..or "I could make it back like it was before."










Ten Theoretical Models of Conservation

Researchers have proposed at least ten theoretical

models attempting to account for transition between Piaget's stages, i. e., what variables help a child acquire conservation ability. All have had some theoretical reasoning and some empirical evidence behind them. None has proven itself as the only correct explanation.

The ten theoretical models reviewed are: (a) Piagetian, (b) cognitive conflict, (c) operational reversibility, (d) computer analogue, (e) information processing,

(f) S-R, (g) social learning, (h) learning set, (i) semantic, and (j) cue constraint, The first nine models are explained briefly. The last, "cue constraint," is dealt with more thoroughly since it was important for the rationale behind the hypotheses of the present study.

Piaget has named four factors that combine to account for the movement from one stage to the next: (a) maturation, (b) physical experience, (c) social experience, and

(d) equilibration (Ginsberg and Opper, 1969). Equilibration has been Piaget's prime explanation of stage transition. Equilibration refers to an ongoing, cyclical process of intellectual balance and imbalance which a growing child experiences. As he interacts with his environment, new experiences throw him into cognitive "imbalance." This imbalance requires him to change in order to comprehend and handle the new situation and return to a state of cognitive










balance. Despite the different environment each child experiences, his interaction with its novelty forces the equilibration process into action and propels him along, from one stage to the next in Piaget's theory, in a predictable fashion.

Two other models, "cognitive conflict" and "operational reversibility;' have had similarities to Piaget's model. Smedslund's (1961a) "cognitive conflict" model was built on the Piagetian model. A subject was presented with conservation trials in which it was possible for him to see a change in both shape and arrangement and also subtraction or addition of some of the material. He had to decide whether he would use perceptual cues, the change in shape or arrangement; or logical cues, the fact that some material was taken away or added, as the basis for his conservation judgment. Smedslund claimed this conflict created the cognitive imbalance that fosters the equilibration process and intellectual growth.

The "operational reversibility" model also uses a Piagetian concept. Brainerd and Allen (1971) asserted that the one common feature in successful attempts to train children to conserve was repeated exposure to "object-bound reversibility. This is a Piagetian term that refers to the realization that if one changes an object, such as the shape of a piece of Play-Doh, it can be restored or reversed to what it was before.










The remaining seven models for conservation acquisition do not have any unifying themes around which to group them and are simply other ways of explaining what it is that helps children acquire the ability to conserve, i. e., other ways to answer the question the present study seeks to answer.

Klahr and Wallace (1970) described learning to conserve as similar to programming a computer. The visual and verbal data the child receives from a conservation task are supposedly encoded, a computer-like routine constructed in the mind, and the program then executed.

Bruner (1964) viewed the ability to conserve as the result of growth in techniques of information processing in which language was the key. The use of language to make sense out of experience, that is, to process the information one gets from experience, enables the child to conserve. He is less dominated by perceptual cues and more able to use symbolic or logical processes as a result of this use of language.

In one theory it has been claimed that there are three steps in a typical conservation task: (a) initial equivalence between two items or sets of items, (b) a change in one item or set of items, and (c) a comparison between the two items or sets of items. An S-R analysis (Sigel and Hooper, 1968) considered these three steps to be three stimuli. The second step was the important one. If nothing










was added or taken away from the items during the change step, step (b), then that was the cue, or the discriminative stimulus, for the answer "the same" when the experimenter asked the subject whether the two items or sets of items were still the same or not. If the second step included addition and/or subtraction of material from the items, then that was the cue for a "more" or "less" response to the experimenter's question.

Waghorn and Sullivan (1970) found that their originally nonconserving subjects began to exhibit conservation ability as a result of viewing a film in which an experimenter and subject modeled conservation ability. They considered this support for a social-learning theory of the acquisition of conservation.

Kingsley and Hall (1967) and Rothenberg and Orost (1969) concluded that conservation ability was dependent on mastery of a sequence of component abilities. Each of these had to be learned, one after another, to a criterion level of performance.

A "semantic model" for conservation has been advanced by Braine and Shanks (1965). They pointed out that when an experimenter tests for conservation, the child has to produce the correct verbal response in order to be considered a conserver. An understanding of conservation is in the child's mind before it shows up in a test for conservation, according to Braine and Shanks, and all that a typical










conservation task shows is whether the child has learned adult definitions for such words as "same," "more," "less," etc.

The last of the conservation models described here is labeled "cue constraint." ialford (1970b) examined the equilibration and learning theory explanations for the acquisition of conservation and decided the truth was somewhere in-between. For him, conservation ability was partly the result of using the right cues. Using the right cues focuses on discrimination between stimuli and is consistent with a learning theory position. But, in consonance with equilibration, he proposed that there must also be "constraint" between the available cues. For instance, there must be constraint between quantity, height, and breadth in a conservation of substance task; or between the number of items and the spacing of items in a conservation of number task. The ability to conserve rests on the use ofall cues in "truth table" fashion and in noting their compensatory relationships.

One of the hypotheses of the present study anticipated a relationship between flexibility of cognitive style and conservation ability. Part of the rationale for this hypothesis came from Halford's "cue constraint" model; ..If a child could see both-the details in-the-items of a*conservation task, which was characteristic of one type of cognitive style, and also the whole or relationships between the items










in a conservation task, which was characteristic of another type of cognitive style, thus demonstrating flexibility of cognitive style, he should have recognized the constraint between cues more easily and demonstrated conservation ability more readily.

The models reviewed above have all attempted to explain how a child grows from a nonconserver to a conserver. Since all of the models have a theoretical basis and some empirical evidence, the search for a single variable which helps a child attain conservation ability was very difficult. Since there was reason to believe the cognitive style preference or flexibility a child used may have helped him become a conserver (Halford, 1970b), the present study sought to find those relationships.


Studies of Attempts to Train Conservation

In the statement of the problem, it was mentioned that many researchers have tried to move children through the Piagetian styles of development at an accelerated pace. The training programs they designed to make conservers out of nonconservers all shared the concern of the present study: "What is it about the individual differences among children, or the different experiences they have, that predisposes them to move from preoperational to operational thought?"

In order to cite some answers that have been offered to this question, literature describing studies of attempts to train conservation are reviewed here. The review has five










parts: comments on successful and unsuccessful methods used to train children in the four types of conservation tasks used in this study (number, length, substance and weight) and, last, a summary of other variables (e.g., IQ, socioeconomic class, conservation task complexity) that make a difference in whether a child can demonstrate conservation ability. In each of the first four sections, the reader is referred to the appropriate table which summarizes the methods used and the success or failure they produced. The review briefly explains each of the training methods that appeaiin the tables.


Studies dealing with conservation of number

Various training methods used in an attempt to foster the acquisition of conservation of number are summarized in Table 1. The effectiveness of thirteen different training procedures was explored in the studies reviewed here. These methods were tabulated according to success or failure and briefly defined in the following review.

The objective of reversibility training was to get the subject to realize that a transformation could be reversed. For example, a lengthened row of pennies that appeared to have more pennies could be shortened again to show one-toone equivalence with the standard, nontransformed, comparison row.

Halford and Fullerton (1970) designed a procedure which has been labeled "cue constraint." In the training sessions,





Table 1

.......... .__Conservation of Number Studies
Item Training Method Success Failure


Reversibility


Cue Constraint Component Abilities Verbal Rule Instruction Direct Reinforcement/
Reinforced Practice Addition - Subtraction


Non-Verbal Reinforcement Discourage Use of Misleading Perceptual Cues Cognitive Conflict Multiple Classification Language Activation Verbal Orientation Equilibration


Wallach, Wall & Anderson
(1967)
Wallach & Sprott (1964) Halford & Fullerton (1970) Rothenberg & Orost (1969) Beilin (1965) Hatano & Suga (1969)* Gruen (1965) Wohlwill (1959)* Wohlwill & Lowe (1962)*






Gruen (1965)


*No statistical significance; trend only


Mermelstein & Meyer (1969)

Wohlwill (1959) Wohlwill & Lowe (1962) Wallach, Wall & Anderson
(1967)

Beilin (1965) Wohlwill & Lowe (1962)




Mermelstein & Meyer (1969) Mermelstein & Meyer (1969) Beilin (1965) Beilin (1965)


w_










a subject was repeatedly asked to select from several rows of items of varying lengths the one row that had the same number of items as a standard row--despite the fact that it wasn't necessarily the same length as the standard row. This method was supposed to lead a child to recognize that length of the row and spacing of the items were the important facts and that they had a compensatory relationship.

Component abilities refers to a sequence of probable steps or component skills that Rothenberg and Orost (1969) considered the antecedents to conservation. The component abilities necessary for number conservation were: (a) rote counting, (b) counting attached to objects, (c) "same" number, (d) the "same" versus "more" distinction in terms of number, (e) addition and subtraction, representing a change in number, (f) one-to-one correspondence, (g) reversibility, and (h) the distinction of "more," referring to the actual number of objects, versus "longer," referring to their arrangement in space. Each of these abilities was learned, in sequence, to a criterion level of performance. At that point, conservation ability was supposed to emerge as a result of the mastery of the prior skills.

Verbal rule instruction indicates that the subject was orally told the logical reason for a conserving response during the training procedure. He was then expected to learn it and apply it correctly.










Direct reinforcement consisted of the subject counting the two sets of items immediately after the conservation judgment to see if his prediction of the two rows being "the same" or one row "more" or "less" was correct, Success of this method was viewed as support for a learning theory model of conservation acquisition.

In the addition-subtraction procedure, one or more items were added or subtracted after initial equivalence was established between two rows of items and before one set of items was rearranged. The subject was to recognize the addition or subtraction as the important cue in making his conservation judgment.

Beilin (1965) used a non-verbal reinforcement procedure when presenting subjects with a traditional number conservation task. A correct, conserving response produced a buzzer and red token as reinforcement. An incorrect response yielded neither buzzer nor token,,,_.Wohlwill and Lowe (1-962) trained subjects to pay

attention to the number cue, the number of items, instead of the length cue, the length of the array. This supposedly led to a better basis for conservation judgments and has been labeled "discourage use of misleading perceptual cues."

Smedslund's cognitive conflict procedure required that in at least-some of a se-ries of conservation tasks, the transformation of one set of items included rearrangement of the items and addition-subtraction of some items. The subject had to choose between a perceptual or a logical basis









for his conservation judgment; he had to decide if the two sets of items were still the same or not because of the way they looked or because of the addition or subtraction of items (Gruen, 1965).

Multiple classification has been shown to be a prerequisite to conservation according to Piaget. This training procedure consisted of a series of sessions in which subjects were trained to identify multiple attributes of various objects, that is, multiple ways in which objects were the same and different. With this prerequisite further developed, the child was supposedly more likely to demonstrate conservation ability.

The language activation procedure was modeled on

Bruner's (1964) theory. This method focused on the linguistic aspect of the conservation test situation--hopefully decreasing the child's reliance on deceptive perceptual cues.

In the verbal orientation reinforcement, the subject was told the number concept in the instructions so that he would be verbally oriented to the relevant attribute. The subjects in this procedure were also reinforced with a token for a correct response.

Beilin (1965) attempted to imitate the equilibration

procedure Smedslund (1961a) used to train weight conservation. The spatial arrangement of the items in Beilin's (1965) equilibration method underwent transformation without the addition or subtraction of items. This was supposed to









produce "cognitive uncertainty," which then forced internal reorganization of schemata and resulted in new cognitive certainty or equilibrium and, as a result, number conservation ability.

Mermelstein and Meyer (1969) attempted to replicate the training methodologies of cognitive conflict (Smedslund, 1961d), verbal rule instruction (Beilin, 1965), language activation (Bruner, 1964) and multiple classification (Sigel, Roeper and Hooper, 1966) and test for conservation along more rigid criteria. The results were, as the authors predicted, nonsignificant. Some reviewers (Brainerd and Allen, 1971) have faulted Mermelstein and Meyer for imprecise replication and 'loaded' procedures, Three of the replicated procedures were not developed originally to induce number conservation, but rather substance conservation.

The results of the experiments designed to induce number conservation did not provide a clear answer to the question the present study posed. Some of the methods revolved around Piagetian notions. Reversibility and cognitive conflict, for example, were successful, but multiple classification and equilibration were not. Additionsubtraction results were ambiguous. Other procedures used reinforcement. Non-verbal reinforcement failed and the results for direct reinforcement were equivocal. Three methodologies focused on verbal help or language activation, They were mostly unsuccessful.










What is it that helps a child acquire number conservation ability? The results of literature reviewed here, although not exhaustive of all the pertinent studies, indicated no final answer. Not all the children in any one study cited in the review were helped. The nature of the transition from nonconservation of number to conservation of number and the specific antecedents to this ability remained elusive.


Studies dealing with conservation of length

A number of training methods used in an attempt to

foster the acquisition of conservation of length are summarized in Table 2. These methods were tabulated according to success or failure.

No methodologies were attempted in this review of conservation of length studies that were not explained in the review of studies dealing with conservation of number. One of the observations Smedslund (1963) made is interesting. After viewing the results of an experiment, he concluded that different children seemed helped by one or another of the several variations of the cognitive conflict procedures he used. Perhaps behind the inconsistencies and ambiguities of the research literature is that basic principle: different experiences help different children. Murray (1968) obtained statistically significant results with his reversibility training method. But, he used highly specific








Table 2

Conservation of Length Studies


Item Training Method Success Failure

1 Reinforced Practice Gruen (1965)

2 Reversibility in a Murray (1968) Cognitive Conflict
Situation

3 Component Abilities Kingsley & Hall (1967)

4 Verbal Rule Instruction Beilin (1965) 5 Cognitive Conflict Gruen (1965) Smedslund (1963)*

6 Non-Verbal Reinforcement Beilin (1965) 7 Verbal Orientation Beilin (1965) Reinforcement

8 Equilibration Beilin (1965)


*No statistical significance; trend only










task-related training procedures, and one might have doubts about transfer to length tasks with less similar materials.

As with the conservation of number studies cited in

the previous section, those concerned with length were inconclusive. Success was more prevalent, but all children still were not helped by any one method. The abilities or knowledge necessary for conservation ability defied reduction to a simple item or combination of items,


Studies dealing with conservation of substance

A number of training methods used in an attempt to foster the acquisition of conservation of substance are summarized in Table 3.

Two new methodologies that were not explained so far were introduced in this review of conservation of substance studies. The first was Waghorn and Sullivan's (1970) film-mediated model. Nonconservers, who watched a model successfully conserve in a filmed sequence, began conserving. This result was cited as evidence for the role of social learning in conservation acquisition. Fleischmann et al. (1966) compared two variations of a traditional conservation task and a third group which received verbal feedback concerning the correctness of their conservation judgment. The feedback group improved significantly better than the traditional groups.

The manner in which the "cue constraint" method was applied to substance conservation demands explanation.





Table 3

Conservation of Substance Studies Item Training Method _ Success Failure


Reinforced Practice Prerequisites (multiple
classification, multiple
relations & reversibility) Prerequisites (multiple
attributes, classification,
seriation & reversibility) Film-Mediated Verbal Feedback


Cue Constraint


Cognitive Conflict



Addition - Subtraction Suppression of Perceptual Cues


Gruen (1965) Sigel, Roeper & Hooper
(1966)


Baptiste (1969)



Waghorn & Sullivan (1970) Fleischmann, Gilmore &
Ginsberg (1966)

Halford (1969; 1970a;
1970b)

Gruen (1965) Smedslund (1961e)* Smedslund (1961e)*


Strauss & Langer (1970) Fleischmann, Gilmore &
Ginsberg (1966)


*No statistical significance; trend only


I I _____________________









Halford (1969, 1970a, 1970b) believed that acquisition of conservation was not the result of one or another method. He developed the notion that a child must develop a "mental truth table" which guided his judgment according to all the possible combinations of "equal," "more," and "less" cues from quantity, height, and breadth dimensions jointly considered. His training procedures were designed simply to expose the child to many such combinations under the highest possible level of incentive. The three experiments cited here involved numerous opportunities for classifying containers requiring judgments about the combinations of the several dimensions involved. Sometimes significant and always positive results were found. It seemed that merely exposing a subject to experiences which involved compensation of height, breadth, and quantity cues and their joint constraint on each other promoted the acquisition of quantity conservation quite independently of any of the training procedures painstakingly developed to reflect Piagetian, learning theory, or other theoretical positions.

In addition to the three methodologies described above, Brison (1966) used a "no method" method. Instead of designing a training procedure which had its base in some theory, he focused on-accelerating conservation itself. Nonconservers were given two days of training in which the subjects were simply presented with conservation of liquid situations in which they chose which of two deformed









quantities of juice they wanted. A significant difference between experimental and control groups was found.

An impression of a high rate of success of the substance conservation training procedures is given in Table 3. However, when it is noted that Smedslund (1961e) reported no statistical analyses and Sigel, Roeper and Hooper (1966) based their conclusions on trends and one brief statistical test, the evidence is not so clear. Success was mixed and the basic question of what it is that helps children conserve still did not have a clear, universally applicable answer. The manner of transition between stages and the antecedents to such intellectual growth were not revealed by these studies.


Studies dealing with conservation of weight

Several training procedures which have been used in an attempt to foster the acquisition of conservation of weight are summarized in Table 4.

One method found in Table 4, which was not mentioned previously, was labeled "empirical controls," This meant that the subject could observe the objects used in the task on a scale following his conservation or nonconservation prediction. Such a procedure was identical to what Smedslund and others called "direct reinforcement" elsewhere.

Two of the procedures reviewed here involved combination methods. One was successful (Overbeck and Schwartz, 1970) and one showed only positive trends (Smedslund, 1959).









Table 4

Conservation of Weight Studies Item Training Method Success Failure
1 Reinforced Practice plus Overbeck & Schwartz Verbal Rule Instruction (1970)

2 Component Abilities Kingsley & Hall (1967)

3 Direct Reinforcement/ Smedslund (1959; 1961a;
Empirical Controls 1961b)*

4 Empirical Controls plus Smedslund (1959)* Addition - Subtraction

5 Addition - Subtraction Smedslund (1961a)*

6 Subject Active Partici- Overbeck & Schwartz (1970)
pation

7 Suppress Perceptual Cues Smedslund (1961c)


*No statistical significance; trend


only









Another method not discussed previously in this review was "subject active participation." The experimenters who used this method, Overbeck and Schwartz (1970), hypothesized that the personal involvement of the subject in the transformation of the material used in the task was important. The results were nonsignificant.

There were still no clear answers emerging from the

literature. Considering the number of studies that reported only trends, success at training for acquisition of conservation was mixed and evidence for the antecedents to or nature of transition to weight conservation was equivocal. Literature identifying extraneous variables

The problem with the conservation training studies reviewed above is that the results did not reveal how one acquired conservation. The mechanism of transition from preoperational to operational functioning was not exposed. One way to eliminate those elements that hide the essential one(s) is to control as much extraneous variance as possible by experimental design and statistical procedure. Such variables investigated in the research reviewed for the present study are specified in Table 5.

The variables that were found to have a significant effect on measured conservation ability were of two sorts. Some were related to the condition of the subject (intelligence, socioeconomic class, age, vocabulary score and grade), Others were related to variations in training procedure





Table 5

Extraneous Variables in Conservation Studies Item Variable Significant Effect Nonsignificant/Indefinite Effect


Intelligence High Interest Materials Task Complexity Socioeconomic Class Mental Set Age

Mental Age IQ

WISC Vocabulary Language Ability Stimulus Desirability Stimulus Mode


Number Conser

Dodwell (1960) Baker & Sullivan Baker & Sullivan Baker & Sullivan Winer (1968) Goldschmid (1967) Goldschmid (1967) Goldschmid (1967) Goldschmid (1967)


vation


(1970) (1970) (1970)


Wohlwill & Lowe (1962) Gruen (1965) Roll (1970) Murray (1970)





Table 5 (continued)


Item Variable Significant Effect Nonsignificant/Indefinite Effect


1 Grade

2 Mental Age

3 IQ

4 WISC Vocabulary

5 Age

6 Addition-Substraction
Ability

7 "Game" Presentation

8 Sex

9 "Warm Ups"




1 Item Difficulty 2 Stimulus Setting
(diameter of container)

3 Type of Judgment
(direct comparison,
identity & equivalence
estimates)


Length Conservation

Murray (1968) Goldschmid (1967) Goldschmid (1967) Goldschmid (1967) Goldschmid (1967)











Substance Conservation

Peisach & Wein (1970) Schwartz & Scholnick (1970 Schwartz & Scholnick (1970


Gruen


(1965)


Murray (1968) Murray (1968) Smedslund (1963)





Table 5 (completed)


Item Variable Significant Effect Nonsignificant/Indefinite Effect


Composite Verbal Score Mental Age WISC Vocabulary Age



IQ



Task Complexity Sex

Schooling




Mental Age Age

Stimulus Mode Schooling


Sollee (1969) Goldschmid (1967) Goldschmid (1967) Waghorn & Sullivan (1970) Fiegenbaum (1963)
Goldschmid (1967) Fiegenbaum (1963) Goldschmid (1967) Waghorn & Sullivan (1970)








Weight Conservation

Goldschmid (1967) Goldschmid (1967)


Baptiste (1969) Sigel, Roeper & Hooper (1966) Sigel, Roeper & Hooper (1966)



Fiegenbaum (1963) Baptiste (1969) Goodnow & Bethon (1966)








Murray (1970) Goodnow & Bethon (1966)









(high interest materials, task complexity, mental set, item difficulty, stimulus setting and type of judgment required). The factors that covaried with conservation helped provide insight into the characteristics of a conserving child and the type of procedures that made a difference. Summary of conservation studies

All the methods of training for conservation of number, length, substance and weight that have been reviewed shared the basic problem of the present study, "What is it that helps a nonconserving child to grow intellectually so that he can demonstrate an understanding of conservation?" It is apparent that there is no simple answer.

Smedslund must have had part of the answer when he observed that different procedures helped different children. The search for extraneous variables turned up a number of factors relating to the condition of the child. Taking a cue from these thoughts which suggested that it was unique characterisitcs of the child that predisposed him to acquisition of conservation ability, the present study focused on one of these characteristics: cognitive style. Theories and Studies of Cognitive Style

Neither the theoretical models for conservation nor the results of the experiments that have tried to train children to conserve have clearly answered the question, "What is it that helps a child become a conserver?" The author of the










present study hypothesized that the individual differences between children contribute substantially to the facilitation or inhibition of conservation acquisition. Much of the answer to the basic question of the current study, therefore, lay in identifying further characteristics of children that correlated with conservation ability, The dimension chosen for investigation was cognitive style.

Cognitive style has been used to refer to one way in which researchers have measured individual differences. Basically, measuring cognitive style has been an attempt to find characteristic, consistent ways that people have used in dealing with stimuli in their experience. There have been two main theoretical positions regarding cognitive style that have dominated the recent literature, One has been Field-dependence--Field-independence developed by Witkin and his associates and the other has been Analytic--Non-analytic (or Relational), researched by Kagan and his associates.

Witkin and his associates (Witkin, Dyk, Faterson,

Goodenough, and Karp, 1962) defined a Field-dependent person as one who finds it difficult to overcome the influence of the field surrounding an item or to separate an item from its context. When viewing stimuli or a problem this person prefers to see it as a related whole. Field-independent subjects, on the other hand, are able to distinguish an item:-from its context. These subjects can handle the parts of stimuli or a problem independently from its context,










Cognitive style has been shown to influence perception of people and events in everyday experience, experience of one's self and body concept, ego defense structures, reading ability (Wineman, 1971) and other variables.

Kagan and his associates and other researchers developed a second main theoretical position. This position described two dimensions of cognitive style: (a) Analytic--Nonanalytic and (b) Reflective--Impulsive. Since the SCST, which was used in the experimental portion of the present study, measures cognitive style according to the dimension established by this school of thought, the review is more extensive.

Kagan and his associates (Kagan, Moss and Sigel, 1963) began by noting that when adults were asked to sort figures on the basis of some conon feature, they sorted in consistently different ways. Different subjects individually preferred using one of-three bases for sorting the waythey did: (a) Analytic-descriptive (similarity of visible, objective elements), (b) Inferential-categorical (categories made on the basis of inferred characteristics of the stimuli), and (c) Relational (functional or thematic interdependence between elements in a grouping). After working with these categories, the Inferential-categorical was not found to discriminate among subjects reliably and it was de-emphasized. The major dimension researched by Kagan has been an Analytic-Non-analytic (Relational) one.









Of Kagan's style measures, the Cognitive Style Test (CST) has been the most widely used with children. This test involved the presentation of 30 (originally 44) cards with three figures drawn on each card. The subject was requested to pick two of them that were alike or went together in some way. The subject revealed his cognitive style preference by telling the examiner why he thought the two he selected were alike or went together. If, for instance, a child was shown pictures of a chair, lamp and table, he might have said the chair and table went together because they both had four legs. This would have been an analytic response since he was considering visible, objective parts of the stimuli. If he said the lamp and the table went together because a lamp was always set on a table, that would have been a relational sort. He was placing them together because of their relationship to one another. Bases for analytical and relational style were available on all cards.

A great many personality variables were found to be

associated with the Analytic--Non-analytic dimension (Kagan and Moss, 1962; Kagan, Moss and Sigel, 1963; Kagan, Rosman, Day, Albert and Phillips, 1964; Lee, Kagan and Rabson, 1963; Sigel, Jarman and hanesian, 1967). Highly analytic children were persistent in problems, confident about challenging intellectual tasks, motivated for achievement-related goals, reflective, able to differentiate details of experience, able to resist the effects of distracting stimuli, less









"malleable" in their behavior and more able to form analytic concepts. They produced more word associations homologous by part of speech in a word association test, they mentioned objective parts of stimuli in the Thematic Apperception Test (TAT) before offering any thematic responses, and their style scores correlated with nonverbal subscores on the California Test of Mental Maturity (CTMM). Non-analytic (Relational) children were anxious in new social situations, expecting peer and adult rejection, impulsive, more reactive to external stimuli, less likely to differentiate complex stimulus situations, impulsively aggressive, not easily withdrawn from a group to work on a task, and hyperkinetic.

Significant sex (Sigel, 1965) and age variations in

the data have been demonstrated. Boys generally have been more analytic than girls and have produced higher correlations between analytic style and the characteristics related to cognitive style. In retesting subjects a year after -. initial tests on the CST and on other variables, the results were more stable for girls than for boys. This finding plus the evidence that IQ for the six-to ten-year age span has been more stable for girls than for boys has led some investigators to conclude that cognitive organization is fixed earlier in girls. The relationship between Analytic--Nonanalytic style and age has been shown to be linear. -The . older the subject, the more analytically he performed. In the lower elementary grades, boys' increase in analytic responses has been found to be faster than girls'.










Kagan and his associates also investigated the

Reflectivity--Impulsivity dimension which has been seen as parallel in many ways to their Analytic--Non-analytic style (Kagan, Rosman, Day, Albert and Phillips, 1964; Kagan, Pearson and Welch, 1966; Schwebel and Bernstein, 1970; Messer, 1970; Drake, 1970; and Milgram, 1970).

To summarize, Kagan and his associates have demonstrated the existence of cognitive style along the Analytic--Nonanalytic (Relational) dimension. These predispositions were demonstrated to generalize to various personality characteristics and other areas of performance. The Reflectivity-Impulsivity dimension paralleled the Analytic--Non-analytic one. Analytic--Non-analytic cognitive style appeared relatively stable over time but was subject to the influence of age and sex.

Before leaving this discussion of Kagan and the

Analytic--Non-analytic dimension, one important experiment (Yeatts and Strag, 1971) is here reviewed in detail, The study is important because it challenged the unidimensionality of cognitive style and supplied the basis for the hypothesis regarding flexibility of style which was investigated in the present study.

The study investigated the relationship between an

individual's ability to behave flexibly, that is, to shift cognitive style, and his academic achievement. One hundred and twenty-one fourth- and sixth-grade students were tested










on Kagan's CST and the California Achievement Test (CAT), The only difference from standard procedure was in Kagan's CST. The subject was given 45 seconds on each of nineteen test items and instructed to arrange the materials in as many ways as he was able. In scoring this test, the subject's first answer identified his cognitive style preference. He was also given a flexibility score according to the number of times he changed his cognitive style in the successive classifications. The results indicated that regardless of cognitive style preference or grade level, flexible subjects performed at a higher level of achievement. Furthermore, of the 31 subjects who were scored inflexible, 25 were at least six months below grade level,

6 at grade level and none above. Review of Literature Linking

Conservation and Cognitive Style

This section of the review of the literature again-begins with the question, "What is it that helps a-child to acquire conservation ability?" Ten theoretical models for conservation were cited to see what answers they offered and research attempting to train children to conserve was reviewed in hopes that they could identify experiences or individual differences that facilitated transition from nonconservation to conservation. Experiences or individual differences that could explain the appearance of conservation ability in all children were not found,










Taking a cue from Smedslund's observation that different children were helped by different training procedures and from evidence that early conservers did share some particular characteristics, attention was turned to cognitive style--one way of measuring individual differences. Perhaps cognitive style played a role in what helped a child acquire conservation ability. The two dimensions of cognitive style that Witkin and Kagan and their associates have researched were reviewed.

The present study was not the first to look for relationships between cognitive style and conservation ability (or performance on classification tasks--a prerequisite for conservation according to Piaget). The research of three investigators (Peters, 1970; Garrettson, 1967; and Orpet and Myers, 1970) who have explored these relationships is reviewed here. Since these investigations were central to the rationale behind the hypotheses of the present study, they are reviewed in detail.

Peters (1970) investigated the effectiveness of three methods of reversibility training on number conservation:

(a) non-cued discovery, (b) perceptual cue-guided, and (c) verbal rule instruction under several conditions. The subjects, 131 predominantly lower socioeconomic class kindergarten children, were pretested on cognitive style. This measure was derived from a 25-object sorting task published by Educational Testing Service. The subjects were randomly










assigned to the three experimental groups and a control group. The non-cued group established equivalence between two sets of items 12 times in two training sessions utilizing wooden blocks. These blocks offered no cues that the child could use to infer one-to-one correspondence. The perceptual cue-guided group experienced a training procedure identical to the first, but the blocks had color and dominodot cues. The verbal rule instruction group had materials and procedures like the first again. But, this time a statement of the rule, that is, the logical reason for conservation, was given following the completion of each transformation. At posttest, the means of all three training procedures were significantly higher than the control group. The verbal rule group was significantly higher than either the perceptual cue-guided or non-cue discovery groups. These two did not differ significantly. In a delayed posttest, however, both the perceptual cue-guided and verbal rule instruction groups were superior to the control and did not differ significantly from each other. The best predictor for number conservation performance on pre-and posttests was the subject's age. This was followed by language comprehension and analytic cognitive style. The last finding was evidence that there was a relationship between cognitive style and conservation ability.

Some of the reasoning the author included in his conclusion is pertinent to the present study. Since the cognitive style pretest was a measure only of the preferred way a










child perceived and organized his environment, it did not reflect an inability to organize things other ways. Peters reasoned that the training may have forced the non-analytic subjects to relinquish their preferred style and to adopt the analytic stance in the experimental situation. This meant that the ability of the subjects to be flexible in cognitive style may have enabled them to take advantage of the analytic cues offered in the training procedure, regardless of the style preference they showed on the pretest, and helped produce the positive experimental results. This was evidence that flexibility of cognitive style was related to conservation ability.

Garrettson (1969) tested 60 seven-year-old, secondgrade, suburban, public school boys on three Piagetian classification tasks. Kagan's CST was administered to assess the subjects' cognitive style. Almost all of the subjects proved to be transitional between preoperations and concrete operations. No significant correlations were observed between the use of analytic style on Kagan's test and the subjects' performance on the Piagetian tasks. This evidence did not agree with that of Peters (1970), but the instrument used to measure cognitive style was different and one also had to assume that a relationship with classification ability would be like a relationship with conservation ability. Despite the fact that classification abilities have been considered by Piaget to be prerequisite to conservation ability, such an assumption was a risky one.










Part of the author's discussion of this study included the hypothesis that paying attention to fine perceptual details (Kagan's analytic style) is associated with superior classification behavior only when it is used in conjunction with attention to the part-whole or hierarchical aspects of the classes. This was evidence that flexibility of cognitive style related to classification ability--and possibly to conservation ability.

A study by Orpet and Myers (1970) of 133 first- and second-grade, middle-class subjects produced a discriminant function analysis of conservation stages by structure of intellect and cognitive style variables. The test battery, totaling 22 variables, included conservation of liquids tasks, structure of intellect tests and a cognitive style test. Chronological age was also a variable. Cognitive style was determined by the Descriptive part-whole, Descriptive-global, Relational-contextual and Categoricalinferential scores on the SCST (Sigel, 1967). The subjects were scored in one of three stages of conservation according to their persistence of judgment. The subjects were rated as nonconservers, transitional conservers or consistent conservers.

The results did not discriminate transitional conservers from consistent conservers. The variables best discriminating nonconservers from transitional conservers, in order of strength, were (a) Wechsler Intelligence Scale for










Children (WISC)--picture arrangement, (b) Nebraska Picture Associations, (c) Knox cube tapping, (d) Descriptiveglobal style, and (e) chronological age. Of importance for the present study was the finding that Descriptive-global scores discriminated the more successful conserver. This was evidence for a relationship between cognitive style and conservation ability. Since Orpet and Myers' research used the same instrument to measure cognitive style as the present study used, the results were the most supportive of the three studies cited here for this paper's hypotheses.

The present study, therefore, did not explore the unknown. Peters (1970) found analytic style related to number conservation. Descriptive-global style predicted conservation of liquids ability in a study by Orpet and Myers (1970). Garrettson (1969) looked for relationships between cognitive style and Piagetian classification tasks. No relationships were found. This could have been-seen as contradic-M tory evidence only if one assumed that the ability to 7 classify was intimately connected to the ability to conserve. Some of the reasoning in the discussion sections of the studies by Peters and Garrettson suggested relationships be-. tween flexibility of cognitive style and conservation and classification. These studies provided empirical support for research into the role of cognitive style in the acquisition of conservation ability.










Rationale

This investigation sought to answer the question, "What is it that helps a child acquire conservation ability?" The review of the literature presented answers that others offered through their theoretical models and training methods. The present study hypothesized another answer--that preference and flexibility of cognitive style play a role in the ease with which a child becomes able to conserve.

There were reasons why this answer was a likely one.

The rationale behind the hypotheses used supporting evidence from three areas: (a) evidence which indicated a relationship between preference in cognitive style, that is, which style categories were used most frequently thrcughout all test items, and conservation ability, (b) evidence which indicated a relationship between flexibility in cognitive style, as measured by the frequency of successive style alternations in multiple responses on each test item in a cognitive style test, and achievement, and (c) observations of experimenters which suggested a relationship between flexibility of cognitive style and conservation ability. The specific experimental results and research that pertained to each of these three areas are cited below:

1. Using the SCST (Sigel, 1967), Orpet and Myers (1970) found Descriptive-global style preference to be a reliable basis for predicting a child's ability in conservation of liquids. Peters (1970) obtained a measure of cognitive










style from an Educational Testing Service (1968) sorting task. He found analytic style to be a significant predictor of number conservation ability, Using Kagan's CST, Garrettson (1969) found no relationship between analytic style and success on Piagetian classification tasks. Success on such tasks has been described as a prerequisite to conservation according to Piaget. Two of these three experiments (Orpet and Myers, 1970 and Peters, 1970) succeeded in finding a relationship between cognitive style preference and conservation ability. The third (Garrettson, 1969) did not find cognitive style relating to her criterion variable. But, since classification ability was tested rather than conservation ability, her results were not as directly applicable. There was an ambiguity between the two experiments that obtained positive results. Orpet and Myers (1970) found Descriptive-global style to relate to conservation and Peters (1970) found analytic style to relate, This may have been a plain inconsistency, or it may have been that each of these two different cognitive styles related specifically to the particular conservation ability tested in each experiment.

Despite the ambiguity, these experiments suggested a relationship between cognitive style and conservation ability. Discriminant function analyses and correlational studies such as the ones cited above did not show that cognitive style caused conservation ability. Nevertheless, a









more adequate answer to the question of what it is that helps a child conserve appeared likely through further research into the demonstrated relationship.

2. There was evidence that flexibility of style was as important a characteristic as style preference. Flexibility of style referred to a subject's tendency to alternate style on successive choices within each item on a cognitive style test. Using chi-square and multiple correlation analyses, Yeatts and Strag (1971) were able to demonstrate that shift, or flexibility, in cognitive style was significantly related to academic achievement. Flexibility of style was obviously an important individual characteristic of children with consequence for their intellectual functioning. Since this was true for academic achievement, it was reasonable to hypothesize a relationship between flexibility of cognitive style and conservation.

3. The proposed relationship between flexibility of cognitive style and conservation ability was supported by research evidence. The link between flexibility of cognitive style and conservation came from three sources (Halford, 1970b; Peters, 1970; Garrettson, 1969). Halford (1970b) proposed that it was the "constraint" between more global quantitative cues and more discrete height and breadth cues that had to exist before conservation judgments were possible. It was reasoned here that the ability to perceive flexibly, to see things one way and then another, favored










the attention to such "constraint" between cues. Peters' (1970) experiment included a training procedure for number conservation. In discussing the results, he suggested that the kind of experience provided in his training procedure forced all subjects to focus on analytic cues and drop whatever preferences were shown on a style pretest. Ability to be flexible in style, and thus to use the analytic style cues offered in his training procedure, may have contributed to his positive results according to Peters, Garrettson (1969), who found no significant correlation between the subjects' use of analytic style and their performance on Piagetian classification tasks, proposed that paying attention to fine perceptual details, characteristic of analytic style, was associated with superior classification behavior only when it was used in conjunction with attention to the part-whole or hierarchical aspects of the classes. Flexibility of style would have lent itself to the recognition and use of such a broader spectrum of cues.

Halford's (1970b) "cue constraint" model and Peters'

(1970) and Garrettson's (1969) investigations offered strong evidence for a relationship between flexibility of cognitive style and conservation ability.


Hypotheses

Strong evidence for a relationship between cognitive style preference and conservation ability was produced by Orpet and Myers (1970), Peters (1970) and Garrettson (1969),










The results of Yeatts- and Strag's (1971) investigation, the discussion offered by Peters (1970) and Garrettson (1969) and implications from Halford's (1970b) model clearly indicated a relationship between style flexibility and conservation ability. It was, therefore, proposed to analyze the relationships between cognitive style preference and flexibility and conservation. On the basis of the supporting evidence, the hypotheses were:

1. There will be a significant relationship between preference of cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability.

2. There will be a significant relationship between flexibility of congitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability.


Summary

The purpose of this study was to investigate the relationship, if any, between preference and flexibility of cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance, and weight conservation tasks. Considerable literature was reviewed in an attempt to explain the transition from nonconservation to conservation. Studies that offered evidence for relationships between preference of cognitive style and conservation ability, flexibility of






47



cognitive style and achievement, and flexibility of cognitive style and conservation ability provided a rationale for hypothesized relationships.
















CHAPTER II


METHOD AND PROCEDURES


Sa2le
A sample of 37 first-grade, middle-class, suburban boys (almost the entire male population from that group at Lime Street Elementary School, Lakeland, Florida) was used. Such a sample was chosen because a review of the literature revealed that conservation ability had been affected by urban-rural residence, socioeconomic class and sex. Socioeconomic class and sex have been shown to affect cognitive style. Limiting the sample in the above manner limited the generalizability of the results, but helped control variance. Judgments about the subjects' urban-rural location and socioeconomic class were made on the basis of residence and vocation of the head of the house. These judgments were made in consultation with the principal.


Instrumentation

The Peabody Picture Vocabulary Test (PPVT) was administered to all subjects. This test was chosen to obtain an IQ measure because it could be quickly and easily administered and because verba. subscores have been generally the most highly correlated with overall IQ scores (Terman and 48










Merrill, 1937; Wechsler, 1949). Buros (1965) reported alternate form reliability at .77 at the six-year level for the PPVT. Intertest correlations were also reported between the PPVT (Form B) and the CTMM, Henmon-Nelson Tests of Mental Ability, the Stanford-Binet (S-B) and the WISC. These ranged from .58 to .80.

The SCST, Form M (1967) was administered to all subjects. The SCST consists of a set of 21 cards, each with three black and white drawings/photographs of familiar objects. Each child was asked to pick out two pictures that "go together, belong together, or are related in any way" and to state the basis for his sort. These stimuli were constructed to elicit Descriptive part-whole, Descriptiveglobal, Relational-contextual and Categorical-inferential concepts. Descriptions of these categories (as Sigel defines them in the SCST Manual) appear in Appendix A, Testretest and split half reliability has varied from .60 to .80 according to Dr. Irving Sigel (personal communication, February, 1972).

Davis (1971)� reported a mean test-retest reliability coefficient of .66 for Form A of the SCST when it was administered to fifth, eighth, and eleventh graders and college students. At the fifth-grade level (closest to the age of the sample in this study) the coefficients were between .67 and .87 on the four major style categories.










Standard tasks of number, length, substance and weight conservation were also administered to all subjects. The precise procedure and materials for each are described in the Procedure section.


Assistants

Nine volunteer, undergraduate students from an educational psychology class at Florida Southern College, Lakeland, Florida, were used as assistants. Two females administered the Peabody tests. They were trained by the school principal for several days before the testing was begun. Six males administered the SCST and conservation tasks. They were trained by the author of the present study for several sessions and practiced on non-sample children before testing was begun. Not all the male students tested the same number of children. But, effects due to the tester should have been negligible since all the subjects were randomly assigned to the assistants for testing. Male assistants were used to control for sex differences among the examiners affecting the subjects differently. The two females and the seventh male assisted in collecting the data.

Two students from a child psychology class at Valencia Community College, Orlando, Florida, also assisted with this study. One, a female, was trained in Smedslund's categories of justification for conservation by the author of the present study. When an interrater reliability between her and










this author reached 92 percent agreement on practice responses, she scored the justification portion of the conservation tests. The student and this author obtained 96 percent agreement in scoring the subjects' justifications. The second student, a male, was trained by the author in scoring the SCST. When an interrater reliability between him and the author of this study reached 80 percent agreement on practice responses, he scored four randomly chosen responses on the SCST for each subject. The student and this author obtained 84 percent agreement in scoring. One difficulty was encountered. Neither the student nor the author was able to satisfactorily distinguish between Relational-contextual

1 and Relational-contextual 5 style categories, As a result, they were combined in the data collection. This was not considered much of a loss in precision of measurement since the SCST Manual published with the test states, "Because of the low frequency of some of these, all Relationalcontextual subcategories can be combined for analysis."


Procedure

During the first two weeks of the testing, all subjects received the PPVT. The procedures outlined in the test Manual were followed carefully.

During the third week, the SCST, Form M (1967) was administered to all subjects. The experimenter (student assistant) sat across from the subject at a table and showed









the cards to the subj.ect one at a time. In addition to the standard experimenter's instructions for the SCST, the subject was invited to find as many ways as possible in which any two figures go together. The experimenter said, "Can you do that in another way?" after each subject's response. The subject was given forty seconds for responses, Style preference was recorded in two ways: (a) the subject's first response to each new stimulus and (b) total frequency of responses in each style category. Successive responses to the same item were analyzed as to sameness or difference of cognitive style and a flexibility score given. The flexibility score was the percentage of total categorizable responses in which there were successive alternations in styles. Only shifts in style within the responses to each test item (not including shifts between the last response of one item and the first response to the next item) were counted. . .. . - .

During the fourth and fifth weeks, the conservation tasks were administered. In the conservation of number tasks, the subject was presented with two parallel rows of pennies of equal length, six pennies in each row, arranged in one-to-one correspondence. The experimenter and subject counted the pennies in the experimenter's row and the subject's row to establish equivalence, The experimenter's or subject's row was lengthened or shortened (alternating these features from subject to subject) and the subject was










then asked whether he had more, less, or the same number of pennies as the experimenter. An explanation of the judgment was asked. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you sure that you really have the same number as I do?" The subject's responses were recorded according to correctness, symbolic-logical explanation or not and persistence to countersuggestion.

The conservation of length task consisted of two sixinch sticks placed parallel to each other and side by side in such a way that their ends coincided. The subject was asked whether the experimenter's stick and the subject's stick were the same length. After equivalence had been established, the subject's stick or the experimenter's stick (alternating by subject) was then moved so that its end extended one inch beyond the other and the subject was asked whether his stick was longer, shorter or the same length as the experimenter's. An explanation of the judgment was asked. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you 3ure that your stick is the same length as mine?" The subjects' responses were recorded according to correctness, symbolic-logical explanation or not and persistence to countersuggestion.

Two small Play-Doh balls of the same color and

equivalent to all other properties were presented to the










subject in the test for conservation of substance. The subject was asked whether they both had the same amount of clay. Small portions were added or subtracted if necessary until the child agreed on their equivalence. One was considered the experimenter's and one the subject's. One of the balls (alternating by subject) was then flattened into a pancake shape by the experimenter. The subject was asked whether his had more, less, or the same amount of clay as the experimenter's. An explanation was requested. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you sure yours has the same amount of clay as mine?" The subject's responses were recorded in terms of their correctness, symbolic-logical explanation or not and persistence to countersuggestion.

The conservation of weight task was similar to the

substance task. Initial equivalence was asserted with the help of a balance scale. Clay was added or subtracted, if necessary, to establish equivalence. All the questions related to weight instead of amount, but scoring was the same.

In scoring the conservation tasks, the subject was

awarded one point for each correct judgment, one point for each symbolic-logical explanation and one point for each survival to countersuggestion, This produced possible scores for each subject from 0 to 12. Sequence of conservation tasks was varied randomly to control for order effects.










All testing was done in four rooms made available by

the school for the purposes of this study. Conditions were not identical for each of the subjects, but as close as possible. All sessions of cognitive style and conservation testing were tape recorded. The children's responses were transcribed off of the tapes and ultimately onto forms printed for the purpose of recording the data, This procedure was chosen because it eliminated the distraction and difficulty of a recording person in the test situation and also provided a more accurate transcription of the child's responses. The experimenters (student assistants) called for each subject from his classroom, walked with him to the testing room, being casual and friendly but not overly solicitous, tested him, walked him back to the classroom, called for the next subject, etc. The boys came from four first-grade rooms and were called for and tested in random order.

The literature indicated that error had come from

variables such as varying desirability of materials (Roll, 1970), varying task complexity (Fiegenbaum, 1963), anxiety due to the strangeness or threatening nature of the test situation, unintentional reinforcement of the experimenter to the responses of the subject--perhaps somehow turning the conservation testing procedure into a training procedure, among other dangers. The test materials were designed with a sensitivity to the problems of stimulus desirability and










task complexity, and it was believed that those factors were not sufficient to affect the results. The experimenter and assistants attempted to create a test situation which was warm and allayed fears without becoming too personal or producing unintended reinforcement.


Data Collection and Analysis

THE PPVT IQ's were recorded directly on the scoring

sheets provided with the test Manual and booklets. The age of each subject was recorded here in years and months and later converted into months for the analyses.

Cognitive style tests were tape recorded. All responses were then transcribed verbatim onto sheets printed for that purpose by the author. The responses were then scored independently by this author and the student with whom interrater reliability had been established. The results for each subject were tabulated. Preference according to initial preference (first response for each item) was tabulated in two ways: (a) by major categories and (b) by the 20 substyle categories. Flexibility (successive alternation or shift in style within each test item) was tallied in two ways: (a) shift between the four major categories and (b) shift between the 20 substyle categories.

The four major categories in the SCST are: Descriptive part-whole (DPW), Descriptive-global (DG), Relationalcontextual (RC), and Categorical-inferential (CI). It










should be remembered that only 20 substyle categories appear in the data because two substyles, Relational-contextual 1 and Relational-contextual 5, were combined in the statistical analysis.

The conservation task sessions were also tape recorded and all the children's responses were then transcribed onto forms printed for the recording of these data. The justification responses were then scored independently by this author and the student with whom interrater reliability had been established. The results for each student were tabulated. The number of points awarded for conservation on all four conservation tasks, the number of points for symbolic-logical justification on conserving judgments and the number of points given successful resistance to countersuggestion and extinction were noted. A total, composite score was then figured.

At the conclusion of the data collection, there were scores on each subject for: I. Cognitive Style
A. initial preference on four major styles
B. total preference on four major styles
C. initial preference on 20 substyles
D. total preference on 20 substyles
E. flexibility of style between major categories
F. flexibility of style between all categories
G. fluency
II. Conservation--composite scores for all points on all
tasks

III. PPVT IQ

IV. Age in months










This information was then punched onto data cards. The data were analyzed using regression techniques, To screen the data and reduce the number of independent variables, discriminant function analyses were completed. Then, a multiple regression analysis was completed on the variables which proved of value in the discriminant function analyses. The multiple regression analysis identified the combination of independent variables with the most power for predicting a subject's conservation score.

Stepwise discriminant function analyses were run using the BIOMED 07M program. The results of a discriminant function analysis indicate to a researcher whether any of the data he has for his subjects are useful in predicting to which of two or more groups the subjects belong. In the present study, theyindicated the usefulness of cognitive' style preference and/or flexibility, fluency of response, PPVT IQ, and age for predicting whether each subject was a conserver or a nonconserver. The stepwise portion of the analysis indicates which variable is the most powerful in predicting group membership; and then, in order of predictive power, which further variables, in combination with those already entered, are most helpful. Membership in the conserving or nonconserving group was the dependent variable (the one to be predicted) in all five analyses. The independent variable was the score on some characteristic of the subject (e.g., cognitive style preference) that was hypothesized to relate to or predict the dependent variable.










The subjects were divided into two groups for purposes of the discriminant function analyses--conservers and nonconservers. A total of five analyses were completed. The first analysis used initial preference scores on each of the four major style categories as the independent variable; the second, initial preference scores on the substyle categories; the third, total preference scores on each of the four major style categories; the fourth, total preference scores on the substyle categories; and fifth, an analysis was done using the two flexibility scores, PPVT IQ, age in months and fluency (total number of categorizable responses) as the independent variables.

The independent variables that demonstrated power in the discriminant function analyses were used in a multiple regression analysis. This analysis was run using the BIOMED 02R program. The results of a multiple regression analysis indicate to a researcher whether there is a combination of independent variables that will predict (when entered into an equation) the score of each subject on the dependent variable. In the present study, they indicated a combination of measures of cognitive style that, when entered in a regression equation, predicted at a statistically significant level the conservation scores of the subjects.
















CHAPTER III


RESULTS


The conservation scores were bimodally distributed.

Most of the subjects clustered around either low scores or high scores and few were in the middle. Twenty-three subjects scored between 0 and 5 points on the composite conservation score. They were classed as nonconservers. Thirteen subjects scored between 7 and 10 points, They were classed as conservers. One subject who scored 6 points was dropped. No subjects scored 11 or 12 points. The distribution of conservation scores is shown in Figure 1.

A total of five stepwise discriminant function analyses were completed using the BIOMED 07M program. --he first analysis used initial preference scores on each of the four major style categories as the independent variable;- the second, initial preference scores on the substyle categories; the third, total preference scores on each of the four major style categories; the fourth, total preference scores on the substyle categories; and fifth, an analysis was done using the two flexibility scores, PPVT IQ, age in months and fluency as the independent variables.























71








4 �


31
T%


Figure 1. Distribution of Conservation Scores


1 2 3 4 5 6 7 8 9 10
Composite Conservation Scores










In those cases in which a substyle category was never used by any conserving or nonconserving subject, that variable was omitted from the analysis in which it occurred. This prevented artificial relationships from appearing. Using such variables would have meant that points (0.0) would have been entered into the equation rather than measures of variance. As a result, six variables were dropped from the discriminant function analysis using initial preference for the independent variable. Two variables were dropped from the analysis that used total perference.

The approximate multivariate F values of all independent variables in predicting the conservation classification of the subjects are presented in Table 6. In each instance, the variables are listed in the order in which they were stepped into the equation. The numbers of conserving and nonconserving subjects who were classified as conservers and nonconservers on the basis of the variables entered into the equation at each step are also reported in Table 6.

The only independent variable that demonstrated statistically significant power was initial preference on the substyle categories. With four variables entered, the .05 level of significance was reached. Optimum power for classifying (p <.01) was obtained from an equation in which seven variables had been stepped. Therefore, a multiple regression analysis was performed on these data. The BIOMED 02R program was used. The fourteen variables that were analyzed in










Table 6

Stepwise Discriminant Function Analyses


(1)
Q) 0
(0 -4q
.4
�-4 '
0
P 4J


rt,
a)
-4
44 .4

o


U) ( 0 0


UU 0 0

Ocn


U -4 .0)


U04-)
-1 M(
-4 3

-H4-4
m )0


Initial Preference


Major Styles


Substyles


NS NS NS
S (p<. 05) S (p<.05) S (p<.05) S(p<.01) S (p<. 01) S (p<. 01) S (p<. 01) S(p<.05) S(p<.05)


a)

-Hi 0)
-,4 4m r


-4
44 .4

C')
>
U


0)0 U d


o n


ro
-4
44
-E4

>

4
)o
(Do >0 0) 0
U) z


DPW CI RC DG


2.7478 2.1624 1.7140 1.6333


1,34 2,33 3,32 4,31


RC2 DPW1 RC1&5 RC6 DG7 C12 DG5
RC4 C14 C16 DG4 DPW2


2.6122 2.5159 2.6923 2.9904 3.4366 3.5058 4.1207 3.7995 3.4499 3.2106 2.8764 2.5535


1,34 2,33 3,32
4,31 5,30 6,29 7,28 8,27
9,26 10,25 11,24 12,23










Table 6 (continued)


01)
(13 d
-4 C)
-H 40)


PZ4
Q)
4J It

-H M~ o >H 04 "1P ir4


13 DG6
14 CII


2.2586 2.0040


13,22 14,21


S (p<. 05)
NS


Total Preference

Major Styles


1 CI 2.6280


DPW DG RC


1.5542 1.1137 .8160


1,34 2,33 3,32 4,31


Substyles


RC2 C17 RC6 C16 C15
C14 DG4 DPWI DG7
DG5 RC1&5 RC4


3.4434 2.7494 2.4997 2.6076 2.5180 2.1683 1.9178
1.7310 1.6327 1.5292
1.4148 1.4144


1,34 2,33 3,32 4,31 5,30 6,29 7,28 8,27 9,26 10,25
11,24 12,23


0)

z 0



-r-4 44 c o


4-4



0)



0D)0 o w
tUr(a










rable 6 (continued)


a)


DPW3
*r4 4i)



DPW3 C12 RC 3 C1I

DPW2 DG6


4, .i)


X > O-4 C1

4X


1.3581 1.2930 1.2595 1.1265 1.0072 .9001


1 Fluency
2 Flexibility
between
all
styles
3 Peabody
IQ
4 Age in
months 5 Flexibility
between
major
styles


.8798 .6717




.4787 .3636 .2815


Other 1,34 2,33




3,32 4,31 5,30


Variables
NS NS




NS NS NS


14 9 4 9


10 13 10


12 11 8 5 12 11 9 4 12 11 9 4


-1
44

,4
a)
U 4 C>
a)0 >Cn


tn)
0 0 otz
Z
z 0


r4



rd .H

-4 4-4

U) 0


-4
44 .-4

,n>
U


W
r4 Ct)


c~i
> M lU U (d


13,22 14,21 15,20 16,19 17,18 18,17










the discriminant function analysis using initial preference on substyle were entered into the multiple regression analysis. The dependent variable was conservation score. The results of this analysis are presented in Table 7. Conservation scores were predicted at the .05 level with two variables entered. With seven variables entered, maximum power (p <.01) was obtained. The means and standard deviations of all variables are presented in Table 8.

In summary, the subjects' conservation scores were bimodally distributed. This distribution allowed reasonable division of the subjects into conservers and nonconservers. Five stepwise discriminant function analyses were completed. These tested the power of initial cognitive style preference, total style preference, style flexibility (measured in two different ways), PPVT IQ, age, and fluency in predicting the classification of the subjects as conservers or nonconservers. The results of these are presented in Table 6. Significant results were produced when initial preference was used as the independent variable. A multiple regression analysis was performed on the fourteen measures on this variable and the dependent variable, conservation score. The results of the multiple regression analysis are reported in Table 7. With seven variables entered into the equation, optimum power was obtained. The variables that were able to predict the subjects' conservation scores were measures of the subjects' tendency to pair the pictures in the item on the SCST







Table 7

Stepwise Multiple Regression Analysis


Step
1

2 3 4 5 6 7 8

9 10 11

12 13 14


Table 7 Stepwise Multiple Regression Analysis


Variable
RC4 DG5

C12 DG7 RC1&5 RC6 DPWI DG6 RC2 DG4 C16 C14 DPW2 CIlI


F
3.242 3.507 3.167 3.236 3.085 3.583

4.010 3.758 3.484 3.122 2.799 2.515 insuff. insuff.


df 1f34

2,33 3,32 4,31 5,30

6,29 7,28 8,27 9,26 10,25 11,24 12,23


Significance
NS

S (p<.05) S (p< .05) S (p<.05) S(p<.05) S (p<.0l) S (p<. 01) S (p<. 01) S (p<.0l) S(p<.05) S (p< .05)

S (p<.05)


Multiple
R
.2950 .4187 .4785 .5427 .5827 .6525 .7075 .7259 .7394 .7454 .7496 .7533


Correlation
with
Conservation
-.295

-.270

+.232 -.074

+.031 -.214

+.201 -.260

.223

-.258

+.059 +.240 +.275

+.092









Table 8

Means and Standard Deviations


Variable Nonconservers Conservers

Mean Std.Dev. Mean Std.Dev.

Initial Preference

DPW 3.609 3.340 5.538 3.382 DPWI 1.522 2.274 2.385 2.631 DPW2 2.087 2.130 3.000 1.871 DPW3 0.000 0.000 0.154 0.376 DG 2.304 2.285 1.769 1.013

DG4 0.391 0,583 0,308 0.480 DG5 0.696 1.550 0.538 0.519 DG6 0.565 0.728 0,462 0.776 DG7 0.652 0.935 0.462 0.877 RC 4.130 3.321 4.615 3.404

RC1&5 2.304 2.363 3.462 2.634 RC2 0.217 0.518 0,538 0.660 RC3 0.043 0.209 0.000 0.000 RC4 1.087 1.345 0.462 0.877 RC6 0.391 0.656 0,154 0,376 RC7 0.087 0.288 0.000 0.000 CI 3.478 2.810 5.000 2.345 CIl 1.957 2.078 2.231 2.127 C12 1.000 1.314 1.615 1.387 C13 0.000 0.000 0.077 0.277 C14 0.304 0.635 0,615 0,870










Table 8 (continued)


Variable


DPW DPW1 DPW2 DPW3 DG

DG4 DG5 DG6 DG7 RC

RC1&5

RC2 RC3

RC4 RC6 RC7 CI CI1 C12


Conservers
Mean Std.Dev.

0.154 0.376 0.308 0.480 0.000 0.000


CI5 C16

C17


Nonconservers Mean Std.Dev.

0.000 0.000 0.217 0.671 0.000 0.000 Total Preference

6.304 7.600 2.348 3,511 3.870 4.605 0.087 0.417 3.043 3.843 0.435 0.590 1.174 3.525 0.070 0.876 0.739 1.096 9.087 1.774 5.348 6.135 0.217 0.518 0.043 0.209 2.304 4.061 1.087 1.782 0.087 0.288 5.217 4.199 2.870 3.065 1.478 1.780


7,782

4.231 4.723 0.376

2.066 0.660

0.630 0.630 1.121 8.122 5.576 0.768 0.277

2.287 0.967

0.000 3.573 2.983

2.421


9.308 3.308 5.846 0.154 2.462 0.462 0.692 0,692

0.615 8.846 6.385 0.615 0.077 1.308 0.538 0,000

7.461 3.308 2.231










Table 8 (continued)


Variable


C13

C14

CI5

C16

C17

Flexibility Between
Categories

Flexibility Between
and Within Categories

Conservation Score PPVT IQ Age in months Fluency Number of Different
Styles Used


Nonconservers Mean Std.Dev.

0.000 0.000 0.435 0.662 0.140 0.458 0.435 0.896 0.043 0.209 12.261 11.001


19.348



2.261 106.348 80.783 23.217 6.83


18.059



1.814 19.242 4.502 16.251 3.01


Conservers

Mean Std.Dev.

0.077 0.277 0,692 0.947 0.154 0.376 0.769 0.927 0.231 0.439 12,462 8.705 19.077 13.219


8.538 111.000

80.538 28.000

8.85


1.050 18.102 3.526 11.299 2.23






71



on the basis of comparison between figures (RC4), age categories (DG5), common role or attribute (12), age and sex (DG7), thematic interaction or interdependent function (RCl & 5), family and other relationship (RC6), and physical attributes (DPWI). The means and standard deviations of all variables are reported in Table 8.
















CHAPTER IV


DISCUSSION AND CONCLUSION


To aid the reader in following this discussion, a brief, descriptive caption for each subcategory, followed by the symbol, has been used as the subcategories occur in the text, The caption refers to the category of reason a subject gave for pairing two of three pictures presented in each item on the SCST. For a fuller description of each category, the reader is referred to Appendix A. First Hypothesis

The first hypothesis was: There will be a significant relationship between preference of cognitive style as measured by the Sigel Cognitive Style Test and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. Four stepwise discriminant function analyses were completed in testing this hypothesis. The independent variables were: 1) initial preference on the four major style categories, 2) initial preference on the substyle categories, 3) total preference on the four major style categories, and 4) total preference on the substyle categories. Neither analysis










using total preference produced statistically significant results. Likewise, the results of the analysis utilizing initial preference on the four major styles were statistically nonsignificant. There were statistically significant results, however, when initial preferences on the substyle categories were the independent variables,

The results are reported in Table 6. Statistically significant (p <.05) results were obtained in the fourth step of the analysis which employed initial preference on the subcategories as the independent variable. The four variables that were entered into the equation at that point were those which indicated the subjects' tendency to pair pictures on the basis of common locale (RC2), physical attributes (DPWl), thematic interaction or interdependent function (RCl & 5), and family or other relationship (RC6). The approximate multivariate F increased through the seventh step. At this step significance reached the .01 level and only six subjects were misclassified. The fifth through the seventh step added these three style categories: age and sex (DG7), common role or attribute (C12), and age (DG5). Stepping in further variables progressively lowered the approximate F value and correctly classified only two more subjects--even through the fourteenth step. Adding the next three variables--comparison between figures (RC4), common affect (C4) and inferred attribute or unseen part (C16)-did not change the level of significance. However,










significance dropped to the .05 level when the next three variables were entered: status or occupation (DG4), description of objects (DPW2), and sex (DG6). When the final variable, common behavior of function (CIl), was entered, the predictive power of the equation became nonsignificant. These results indicated that the subjects' membership in either the conserving or nonconserving groups could be predicted on the basis of the subjects' scores on seven substyle categories.

The variables useful in classifying subjects into two

categories, as the discriminant function analysis did, might not be the same as those that predict the subjects' conservation score, as a multiple regression analysis does. Said another way, comparing continuous data (style scores) with discontinuous data (conserving or nonconserving groups) might not produce the same results as comparing continuous data (style scores) with continuous data (conservation scores). The latter is to be preferred in answering the hypothesis of the present study.

In order to obtain the most powerful combination of

variables from the 14 substyle categories, these 14 measures and conservation score, the dependent variable, were placed in a stepwise multiple regression analysis, The results are reported in Table 7.

Seven of the first eight variables in the discriminant function analysis were the first seven in the multiple regression analysis; only the order in which they were stepped










into the equation differed. The variable that was entered first in the discriminant function analysis, common locale (RC2), was not entered until the ninth step in the multiple regression analysis.

The results of the multiple regression analysis indicated that an equation with only two independent variables, comparison between figures (RC4) and age categories (DG5), will predict the subjects' conservation scores at a statistically significant level (p <.05). The addition of four more variables raised the level of statistical significance to .01. These four were common role or attribute (C12), age and sex (DG7), thematic interaction or functional interdependence (RCI & 5) and family or other relationship (RC6). Entering one further variable, physical attributes (DPWI), to the equation, raised the F ratio considerably and accounted for a fair amount of variance. Adding more variables helped to account for very little additional variance and, after the tenth step, lowered the statistical significance to the .05 level. Two of the 14 variables, description of objects (DPW2) and common behavior or function (Cl), obtained an insufficient F for entry into the equation.

Therefore, as predicted in the first hypothesis, there was a statistically significant relationship between cognitive style preference and composite scores on several Piagetian conservation tasks. This relationship was










demonstrated between initial preference cognitive style scores and conservation scores. Of the variables entered in the first seven steps of the multiple regression analysis, all four major style categories were represented. Four of these variables were preferred by subjects with low conservation scores. These were comparison between figures (RC4), age categories (DG5), age and sex (DG7) and family or other relationship (RC6). Three of the seven variables were preferred by subjects with high conservation scores. These were common role or attribute (C12), thematic interaction or interdependent function (RCI & 5), and physical attributes (DPWI).

Patterns were identified among the major styles as they were represented by the subcategories used in the multiple regression analysis. One Descriptive part-whole variable, physical attributes (DPWI), appeared in the seventh step and was positively correlated with the dependent variable. _Two Descriptive-global variables, age categories (DG5) and age and sex (DG7), occurred in the second and fourth steps. Both correlated negatively with conservation score, The Relational-contextual major category appeared three times. Comparison between figures (RC4), thematic interaction or interdependent function (RCl & 5) and family or other relationship (RC6) were entered in the first, fifth and sixth step. Two of these, comparison between figures (RC4) and family or other relationship (RC6),were correlated negatively










with conservation score. Conservation correlated positively with thematic interaction or interdependent function (RCl & 5). One Categorical-inferential variable, common role or attribute (C12),was entered in the third step and was positively correlated with conservation score.

Summarized another way, positive relationships existed between subcategories from two major styles, Categoricalinferential and Descriptive part-whole and conservation scores. There were negative relationships between two subcategories of the Descriptive-global style and the dependent variable. The relationship of the subcategories within the Relational-contextual major category was ambiguous.

These results implied that one can predict a given subject's conservation score by his preferred use of the common role or attribute (C12), physical attributes (DPWI) and thematic interaction or interdependent function (RCI & 5) cognitive styles and by his infrequent use of age categories (DG5), age and sex (DG7), comparison between figures (RC4), and family or other relationship (RC6) styles. Furthermore, one can predict a subject's conservation score at a lower level of statistical significance (p <.05) on the basis of a subject's score on just two variables--his infrequent use of comparison between figures (RC4) and age categories (DG5).

Why was a combination of these particular styles capable of predicting what a subject's conservation score would be?










Was there something shared by C12, DPWl and RCI & 5 that a subject needed to use to be able to score high on conservation? Or, was there something shared by DG5, DG7, RC4 and RC6 that a subject needed to ignore to be able to score high on conservation?

C12, DPWI and RCl & 5 appeared an unlikely combination. One might have expected a clear preference of one style or another, but a combination of three of the four major styles was confusing. For a subject to choose the C12 category, he was grouping objects in the SCST on the basis of an inherent common role, class or attribute (e.g., both figures were animals, ways of transportation, tools, professional people, violent, juicy, etc.). When a subject chose the DPWI category, the basis for the grouping was the physical attribute or property of the materials in the pictures (e.g., color, texture, shading, shape). Sorts based on themes, plots or stories (e.g., he killed this man, she is giving him food, etc.) and sorts in which objects were grouped together on the basis of their interdependent use or function (e.g., the hammer is being used to bang the nail, ham and bread make a sandwich, etc.) were scored as RCl & 5 cognitive style. The tendency for a subject to prefer sorting on the basis of inherent, common characteristics (CI) or on the basis of observable parts of the stimulus (DPW) or on the basis of relationships (RC) was found to be statistically independent by Sigel. There was no reason for the










combination of these styles in a regression equation predicting conservation scores. The literature cited in this study did not provide an explanation for such results.

Was there something shared by DG5, DG7, RC4 and RC6

that a subject needed to ignore to be able to score high on conservation? In order to score on DG5, a subject sorted on the basis of discrete age categories (e.g., children, old people, adults, etc.). Sorting on the basis of age and sex (old men, young women, boys, girls) indicated a DG7 cognitive style. RC4 sorts were those based on a comparison between two figures (e.g., this one is better than that one) and RC6 sorts indicated grouping on the basis of an understood relationship between the figures (e.g., mother-son, doctor-nurse, teacher-student, etc.). There was no common quality between sorts based on the total objective manifestations of the stimuli (DG) and those based on relationships (RC). The literature cited in this study did not' provide an explanation for such results. .. .

In order to explain the results, the author attempted to discover the reason why the variables entered in the multiple regression analysis were able to predict the conservation score of the subjects. There was no explanatidn provided by the literature cited in the present study to support the results. The more frequent use of common role or attribute (C12), physical attributes (DPWI), thematic interaction or interdependent function (RCI & 5) and the










less frequent use of age categories (DG5), age and sex (DG7), comparison between figures (RC4) and family or other relationship (RC6) predicted a higher score on conservation.

Another observation about the results explained part of what happened. The correlations between the fourteen independent variables used in the multiple regression analysis and the dependent variable, conservation score, indicated a clear pattern. Descriptive part-whole styles and Categorical-inferential styles were consistently positively related to conservation score. Descriptiveglobal styles were consistently negatively related. The Relational-contextual style was ambiguous. A nonconserver preferred Descriptive-global styles and, to some extent, Relational-contextual styles. A conserver rejected the Descriptive-global style for Descriptive part-whole and Categorical-inferential styles, and to some extent, Relational-contextual styles. This suggested that the combination of variables entered in the multiple regression analysis may have been the result of the tendency for a subject who obtained a higher conservation score to choose a broader range of styles while rejecting the Descriptiveglobal style. Conversely, the subject who obtained a iower conservation score preferred the Descriptive-giobal style and used a more limited range of styles.

Additional evidence for this explanation was provided by a simple tabulation of the styles used by the conservers










and nonconservers (as. conservers and nonconservers were defined in the discriminant function analyses). This showed that the conservers used a mean of 8.85 different styles. This compared with a mean of 6.83 different styles used by nonconservers. No subject in either classification used more than 11 different styles (of the possible 20) in all his responses on the SCST. The tabulation indicated that 10 of the 13 conservers (77%) used between 8 and 11 different styles. Only 10 of the 23 nonconservers (43%) used that many different styles.

Another indication of the suggested distinction between conservers and nonconservers was found in the means of response frequencies tabulated according to initial preference. Of the 20 substyles which could be used by the subjects, 11 of them were preferred by the conservers, 8 by the nonconservers, and one was not used by either group of subjects. These means of response frequencies implied that nonconservers had fewer favorite styles and a more limited repertoire. Conservers, on the other hand, used more styles.

The total number of categorizable responses on the SCST was higher for conservers than nonconservers (Table 8). It was, therefore, possible that the preference for more styles that the conservers displayed was only a result of this higher fluency of response. Or, as suggested here, it may truly have been the result of a larger repertoire.










One explanation of the combination of independent variables (cognitive styles) that were entered into the multiple regression analysis to predict the dependent variable, conservation score, has been offered. Inasmuch as no literature cited in this study offered an explanation for the variables that emerged, another observation was made. This observation noted two things:

1) the pattern of correlations between independent and
dependent variables, and

2) the number of styles used by conservers in comparison to nonconservers.

Categorical-inferential and Descriptive part-whole styles were consistently positively related to conservation score. Descriptive-global was negatively related. Relationalcontextual was ambiguous. Conservers demonstrated a wider choice of styles.

Therefore, it was concluded that the results of the multiple regression analysis were a consequence of the tendency for subjects who scored higher on conservation to differ from subjects who scored lower by the increased scope of cognitive style used rather than by transition to a new but also limited repertoire.

This was also the response to the first hypothesis.

There was a significant relationship between cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. But, this significant









relationship was a result of the difference in number of styles used by low and high scorers on conservation rather than by a unique and contrasting set of styles used by the two groups of subjects.

What were the theoretical implications of the preceding discussion for the hypothesis that there would be a relationship between cognitive style preference and conservation ability? Several studies cited in the review of the literature found a relationship. Peters (1970) found that analytic style was the third most powerful predictor of number conservation abilities among kindergarten children. In an experiment with second-grade suburban public school boys, Garrettson (1969) did not find a relationship between the use of analytic style and Piagetian classification tasks. Orpet and Myers (1970) administered the SCST (1967) to 133 firstand second-grade middle class subjects and found Descriptiveglobal style the fourth most powerful variable in discriminating ability in conservation of liquids.

Both styles mentioned in the literature above as predicting conservation ability, that is, analytic style (Peters, 1970) and Descriptive-global style (Orpet and Myers, 1970) would find support for their results in the present study. The first study would find this support because of a positive relationship between Descriptive partwhole style and conservation ability and the second because of a negative relationship between Descriptive-global style and conservation scores.










The results of the present study did not indicate that one particular cognitive style preference related to conservation ability. It produced evidence establishing the role of cognitive style in conservation ability--if only a general expansion in the use of part-whole (analytical) and inferential styles and a decreased use of global style.


Second Hypothesis

The second hypothesis was: There will be a significant relationship between flexibility of cognitive style and intellectual maturity as measured by the composite conservation score. Flexibility of style was measured in two different ways: (a) flexibility of style as measured in an overall percentage of total responses that shifted between the four major style categories within each item on the SCST and (b) flexibility of style as measured in an overall percentage of total categorizable responses that shifted between the 20 substyle categories within each item on the SCST.

A stepwise discriminant function analysis was done

using the two sources of data and the results (Table 6) produced neither statistical significance nor mentionable trends. The number of shifts of style a subject made in responding to individual items on the SCST had no predictive value for classifying him as a conserver or nonconserver. In a tabulation of frequency of shifts (Table 8), the










mean score on both measures of flexibility did not differ by more than .3 between conservers and nonconservers. The correlation coefficient between these two measures of flexibility was .88 and appeared to carry the same meaning. A subject who shifted between major styles shifted in a like manner between the substyles.

What does this mean theoretically? The rationale behind the hypotheses cited theory and research which indicated the plausibility of a relationship between flexibility of cognitive style and conservation ability. Halford (1970b) argued that there must be "constraint" between available cues before a child can conserve. He must both discriminate the cues and see their compensatory relationship. Yeatts and Strag (1971) claimed that not only initial preference but also flexibility of cognitive style is associated with academic achievement. Peters (1970) found analytic sort related to number conservation, According to the same author, ability to be flexible in style may have contributed to the positive results of his training procedure. GarretCson (1969) did not find any significant relationships between analytic style and Piagetian classification tasks. But, she stated that paying attention to fine perceptual details was associated with superior classification when it was used in conjunction with attention to partwhole or hierarchical aspects of the classes. The present study did not support these research findings or the










rationale built on them. Discriminant function analyses attempting to identify conservers and nonconservers on the basis of flexibility of style did not produce significant results nor mentionable trends.


IQ, Age and Fluency

There were a number of other independent variables considered in this study. Some of the literature (Dodwell, 1960; Murray, 1968; Fiegenbaum, 1963; Goodnow and Bethon, 1966; Goldschmid, 1967) found that IQ related to conservation ability. Therefore, a PPVT was administered to all the subjects. Intelligence as measured by this instrument did not relate significantly to conservation ability (Table 6). A glance at the mean scores on IQ (Table 8) indicated conservers averaged less than five IQ points higher than nonconservers. With an N of 37, not much could be said on the basis of that difference. Since the IQ scores obtained by the researchers cited above were measures of more general intelligence, it could be that the PPVT IQ does not correlate very highly with conservation. Nevertheless, as mentioned in the Instrumentation section, the vocabulary subscores of the S-B and WISC correlate highly with the full scale scores of the PPVT. Also, congruent validity of the PPVT as reported in the Instrumentation section of this study is high. Nevertheless, for this study, IQ did not emerge as a significant predictor of conservation ability.










Another variable mentioned in the literature as predictive of conservation ability was age (Baptiste, 1969; Fiegenbaum, 1963; Goldschmid, 1967). This was controlled in the present study by selecting subjects in the same grade. Although it was expected that older children would be more likely to conserve than younger children, this didn't happen. The difference in the average age of the conservers and nonconservers was less than .3 of a month--and that was in the opposite direction than expected (Table 8). The F value obtained in the discriminant function analysis based on age in months was extremely low (Table 6).

The last variable to be discussed is a measure of the

total number of categorizable responses, or fluency, Yeatts and Strag (1971) found that fluency related to intellectual performance. In the present study the F obtained in a discriminant function analysis was nonsignificant.


Problems

The author of the present study found difficulties with the measures used for scoring. One difficulty was the manner in which conservation ability was assessed. The opportunity for variance provided by a total range of 0 - 12 inthe scores was less than optimal. Inasmuch as no child actually scored above 10, such opportunity was even less. When one looked over the results on the conservation tasks, it became apparent that the extinction procedure was not very powerful. Only in three instances did the conserving subject










fail to resist the countersuggestion in the extinction procedure. This means that only 8 of the possible 12 points on the conservation score distinguished between subjects. Also, since a composite score was used in the statistical analyses rather than separate scores on each of the conservation tasks, it was possible that relationships between one or another conservation task and cognitive style were masked by the composite score measurement,

There were problems associated with using the SCST at this age level. The pictures presented in the text booklet were so poor in their detail that some children were not able to recognize them. Particular difficulties were encountered with items 3, 6, 16, 19, 21, and 31, The reader is referred to Appendix B for descriptions of each of the test items. The photographs of a snake, monkey, old man and old woman, ham slice, nurse and melon were not recognized on a number of occasions.

A second problem with the use of the SCST at this age level was that some children could not articulate their choices and reasons. Numerous subjects would remain silent after pointing to their choices or would speak so indistinctly that their reason was incomprehensible. The experimenter often wished he knew what must have been in the child's mind but not on his lips. The letters of the alphabet were used as identifying marks for individual pictures in the test booklet. Some children used the










alphabetical sequence of these letters as the reason for their sorts. For instance, a child would have said, "L and M go together because L comes before M." Others sorted, offering reasons such as "they sound alike," "they look alike," or "don't know" and monotonously stuck with that until their 'ordeal' was over. Since there was no place in the test procedure to prompt or otherwise press the subject to alter his responses, there was no way out of this dilemma. Some children never caught on.

These problems with the use of the SCST on first-grade boys suggested that research into its validity and reliability with such subjects was necessary. Davis (1971) investigated the SCST using 23 items of Form A of the test. The Form M used in this study was a selection of those items from Form A that Sigel found best for male subjects. Davis administered the test to 120 students in the fifth, eighth and eleventh grades and in college. Test-retest reliability ranged from .35 to .87 when scoring was done according to response frequencies as it is in the current study, At the fifth-grade level, the reliability on the four major styles ranged from .67 to .86--all significant at the .01 level.

Problems were present in the item-response elicitation according to Davis. That is, some items of the test elicited only one or another style or inhibited the use of one or another style.

A tabulation of four of the ten troublesome items Davis (1971) identified was done with the data produced in the










present study. The items from the present study which were investigated were numbers 13, 14, 25, and 27, As Davis suggested, the responses were not elicited evenly, Item 13 did, as Davis found, elicit a larger proportion of Descriptive-global responses. Categorical-inferential responses were not exclusively produced by item 14, as Davis discovered, but much in that direction. Davis found that Descriptive part-whole responses were produced out of proportion on item 25. While that style occurred with high frequency on item 25, the notable discrepancy in the present study is between the complete lack of any Descriptiveglobal responses and the occurrence of 30 Relationalcontextual responses. Item 27 replicated Davis' finding of no Descriptive-global responses, but did not elicit a high proportion of Categorical-inferential responses as Davis had found. This check of only four items hardly serves to indict the SCST. Nevertheless, the support that Davis' findings for fifth graders has in the above data for first graders served to suggest the need for investigating the use of the SCST with first-grade children. Conclusion

The purpose of this study was to investigate the relationship, if any, between cognitive style as measured by the Sigel Cognitive Style Test (SCST) and intellectual maturity as measured by success on Piagetian number, length, substance, and weight conservation tasks. Building a










rationale on Halford's (1970b) model for conservation training and on experiments by Yeatts and Strag (1971), Peters (1970), Garrettson (1969), and Orpet and Myers (1970), this author hypothesized that there would be a relationship among cognitive style preference and/or flexibility and conservation ability.

Scores were obtained from 37 first-grade boys for cognitive style preference, flexibility and fluency; conservation ability; Peabody Picture Vocabulary Test (PPVT) IQ; and age in months. Four major categories of style in which the subjects could score were on the SCST: Descriptive partwhole (DPW), Descriptive-global (DG), Relational-contextual

(RC) and Categorical-inferential (CI). The four major categories contained 20 subcategories. These subcategories were indicated by an abbreviation for the major style plus a number (e.g., DPWI, RC4, etc.).

To screen the independent variables, stepwise discriminant function analyses were completed. The variables which demonstrated predictive ability were then used in a stepwise multiple regression analysis.

Cognitive style was scored according to initial preference (first response for each item on the SCST) and total preference (total frequency of responses in each style category). Statistically significant results (a=.0l) were obtained. Subjects' scores for their initial preference on two independent variables










accurately predicted their conservation score (p <.05). Those two variables were cognitive style categories that used comparison between figures (RC4) and age categories (DG5) as the basis for pairing items on the SCST. The best equation (p <.01) used a combination of seven variables. Those variables were cognitive style categories that used comparison between figures (RC4), age categories (DG5), common role or attribute (C12), age and sex (DG7), thematic interaction or interdependent function (RCl & 5), family or other relationship (RC6) and physical attributes (DPWl) as the basis for sorting. The Descriptive part-whole and Categorical-inferential style categories were positively related to conservation scores. Descriptive-global style was negatively related to the dependent variable,

Interpreting these results as they apply to the

hypothesized relationship between cognitive style preference and conservation ability was difficult, The research cited in the literature review did not provide an explanation for these results. An explanation of the findings was offered on the basis of the nature of the correlations between the independent and dependent variables and the fact that subjects who scored high on conservation ability tended to use more style categories than the subjects who scored low. This suggested that subjects who obtained higher conservation scores used the Descriptiveglobal style infrequently and simultaneously enlarged their




Full Text

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AN APPLICATION OF CROSS'S CHAIN-OF -RESPONSE MODEL FOR DESCRIBING FACULTY WHO PARTICIPATE IN PROFESSIONAL DEVELOPMENT ACTIVITIES By WINIFRED BUCHANAN COOKE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 1986

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To my husband, Charles, my son, Ryan, my daughter, Elizabeth, and our families In memory of my father, the Reverend Ralph W. Buchanan

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ACKNOWLEDGMENTS The writer gratefully acknowledges her Indebtedness to those who have assisted in the development of this study. Appreciation is given to Dr. James L. Wattenbarger , chairman of her supervisory committee, for his counsel and guidance and to committee members Dr. John M. Nickens and Dr. Albert B. Smith for their advice and timely suggestions. A special note of gratitude is given to Dr. Jeaninne Webb for encouraging the writer to enter the University of Florida and for her unending interest and support throughout the writer's endeavors at the University. In addition, the writer would like to thank several others who contributed greatly to the completion of her dissertation: Dr. K. Patricia Cross for her evaluation of portions of the dissertation. Dr. Samuel Proctor for his advice on the interview technique, Dr. Sue Legg and Dr. Elois Scott for their assistance with interview question development, and Ms. Rosa Hall for assistance with the coding of data. Appreciation is expressed to the writer's friends and colleagues on the Office of Instructional Resources Teaching Center staff and at Southeastern Community College for their patience and encouragement . The greatest indebtedness is acknowledged to the writer's family for their abiding faith, constant encouragement, and loving sacrifice. iii

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TABLE OF CONTENTS Page ACKNOWLEDGMENTS lii LIST OF TABLES vii LIST OF FIGURES viii ABSTRACT ix CHAPTER I INTRODUCTION 1 Background of the Study I Problem Selected for Study 5 Delimitations of the Study 6 Purposes of the Study 6 Assumptions of the Study 7 Definition of Terms 8 Design of the Study 10 Organization of the Dissertation 14 II THE COR MODEL AND ITS PRECURSOR THEORIES 16 Part 1: The Precursor Theories 16 Part 2: The COR Model 26 Summary 53 III THE DEVELOPMENT OF THE INTERVIEW SCHEDULE 5A Descriptive Statements of COR Model Constructs 54 Interview Schedule Construction 59 Interview Guideline Development 61 Pretest of the Interview Schedule 61 IV DATA COLLECTION AND ANALYSIS 63 Population Studied 53 Data Collection 54 Steps of Data Analysis 55 Analysis and Discussion of Data 68 ^ Summary of Statistical Data 103 ' I I iv

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Page V SUMMARY, CONCLUSION, IMPLICATIONS, LIMITATIONS OF THE STUDY, AND SUGGESTIONS FOR FURTHER RESEARCH 104 Summary and Discussion 104 Conclusions 112 Implications 114 Limitations of the Study 117 Suggestions for Further Research 118 A Final Observation 120 APPENDICES A FORCE FIELD DIAGRAMS OF MOTIVATIONAL FORCES TOWARD EDUCATION AFFECTING MIDDLE CLASS ADULTS 121 B RUBENSON'S PARADIGM OF RECRUITMENT 128 C A MODEL TO EXPLAIN ADULT EDUCATION PARTICIPATION AND DROPOUT 130 D ANTICIPATED BENEFITS FROM LEARNING 132 E DESCRIPTIVE STATEMENTS FOR CONSTRUCTS CROSSREFERENCED TO THE COR MODEL INTERVIEW SCHEDULE, FACULTY QUESTIONNAIRE, AND CODE BOOK 133 F INTERVIEW GUIDELINES 139 G COR MODEL INTERVIEW SCHEDULE 146 H FACULTY QUESTIONNAIRE 152 I LETTER OF INTRODUCTION 157 J INITIAL TELEPHONE CONTACT GUIDE 158 K SUGGESTED REVISIONS FOR CODING OF THE INTERVIEW SCHEDULE 161 L CODE BOOK 162 M SUMMARY OF STATISTICAL DATA BY HYPOTHESIS AND DATA SOURCE 172 N SUMMARY OF CONSTRUCT STANCES FOR ENTIRE COR MODEL BY INDIVIDUAL AND GROUP (DATA FROM INTERVIEW SCHEDULE) 175 0 SUMMARY OF CONSTRUCT STANCES FOR' ENTIRE COR MODEL BY INDIVIDUAL AND GROUP (DATA FROM FACULTY QUESTIONNAIRE) 178 V

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Page REFERENCES 180 BIOGRAPHICAL SKETCH 182 vi

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LIST OF TABLES Table Page 1. Descriptions of life-cycle phases 41 2. Milestones of ego development 44 3. Demographic characteristics of respondents by group. . . 69 4. Breakdown of construct stance by descriptive statements. Construct: Self-evaluation 71 5. Breakdown of construct stance by descriptive statements. Construct: Attitudes about education ... 76 6. Breakdown of construct stance by descriptive statements. Construct: Goals and expectations 81 7. Breakdown of construct stance by descriptive statements. Construct: Life transitions 86 8. Breakdown of construct stance by descriptive statements. Construct: Opportunities and barriers. . . 90 9. Breakdown of construct stance by descriptive statements. Construct: Information 95 10. Breakdown of construct stance by descriptive statements. Construct: Participation 99 11. Comparison of construct stance from Interview Schedule with Faculty Questionnaire 108 vii

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LIST OF FIGURES Figure Page 1. The Chain-of-Response (COR) Model for understanding participation in adult learning activities 4 2. Expectancy-valence theory applied to recruitment in adult education 21 3. Level of self-evaluation by frequency 73 4. Level of attitudes about education by frequency .... 78 5. Level of goals and expectations by frequency 82 6. Level of life transitions by frequency 87 7. Level of opportunities and barriers by frequency. ... 91 8. Level of information by frequency 96 9. Level of participation by frequency 101 10. Relationship of the number of constructs which were positive descriptors with the level of participation. . 113 viii i

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy AN APPLICATION OF CROSS'S CHAIN-OF -RESPONSE MODEL FOR DESCRIBING FACULTY WHO PARTICIPATE IN PROFESSIONAL DEVELOPMENT ACTIVITIES by Winifred Buchanan Cooke May, 1986 Chairman: Dr. James L. Wattenbarger Major Department: Educational Leadership This study was an effort to determine whether the university faculty who participated in organized professional development activities could be described using Cross's Chain-of-Response (COR) Model. Two questions were addressed: (a) Does the operationally defined model provide adequate information to explain participation or non-participation? (b) Does the operationally defined model provide adequate information to explain the level of participation for those who participate? In her COR Model, Cross portrayed participation in learning activities as a result of a chain of responses rather than a single act. Her continuum began with self-evaluation and attitudes about education and continued through importance of goals, life transitions, opportunities and barriers, and information — culminating in participation. The study was completed in three phases. First, the COR Model was adapted to describe faculty who participate in structured professional development activities. Second, an interview schedule ix

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and a Likert-style questionnaire were developed to determine the utility of the model. Third, both instruments were administered to two groups of University of Florida faculty — participants and nonparticipants in professional development activities on computer technology. Data gathered from the faculty were analyzed and compared to the COR Model. The statistics used to analyze the data were median scores, percentile rank. Spearman rank correlations, and the chisquare test of significance. Results of the study provided support for the following conclusions : 1. Motivation of faculty members to participate in learning activities related to computer technology depended largely on goals and expectations. Motivated faculty were likely to seek educational opportunities and overcome barriers. Conversely, barriers were likely to preclude the participation of weakly motivated faculty. Motivated faculty remembered more information about professional development opportunities on computer technology. Thus, participants differed from non-participants primarily on their stance on three constructs: goals and expectations, opportunities and barriers, and information. 2. A high level of participation in professional development activities was an indication that the majority of the constructs in the COR Model were positive descriptors of the faculty member. Conversely, low or non-participation in such activities indicates that few if any of the constructs were positive descriptors of the individual. X

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CHAPTER I INTRODUCTION After a careful review of the literature, K. Patricia Cross (1981, p. 109) noted that theory in adult education was almost nonexistent. She quoted others who shared her opinion: Boshier (1971) called adult education a "conceptual desert" (p. 3) and Mezirow (1971) called the absence of theory a "pervasively debilitating influence" (p. 135). In her book Adults as Learners (1981), Cross developed a Chain-of-Response (COR) Model for understanding participation in adult learning activities. While Cross admitted that the model was still "far from the kind of theory that can be used to predict who will participate in which learning activities" (p. 124) she pointed out its usefulness in organizing existing knowledge and in suggesting more sharply focused research projects. Background of the Study The COR Model (Cross, 1981, p. 112) was based on the work of four scholars of adult learner motivation: Harry L. Miller, Kjell Rubenson, Roger Boshier, and Allen Tough. The focus of the research of the first three theorists was on participation in organized classes; Tough examined anticipated benefits of self-directed learning projects. A brief description of the models developed by these men is presented in the paragraphs following as a basis for understanding the conceptual framework Cross designed to identify variables relevant to -1-

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-2particlpation in a learning activity and to hypothesize the interrelationships of the variables. Miller (1967) examined the relationship between social class and participation in adult education activities. To explain why there were differences in participation between groups with different socioeconomic status and different expectations from participation, Miller utilized Maslow' s hierarchy of needs and Lewin's force field analysis . Rubenson (1977) developed an expectancy-valence paradigm which was an application to adult education of Vroom's expectancy-valence theory. In Rubenson' s paradigm, the strength of an individual's motivation was determined by combining positive and negative forces which existed in the individual and his or her environment. In his congruence model, Boshier (1973) portrayed motivation as a function of the interaction between internal psychological factors and external environmental variables. He concluded that both adult education participation and dropout can be understood to occur as a function of the magnitude of the discrepancy between the participant's self-concept and key aspects (largely people) of the educational environment. Nonparticipants manifest self /institution incongruence and do not enroll, (p. 260) Tough and his colleagues (Tough, Abbey, & Orton, 1980, pp. 1-5) examined the conscious focus involved in motivation for learning. Their model classified anticipated benefits of participating in selfdirected learning projects into three categories of personal feelings: pleasure (happiness, satisfaction, enjoyment, feeling good), selfesteem (regarding self more highly, feeling more confident, maintaining self-images), and "others" (others regard the individual more highly, praise the person, like the person, feel grateful). They

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-3identifled five stages at which these benefits could be anticipated. The stages were (a) engaging in a learning activity, (b) retaining the knowledge, (c) applying the knowledge, (d) gaining a material reward such as a promotion or raise, and (e) gaining a symbolic reward such as a credit or degree. The COR Model, presented in Figure 1, was built on the common elements of these four theorists. In her model. Cross (1981, pp. 124125) portrayed participation in learning activities as a result of a chain of responses rather than a single act. She suggested that the continuum involved a movement from the internal condition of selfevaluation through increasingly external conditions of evaluating one's position in his or her environment — finally culminating in participation. The other variables (or sets of variables) she included were attitudes about education, importance of goals, life transitions, opportunities and barriers, and information. Participation in a learning activity was shown to result ultimately in a changed self-evaluation and attitude about education. While Cross portrayed the primary movement as beginning with self and moving outward, she pointed out that the forces flow in both directions in any interaction. Though the COR Model was helpful in understanding some of the dynamics of a decision by a learner to become involved in adult education, and while narrower models of adult participation which have been measured were incorporated in the model, there remained a need for further development of the model in order that its utility for explaining adult education participation could be enhanced. Cross (1981), while acknowledging the limitations of her conceptual

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-4G O to (3 O 1-1 u tr) w O 00 c o CO a « 0) 13 O 3 i-l < > w a) I u-t 0) cn p4 03 <0 M C 01 O '-N a -H eo 3 4-1 u nj •H O 4J 3 u T3 < 0) 4J •H > c o •H 03 03 •H e u ^ J3 1-1 -a u (Si u 1-1 C 3 •1-1 T3 CO a in Re c o -H XJ CO r-l O. •H o O. •H 4-1 1-1 i-l CO 00 Q, CJN I-l 60 c •H 03 T) 03 C o CO u XJ o 03 I-l CO 0) •H T3 o C •H 3 U )-i to O M-l • iH ode by s 03 U (COR arne h-J 03 I-l c 03 OJ o to j: a 03 03 03 •H 4-1 iH Pi 1 iH J3 3 3 14-1 T3 o <: 1 a (U c •H o 4-1 to I-l <4-4 0 0) VI 9 00

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-5framework. (p. 124), called her conceptual framework "a theory of adult motivations for learning" (p. 112). She included a set of related constructs (which she called variables) in her theory; however, she did not operationally define the constructs. Hall and Lindzey (1957) in their classic definition of theory pointed out the two necessary ingredients of a useful theory: "A theory consists of a set of related assumptions [constructs] concerning the relevant empirical phenomena and empirical definitions [operational definitions] to permit the user to move from the abstract theory to empirical observation" (p. 15). Hence, the expansion of her model to include constructs which were both constitutively and operationally defined and the development of a technique to examine the utility of the model for a sub-group of adults were addressed by this study. Problem Selected for Study The problem addressed in this study was to determine whether it was possible to describe college and university faculty members who participate in organized professional development activities using Cross's Chain-of-Response Model. In order to determine the utility of the COR Model, the following questions were addressed: (a) Does the operationally defined model provide adequate information to explain participation or non-participation? (b) Does the operationally defined model provide adequate information to explain the level of participation for those who participate?

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-6Dellmltations of the Study This study was confined to adult motivation as presented by Cross and the works of the four researchers she identified as the basis for her COR Model. Reference to the works of other scholars of adult education or motivation theory were included only if their inclusion further clarified or deepened understanding of the concepts involved in the COR Model. Furthermore, while the COR Model applied to the total adult population, this study was delimited to a sub-population of adults who were faculty members at postsecondary educational institutions. This study was exploratory in nature, and no claim was made for predictive validity. Cross has pointed out that the model has not yet been developed sufficiently to be used for prediction of participation. The technique developed also was not designed as a predictor of participation; but rather, the technique was used to determine if the COR Model demonstrated potential. Purposes of the Study This study addressed the motivation of college and university faculty toward participation in professional development. An increased understanding of why some faculty participate in development activities while others do not may have important implications for the design of professional development programs and perhaps even for the hiring practices of educational administrators who are faced with the challenge of keeping their faculty current. The Second National Assembly of the American Association of Community and Junior Colleges

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-7(cited in O'Batiion, 1977) emphasized the need of professional development in its recommendations. The staff of a college is its single greatest resource. In economic terms, the staff is the college's most significant and largest capital investment. In these terms alone, we affirm that it is only good sense that the investment should be helped to appreciate in value and not be allowed to wear itself out or slide into obsolescence by inattention or neglect, (p. viii) The problems of the faculty member staying current within his or her discipline are now compounded in the face of new and more diverse student populations who challenge the values and styles of traditional teaching and, moreover, by "the first great technological revolution [computer technology] in five centuries" (The Carnegie Commission on Higher Education, 1972, p. 1). In addition to making data for decision making available to administrators who are charged with faculty renewal, the design of a technique which can be utilized to test the COR Model with this population of adult learners may contribute to the development of procedures for determining the appropriateness of the COR Model for other voluntary adult learner populations . Assumptions of the Study An assumption of the COR Model and of this study is that the individual has control over his or her destiny, and that his or her participation in learning activities is voluntary. The model rejects "both the Freudian notion that human beings are the captives of subconscious forces and the Skinnerian contention that people are pawns in stimulus-response chains" (Cross, 1981, p. 123).

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-8Deflnition of Terms Adult education. For this study, the definition of Rubenson (1977) is used. "All education embarked on by the individual after previously completed or discontinued basic education, usually after an intervening period of job experience" (p. 2) falls under adult education. Card questions. This is a technique used by researchers to help correct a distortion in the data collected caused by the order of the question. Items to be ranked are placed on 3 x 5 cards, one item to a card. The cards are shuffled after each interview and handed to the respondents, and he or she arranges them in the order of preference . Coding of data. This is a technique used by researchers to categorize data. A number or symbol is assigned to each answer which falls in a predetermined class. Construct . A construct is a concept (an abstraction formed by generalization from particulars) which has been deliberately included in a theoretical scheme and which is related within the theoretical scheme to other constructs. Constructs are defiaed constitutively and operationally. A constitutive definition uses other constructs to define a construct, whereas "an operational definition assigns meaning to a construct or a variable by specifying the activities or 'operations' necessary to measure it" (Kerlinger, 1973, p. 34). Expert in social research . For this study, the expert is an individual with experience in interview schedule construction. Faculty development . As used in this study, the term includes all organized activities designed to help faculty members acquire

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-9knowledge, within their discipline; improve skills, sensitivities, and techniques related to teaching and student learning; and become more productive researchers. Typical activities include course work, seminars, and workshops. Instructional development. This term includes all organized activities designed to improve student learning, prepare learning materials, redesign courses, or make instruction systematic. Typical activities include workshops on writing objectives and projects to produce new learning materials or redesign courses. Interview schedule. This data collection instrument is filled in by an interviewer who reads the questions to the respondent. The interview schedule equates to a questionnaire that is administered orally. Item. An item is a question in the interview schedule. Multiple choice questions . Included in this category are questions which are framed so that the respondent must select one of several possible answers to represent his or her opinion or select one to come closest to that opinion. Open-ended questions. Questions which give the respondent free latitude in his or her responses are included in this category. Organizational development. These activities are designed to create an effective environment for teaching and learning, improve interpersonal relationships, or enhance team functioning within the educational institution or subunit of the institution. Typical activities include workshops for group leaders or team members, action research with work groups, and task forces to revise organizational policies .

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-10Professional development activities. Organized activities which fall under faculty development, instructional development, or organizational development are included in this category. Tabulation. This term is used to denote the summarization of results in the form of statistical tables. Theory. "A theory consists of a set of related assumptions [constructs] concerning the relevant empirical phenomena and empirical [operational] definitions to permit the user to move from the abstract theory to empirical observation" (Hall & Lindzey, 1957, p. 15). Triangulation. Triangulation is the technique recommended by Patton (1980) for verification and validation of qualitative analysis. For this study it involved "checking out the consistency of findings generated by different data collection methods" (p. 329). Variable. Cross loosely called her constructs variables. For this study, however, a variable is defined as a symbol to which numbers or values are assigned. Thus variables are measurable. Design of the Study This study was completed in three phases. In the first phase, the COR Model was adapted by defining the model's constructs both constitutively and operationally to describe faculty who participate in structured professional development activities. The second phase included the development of a technique for determining the utility of the adapted model for distinguishing between participating and nonparticipating faculty. This phase was divided into (a) interview schedule construction, (b) interview guideline development, (c) pretest of the schedule, and (d) analysis of data from the pretest.

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-11During the third phase, the technique developed in Phase II was used to deteinnine if there were differences between participating and nonparticipating faculty at the University of Florida. Phase I: The COR Model and Construct Development This phase of the study included an analysis of Cross's COR Model and the contribution of the four scholars identified by Cross as the basis of her model. The works of the four scholars were compared and contrasted with the description of the Cross model. Then, through a logical-deductive process, underlying constructs of the COR Model were projected and defined constltutively and operationally. The constructs were adapted to describe faculty in postsecondary institutions who would involve themselves in structured professional development activities. The constructs developed were submitted to Cross, the originator of the model, who compared the constructs with the COR Model. She then rated the constructs' accuracy of expression. Cross was also given a set of statements which described each construct of the COR Model. She was asked to place each statement in one of three categories — (a) adquately stated and basic to the construct, (b) inadequately stated but basic to the construct, or (c) not basic and/or not representative of the construct — to indicate her judgment of how accurately the statement represented that construct. Cross needed to choose "adequately stated and basic to the construct" in order for the statement to be developed into an item used for the interview which is described in Phase II.

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-12Cross suggested alternative definitions for inadequately defined constructs and alternative statements which described the constructs if she believed the definitions and/or statements were inadequately stated. Cross was also asked to identify any aspects of the constructs she believed were basic but not already included on the list of statements. These statements were added to the list. All proposed statements which received the rating of "not basic and/or not representative of the construct" were discarded. Phase II: The Development of a Technique for Determining the Utility of the Adapted Model An interview schedule, a data collection instrument which is completed by an interviewer who reads the questions to the respondent, was developed to measure the adapted COR Model constructs. The interview schedule was a combination of open-ended questions, multiple choice questions, and a ranking of items. The statements which Cross agreed adequately described the constructs of the model were used to develop interview questions. Only questions which had a direct bearing on the constructs of the COR Model and which could not be answered more accurately and effectively from other sources were included in the interview schedule. To insure that the data obtained on the adapted version of the COR Model would be worth analyzing, the processes by which the information was obtained were controlled. All significant elements of the interview situation — the interviewer, the surroundings of the interview, the respondent, and the process of questioning and

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-13recordlng — were described in interview guidelines. Then a draft of the interview schedule was pretested. Any needed changes were made in the schedule and in the guidelines for its administration before the pilot test was carried out. Phase III; Test of the Adapted Model After problem areashad been corrected, the interview schedule was administered to a sample of faculty who had recently chosen to participate in some structured professional development activity and a second sample who had not. The population sampled was the University of Florida faculty. Fifteen-member samples were randomly selected from each group. The interviews were conducted using the interview guidelines established during Phase II of the study. The data gathered for this descriptive study were both qualitative and quantitative, but primarily qualitative. The procedures for analysis of qualitative data which were outlined by Miles and Huberman (198Aa, 1984b) were utilized. The analysis of data consisted of three concurrent activities: data reduction, data display, and conclusion-drawing/verification. Data reduction involved coding, selecting, focusing, simplifying, abstracting, and transforming the raw data from edited field notes. Data reduction was not limited to quantification. Other ways qualitative data were reduced and transformed included selection, summary, paraphrase, and patterning. Data display, defined as "organized assembly of information that permits conclusion-drawing and actiontaking" (Miles & Huberman, 1984, p. 24), included the development of a wide range of matrices, graphs, networks, and charts.

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-14Conclusion-drawing began with data collection as the researcher noted regularities, patterns, explanations, possible configurations, causal flows, and propositions. Initially, the conclusions were vague and tentative. They became increasingly explicit and grounded as data reduction and display revealed a logical chain of evidence and conceptual/ theoretical coherence. Conclusion verification tactics included making contrasts/comparisons, checking the meaning of outliers, looking for negative evidence, and argumentation and review to develop intersub jective consensus. Also, methodological triangulatlon was used for verification by comparing data from interviews with data from a Likert-style instrument which measured the same constructs. Statistics which were used to differentiate between the two groups were median scores, percentile rank, and Spearman rank correlations. The chi-square test was used to determine significance. Organization of the Dissertation This dissertation consists of five chapters. Included in Chapter I is the introduction, a statement of the problem, delimitations and limitations, a justification for the study, assumptions, definitions of major terms, and the design of the study. In Chapter II, Part 1 is a review of the literature of the precursor theory of the COR Model. Presented in Part 2 are (a) a review of the COR Model and (b) a comparison and contrast of the works of each of the four precursor models with Cross's model. This literature analysis serves as the basis for the adaptation of the COR Model into constitutively and operationally defined constructs which describe postsecondary faculty

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-15who participate in structured professional development activities. The development of the technique for testing the utility of the adapted model is included in Chapter III. Described in subsections of this chapter are the interview schedule construction and interview guidelines. In Chapter IV are a description of the use of the technique described in Chapter III with faculty at the University of Florida and the analysis of data gathered by the interviews. The conclusions of the study, suggested implications, and recommendations for further research are Included in the final chapter (Chapter V).

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CHAPTER II THE COR MODEL AND ITS PRECURSOR THEORIES Cross based her COR Model on the work of four researchers in the area of adult education: Miller, Rubenson, Boshier, and Tough. While the work of these men had many common elements, each person identified a slightly different set of variables and utilized a different technique for measuring motivation. The work of each scholar is viewed individually. Part 1: The Precursor Theories Harry L. Miller: Force Field Analysis Miller (1967) drew heavily on Maslow's hierarchy of needs and socioeconomic status to explain participation in adult education classes. He presented the stages of Maslow's hierarchy with survival needs being the most basic and self-realization topping the hierarchy as follows : '^ Self-realization Achievement Recognition (status) Belonging Safety Survival -16-

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-17Miller (1967) defined the three most fundamental needs from Maslow's scheme in terms of the industrial society: Survival [underline added], in whatever terras the person sees it, comes before the activation of higher needs, and in industrial societies we tend to see it as a gain of marketable skills. Because rapid technological development results in shifts in skill demands, adult education is dominated by job training, where one finds the highest consistent level of participation. The safety need reinforces this domination because in this culture the greatest perceived deprivation is an economic one, and the most general threat is the loss of a job. Belonging needs draw us into a whole range of associations from deep emotional needs we seek to satisfy in marriage to the pervasive needs for acceptance by the members of whatever groups are important to us. (p. 5) The higher order "ego needs," according to Maslow's scheme, became powerful motivators only when the basic ones were at least minimally satisfied. Miller used this principle to explain why recognition was a high motivator for participation in courses leading to educational advancement for the middle class, "which need not be greatly concerned about either survival or safety, and whose stable family structure and active organizational life provide adequate satisfaction of belonging needs" (p. 6). Achievement needs Miller described as more generally distributed across classes and perhaps only indirectly related to participation in adult education: "higher levels of education are associated with a considerable degree of persistence toward relatively distant goals, which in turn is associated with high levels of achievement need" (p. 6). He said the need for self-realization, a drive that moves an individual towards being the most he is capable of being, was rarely a dominant need; however, many persons "are engaged in satisfying it at least fitfully" (p. 7).

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-18Miller also looked at the congruence of Maslow' s hierarchy with age and the life cycle. "The early stages of adulthood," he argued, "are primarily concerned with satisfaction of the three lowest stages — getting established in a decent, stable job and beginning a family" (p. 7). I'/hile Miller (1967, p. 8) emphasized the role personal need plays in adult participation, he asserted that one must consider the interaction of personal needs with relevant social variables in order to get an accurate assessment of the forces at work in the whole environment. The three social variables which he identified as particularly relevant were social class value systems, technological change, and associational structures. Miller then described several studies of the effects of socioeconomic status on participation in educational activities. Since an assumption of this writer is that postsecondary faculty fall into the middle classes, only the information relevant to those classes was reviewed. According to Miller (1967), the socioeconomic status needs of the lower-middle class were almost all sustaining forces in relation to adult education participation. Included in the value system of this group was an emphasis on mobility and status. "Progress" was viewed as good "not only because it demonstrates our virtue as a society, but because it offers hope for family movement as well" (p. 11). Education was seen as the means of achieving status. In addition, some members of the lower-middle class adopted the upper-middle class values of "concern with self-development and achievement, apart from any status these confer" (p. 12). This was a result of what

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-19soclologists called "anticipatory socialization," when members adopt the values of the class they are striving to reach. Both the lowerand upper-middle class cultures were futureoriented, Miller (1967, p. 12) reported; and while their needs were congruent with the major forces of the society, there were some striking differences in values between the two classes. The uppermiddle's interest in career achievement transcended an interest in status, and they actively pursued self-development activities. Also, their cosmopolitan interests directed their attention to national and international associational concerns as opposed to community and local ones. Miller also pointed out that there were actually two upper-middle cultures: the executive and the professional. The executive class value system was closer to the Puritan ethic of the lower-middles, while the professional class values embraced relativism and tolerance of others' values. Yet, the sustaining forces for both of the uppermiddle classes' participation in adult education were strong. Miller elaborated: The upper-middles create and implement the technological shifts which provide either trouble or opportunity for other social class levels, education is a comfortable and familiar tool for "keeping up with the field" and improving skills, and the corporation and firm pays for it. (p. 13) (See Appendix A for force field diagrams which represent the positive and negative forces present in the motivation of the middle class toward vocational competence, personal and family competence, citizenship competence, and self-development.)

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-20Kjell Rubenson: Expectancy-Valence Paradigm Rubenson (1977), as Miller did, viewed participation in adult education as one of many forms of social participation and turned to the behavioral sciences for existing theories upon which he could develop a recruitment paradigm. While Miller drew primarily from Maslow (hierarchy of needs) and Lewin (force field analysis) as he developed his theory, Rubenson drew heavily on Vroom's expectancyvalence theory and Lewin's field theory. In order to clarify Rubenson's paradigm, a brief description of the expectancy-valence theory and field theory is presented. As reported by Rubenson (1977), Vroom defined valence as an attitude toward the result of an action. If the person preferred attaining the result of an action, the valence was positive; if the person was indifferent to the outcome the valence was neutral; and if the individual preferred not to attain the outcome, the valence was negative. The valence varied from +1 to -I. The difference between valence and value was emphasized. Valence was said to be associated with the person's previous belief concerning the outcome that would result from a particular course of action. Value, on the other hand, was said to be related to the satisfaction to which the action led (p. 8). Rubenson (1977) quoted Vroom's definition of expectancy as follows : [Expectancy is] a momentary belief concerning the likelihood that a particular act will be followed by a particular outcome. Expectancies may be described in terms of their strength. Maximal strength is indicated by subjective certainty that the act will be followed by the outcome while minimal (or zero) strength is indicated by subjective certainty that the act will not be followed by the outcome, (p. 9)

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-21Rubenson (1977) applied the expectancy-valence theory to recruitment of adult learners as illustrated in Figure 2. sees participation in adult education as a conceivable means of satisfying experienced needs (valence) believes himself to be in a position to complete and successfully cope with a course, and believes that participation will have certain desirable consequences (expectancy) Figure 2. Expectancy-valence theory applied to recruitment in adult education (from Participation in Recruitment Education; A Research Review by Kjell Rubenson, 1977, p. 9. Rubenson (1977) then analyzed the concepts of valence and expectancy in order to complete his paradigm of recruitment for participation in adult education. He summarized recent findings of previous research in the areas of participation in adult education, self-evaluation, and values of member groups and reference groups. He then concluded that "self-evaluation (which is influenced by the degree of hierarchic structure [perceived freedom for decision making] and the values of the member and reference groups are of great importance in shaping a person's attitude to adult education" (p. 30). high probability of participation

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-22In Rubenson's Paradigm of Recruitment, presented in Appendix B, participation in adult education was regarded as a function of the individual's interpretation of the current psychological field. The paradigm included three groups of independent variables: previous experience and congenital properties, environmental factors, and current needs. A cognitivlst, Rubenson believed that a person's actions must be explained in terms of perception — how the individual perceives and interprets his or her situation. Rubenson's two levels of intermediate variables reflect his orientation. As shown in Appendix B, the first level of intermediate variables (active preparedness, perception, and interpretation of the environment and experienced needs) were said to determine expectancy and influence valence. Expectancy was assumed to be a multiplicative function of (a) the expectation that participation would have certain positive consequences and (b) the expectation of being able to participate in and complete the course of education. Thus, if the individual saw no possibility of achieving either component of expectancy, that component was said to assume the value of 0; and consequently, the resultant force toward participation was assumed to be 0. The valence of a certain course of study was presented as a result of the experienced needs of the individual (the second level of intermediate variables) and expectations concerning the consequences of participation and the values of the member and reference groups. Valence and expectancy were then said to form a multiplicative function which results in a force. "The strength of this force in relation to other forces acting on the individual," Rubenson said, "determines whether the individual will participate in adult education

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-23or not" (1977, p. 38). Again, the multiplicative function implied that both valence and expectancy must exist in order for a force to arise . Roger Boshier; A Congruence Model Like Miller and Rubenson, Boshier (1973) rejected single variable explanations which have been proposed to explain adult education participation and dropout. He contended instead that "'congruence' both within the participant and between the participant and his educational environment determines participation/non-participation and dropout/persistence" (p. 256). As evidence of support for his position, he offered data from participants enrolled in continuing non-credit classes in New Zealand. Boshier's model to explain adult education participation and dropout is found in Appendix C. Boshier characterized all participants as "deficiency" or "growth" motivated. He described growth-motivated people as "innerdirected, autonomous, open to new experience, willing to be spontaneous, creative. . . . The self-actualizing growth-motivated person, by definition gratified in his basic needs, ... is better equipped to adapt to environmental inconsistency and disorder" (1973, pp. 256, 258). Determinants which governed them were primarily inner ones, rather than social or environmental. In contrast, deficiencymotivated people are impelled by social and environmental pressures. They "seem to use work and educational activity more often for achieving gratification of lower basic needs, ... as means to an end, or as a response to cultural expectations" (1973, p. 258). "Growth-motivated persons" were equated to Carl Roger's intra-self

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-24congruence and thus self/other congruence and satisfaction with the educational environment, while deficiency motivation was presented as synonymous with intra-self (self/ ideal) incongruence. Boshier acknowledged that individuals were not entirely growthor deficiencymotivated. Boshier, in his model, presented the individual as a unified system with two problems: maintaining inner harmony within the individual and with the environment. He suggested that both "participation and dropout can be understood to occur as a function of the magnitude of the discrepancy between the participant's selfconcept [explained in terms of 'deficiency' or 'growth' motivation] and key aspects (largely people) of the educational environment" (1973, p. 260). Non-participants did not enroll because of manifested self /institution incongruence; participants, upon discovering that their needs (or self-concept) and their educational environment were not congruent, dropped out. Furthermore, intra-self (self/ideal) incongruence, which was characterized by deficiency motivation, gave rise to self /other incongruence. Boshier viewed the single social, psychological, and institutional variables (e.g. socioeconomic class, age, class size, or transportation difficulties) as mediating variables which triggered dropout if intra-self or self/other incongruence had developed. Allen Tough; Anticipated Benefits Tough's model of anticipated benefits was different from the other models used by Cross as she developed her COR Model. First of all, his focus was on self-directed learning projects rather than

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-25enrollment in organized classes; and second, his model was more fragmentary and incomplete than any of the other three. Cross, however, saw Tough's work as providing useful information on the conscious forces involved in motivation for learning. In his research efforts, Tough (1971, 1978, 1979) and with his associates (1980) focused primarily on the major learning efforts of adults, called adult learning projects. He defined a major learning effort as a deliberate effort to gain and retain a defined area of knowledge or a skill, or to change in some other way. To be included in this definition, a series of related learning sessions (episodes in which the person's primary intention is to learn) must add up to at least seven hours. . . . Any method can be included — reading, listening, observing, attending class, reflecting, practicing, getting answers to questions — as long as the person's primary intention during the learning episode was to gain and retain a defined area of knowledge or skill. (1978, p. 8) Tough presented his framework for anticipated benefits in 1971 (p. 47); however, it was not tested until a decade later (Tough, Abbey, & Orton, 1980). Tough's model which was simplified in order to collect data for the 1980 study is included in Appendix D. The simplified model (Tough et al., 1980) included five stages where benefits might be anticipated: (a) engaging in a learning activity, (b) retaining the knowledge or skill, (c) applying the knowledge, (d) gaining a material reward (e.g., promotion or raise), or (e) gaining a symbolic reward (e.g., credit or degree). The benefits which might be anticipated at each stage were categorized into three clusters of personal feelings: pleasure, self-esteem, and others. Tough and his colleagues defined these clusters as follows: "Pleasure" can include an increase in happiness, satisfaction, enjoyment, or feeling good — or avoiding some unpleasant feeling. "Self-esteem" means you regard yourself more highly, feel more confident, maintain your self-image,

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-26or avoid damaging your self-esteem. "Others" means other persons regard you more highly, praise you, like you more, feel pleased with you, or feel grateful to you. (p. 4) Data for the study were collected from adults in metropolitan Toronto. Each study participant was first asked to think of a learning activity (preferably not a credit course) that they were enthusiastic about and that was still in progress. After the model was explained, each respondent was then asked to distribute 10 imaginary motivational units on the diagram "in whatever pattern would best reflect the anticipated benefits [pleasure, self-esteem, others] that actually motivated them to continue this learning effort" (p. 5). The subjects identified the "application of knowledge or skill" as the most likely stage for anticipated benefits. The other stages were selected in the following order: "engagement in learning activities," "retention of knowledge," "material reward" and "credit." "Pleasure" was the most frequently anticipated reward, followed by "self-esteem" and "reaction from others." Part 2: The COR Model Cross proposed her Chain-of-Response Model to explain participation in adult learning activities. While her description of participation included all adults involved in adult learning activities, this study focused on those adults who were faculty at postsecondary educational institutions and who engaged in structured professional development activities. Therefore, the description of the model was adapted to describe this sub-population. Cross included seven constructs in the COR Model: (a) selfevaluation, (b) attitudes about education, (c) importance of goals and

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-27expectatlon that participation will meet goals, (d) life transitions, (e) opportunities and barriers, (f) information, and (g) participation. For this study, the two parts of constructs (c) and (e) were treated as separate but closely related constructs (see Table 1). Each construct was addressed individually and a comparison/contrast was made between Cross's description of the construct and descriptions given in precursor theories. Finally, a constitutive and operational definition was extended for each construct . Self-Evaluation Cross and the four earlier educators each described the impact he or she believed self-evaluation had on participation in adult learning. All emphasized the relationship between positive selfevaluation and participation. Tough and his associates (1980, pp. 7-8) found that motivation for participation in adult learning projects came from the desire to enhance pleasure (50% of participants) and self-esteem (41% of participants). Only 9% of the persons in his study indicated their desire to please and impress others. Boshier, who did extensive research on adult student behavior, described participators/persistors as growth motivated, inner directed, autonomous, open to new experience, willing to be spontaneous, creative, self-actualizing, and gratified in their basic needs. He presented them as equipped to handle environmental inconsistence and disorder since they were governed by inner

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-28determinants rather than social or environmental ones (1973, pp. 256-259). Rubenson (1977, pp. 20-22) came to a similar conclusion after examining a study done by Denmark and Guttentag in 1967 in which the self-perception of the subjects was directly related to participation in adult education and after examining many studies which supported the supposition that persons with a high degree of self-respect perform better in achievement-oriented situations than persons with a low degree of self-respect. Rubenson took, self-concept a step further when he presented data which indicated that a hierarchic environment influenced participation in adult education. Persons who in their childhood, school, and work environments were permitted and encouraged to make individual initiatives (as opposed to being hierarchically controlled) developed a more positive self-evaluation. Rubenson concluded , in the light of the above discussion of self-evaluation, its importance to achievement-oriented behavior and factors influencing self-evaluation, the degree of hierarchic structure in the current surrounding of the individual and especially the work situation appears to be vitally important to expectations concerning adult education. (1977, p. 25) Miller presented the upper middle class values of concern with self-development and achievement, apart from any status these confer. Miller's theory about participation in adult education fits largely under other constructs; however, he did examine the interaction of personal needs (as described by Maslow's hierarchy) and their interaction with social class value systems (see Appendix A). He proposed that persons in the lower-middle class have satisfied the basic needs of survival, safety, and belonging. For the lower-middle class, the motivator was primarily a need for recognition (status). In

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-29contrast, he claimed the upper-middle class valued self-development and achievement, apart from any status these confer (1967, pp. 11-13). The constitutive definition for self-evaluation as Cross described the construct follows. The operational definition used in this study to measure the construct is also presented. Constitutive definition. Self-evaluation is the general or global value which a person ascribes to himself as a learner. Individuals (faculty) who perceive themselves positively and have confidence in their own abilities are more likely to voluntarily participate in learning activities (professional development). Other terms used to describe persons who perceive themselves positively are self-confident, self-assured, secure, and unthreatened . Operational definition . In this study, self-evaluation is defined operationally as how the respondent describes himself /herself as a learner. Analysis of the verbal responses of the respondent separated his or her comments into the following categories: positive or approving self-reference, negative or disapproving self-reference, ambivalent self-reference, ambiguous self-reference, and reference to external objects and persons. Attitudes about Education Boshier (1973) explained attitudes about education as an extension of self-evaluation. He described his growth-motivated individuals as having intra-self congruence: They had by definition satisfied their lower-order needs in Maslow's hierarchy. They welcomed rather than rejected or feared new experiences. Because of

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-30their Intra-self congruence, Boshier said they were also self /other congruent. They demonstrated an independence from the environment which was "accompanied by a relative independence from adverse external circumstances, such as poor teaching" (1973, p. 258). Deficiency-motivated individuals, in contrast to growth motivated ones, were described as having intra-self incongruence and thus self/other incongruence. Boshier presented the person with self /other incongruence as entering a dissonant relationship which was stressful and anxiety ridden when the individual engages in an educational activity because of his or her perceived deficiency. Boshier saw the individual participant, whether deficiencyor growth-motivated, as a "unified system with two problems: maintaining harmony with himself and with the environment" (1973, p. 259). Thus, he said the deficiency-motivated (intra-self and self/other incongruent) person would either not enroll or would drop out of activities which threatened the harmony within the individual or between the individual and the environment. He asserted that "both adult education participation and dropout can be understood to occur as a function of the magnitude of the discrepancy between the participant's self concept and key aspects (largely people) of the educational environment" (1973, p. 260). Rubenson also examined the effect of attitudes about education on participation. He reported that "self-evaluation . . . and the values of the member and reference groups are of great importance in shaping a person's attitude to adult education" (1977, p. 30). Rubenson emphasized that past experiences, while having influenced the individual's attitudes about education, were of minor importance to

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-31partlcipation: "the main thing Is the traces they have left in the form of experience operating in the current psychological field" (1977, p. 31). Throughout Rubenson's research review, he emphasized the importance of an ahistorical approach to studying educational participation. Participation, according to the ahistorical approach, would be regarded as dependent solely upon events existing at a particular point in time. Miller (1967) did not address attitudes about education per se. Instead, he looked at attitudes in light of goals to be achieved through education. Therefore, his ideas are discussed under a later construct. Tough and associates (1980) also did not address this topic directly. Without defining attitude, Cross asserted that people's attitudes toward education "arise directly from the learner's own past experience and indirectly from the attitudes and experiences of friends and 'significant others'" (1981, p. 125). If they had positive attitudes as a result of successful educational experiences and if their reference groups valued education, they were more likely to participate in educational activities. For this study, a clear definition of attitude was needed. A definition of attitude which is appropriate to the use of the term as Cross used it was the stimulusresponse definition given by Cattell, Radcliffe, and Sweney (1963, pp. 62-63). They defined attitude as an individual's interest/need of a certain intensity to achieve a specific goal under a specified set of circumstances. Their definition of attitude is used here to define Cross's construct "attitudes about education" as applied to the subpopulation of adults addressed in this study.

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-32Constltutive definition. A person's (faculty member's) attitude about education is the interest of a certain intensity that he or she has In participating In educational activities (structured professional development activities). Attitudes may be positive, indifferent, or negative. The sources of a person's attitudes are the learner's own past experiences and the attitudes and experiences of friends, "significant others," and reference or membership groups. Operational definition . In this study, a person's (faculty member's) attitude about education (structured professional development activities) is defined operationally as the individual's expressed opinion of such activities. The individual's perception of other faculty members' opinions of his or her participation is also used to indicate the Intensity of the attitude. The individual's opinion of activities in computer technology will be explored as a case in point. Analysis of the verbal responses of the respondent will separate his or her comments into positive, indifferent, or negative opinions about participation in professional development activities in computer technology. Importance of Goals and Expectation that Participation Will Meet Goals ~ " Point C of the COR Model, importance of goals and expectation that participation will meet goals, reflects the expectancy-valence theory described by Rubenson (1977) and Vroom and Lewin before him. Rubenson (1977) and Cross (1981) equated "valence" to the importance of the goal (the result of an action) to the individual; they equated "expectancy" to the individual's subjective judgment that

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-33(a) participation in further education would lead to a desired reward and (b) that the individual would be successful in the educational activity. Both educators described a positive correlation between motivation of the individual to participate in educational activities and "a multiplicative function [of valence and expectancy] which results in a force. The strength of this force in relation to other forces acting on the individual determines whether the individual will participate in adult education or not" (Rubenson, 1977, p. 38). Rubenson also presented research which supported his contention that a person's goals and expectations were related to self-evaluation (and factors which influence one's self-evaluation) and attitudes of one's member and reference groups. Thus, Cross's model shows an interaction between point C and points A, self-evaluation, and B, attitudes about education, by using a reverse arrow. Miller (1967) found that Maslow's hierarchy of needs and the socioeconomic status of an individual could be used to explain that individual's educational goals. An assumption of this study is that all faculty hold middle class socioeconomic status. However, within academic life there is a unique (special) class system based on rank and tenure. In order to adapt Cross's model to the sub-population of adults addressed in this study, both the hierarchy of needs and academic class were used to explain a faculty member's participation in professional development. Adapting Miller's analogy, the newly appointed faculty member who has not yet gained tenure (hence in the lowest academic class) may participate in educational activities (professional development) in

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-34order to satisfy the three most fundamental needs from Maslow's scheme : 1. Survival needs must be satisfied before the activation of higher level skills. In higher education, this translates into knowledge of subject matter. Because rapid technological development results in shifts in information and skill demands, one expects professional development to be dominated by job training. 2. Safety needs reinforce the domination of professional development activities by job training because in the industrial society the greatest perceived deprivation is an economic one, and loss of job is the most general threat. 3. Belonging needs cover a wide range of associations including the pervasive needs for acceptance by the members of one's department and other groups which are important to the faculty member. For tenured faculty who have not achieved full professor status (the middle academic class), the higher order "ego needs" of Maslow's scheme become powerful motivators. Therefore, recognition is expected to be a high motivator for participation in courses leading to educational advancement. Miller (1967, p. 6) described achievement as generally distributed across all social (for this study "academic") classes and only indirectly related to participation in adult education (professional development). The need for self-realization, a drive that moves an individual towards being the most he is capable of being, is rarely a dominant need. However, the interest in career achievement of senior faculty

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-35members who hold full rank can transcend an interest in status, and these faculty members actively pursue self-development activities. Yet, the sustaining forces for professional development for the professors who have established themselves are strong. In their leadership positions within the department, they create and implement the technological shifts which provide either trouble or opportunity for other faculty members. They see education (professional development) as a comfortable and familiar tool for staying abreast of developments within their field and for improving skills. Boshier (1973) characterized all participants in adult education as deficiency or growth motivated. Carrying the "academic class" analogy through Boshier' s characterization of participants, nontenured faculty members who have not yet established themselves in their departments are deficiency motivated. They participate in educational activities for achieving gratification of lower basic needs, as a means to an end, or as a response to cultural expectations. In contrast, the tenured faculty are governed primarily by inner determinants rather than environmental or social ones: This is true of full professors even more than tenured faculty who have not attained that status. Tough et al. (1980) in his model of anticipated benefits divided what Cross called "goal" into three clusters of personal feelings (benefits) and five stages where benefits might be anticipated. The three clusters of personal feelings he named were (a) pleasure (an increase in happiness, satisfaction, enjoyment, or avoiding some unpleasant feeling), (b) self-esteem (maintained or improved selfconfidence), and (c) others (higher regard for individual by

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-36significant others). The stages where benefits might be anticipated were (a) engaging in a learning activity, (b) retaining the knowledge or skill, (c) applying the knowledge, (d) gaining a material reward (e.g. promotion or raise), or (e) gaining a symbolic reward (e.g. credit or degree). Cross (1981, p. 122) acknowledged that Tough's model was fragmentary and incomplete; however, she saw Tough's work as providing useful information on the conscious forces involved in motivation for learning. Point C in Cross's model (importance of goals and expectation that participation will meet goals) actually included two different but interdependent constructs: goals and expectancy. Motivation is strong at point C only if the individual believes a goal important to him or her is likely to be achieved through participation in an educational activity. Motivation decreases accordingly as a goal is less important to the individual or if the likelihood of success is in doubt. The constitutive and operational definitions of each of these constructs are presented separately. Construct: goals Constitutive definition . A goal is an objective or end that one strives to attain. The goals of an individual are derived from his or her experienced needs. The dimension of personal need follows Maslow's hierarchy of need with major participation in professional development activities aiming at the satisfaction of lower need levels (survival, safety, and belonging) and tapering off at higher levels (recognition, achievement, and self-realization). Other forces which strongly affect goals are one's social class (adapted to academic

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-37social class), technological change, and assoclational structures. The importance of a goal to an individual is expressed as valence (an affective attitude toward the result of an action). If the individual prefers attaining the result, he or she has a positive valence. Indifference toward the result is neutral valence, and negative valence indicates the person prefers not to attain the result. Operational definition. For this study, a goal is a desirable educational objective for which the individual is willing to exert effort. The desired objective could be increased rank or recognition or acquiring a skill. Goals identified by the faculty member were categorized using Maslow's hierarchy of needs and faculty member's academic social class. Construct; expectancy Constitutive definition . Expectancy is defined as a multiplicative function of two components — the expectation by the individual that he or she could successfully complete an educational activity and the expectation that his or her participation in that activity would result in certain positive consequences, namely, the accomplishment of or major movement toward the accomplishment of a goal. Operational definition. In this study, expectancy is the confidence expressed by the faculty member that his or her participation in a professional development activity will assist with the achievement of a goal he or she has established. Expectancies were described in terms of their strength. Subjective certainty that participation would be followed by a positive outcome indicated

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-38maximal strength while subjective certainty that participation would not be followed by a positive outcome indicated minimal (or zero) strength. To determine the faculty members' expectations of successful participation, statements concerning their preparedness for the activity and concerning their perception of control of their current situation (hierarchic structure) were categorized. Statements concerning "deficiency" or "growth" motivation for participation were used to identify self /other incongruence and thus non-participation. Indicators that the faculty members expected desirable consequences included (in addition to a straightforward statement concerning consequences) statements about the members' current situation (hierarchic structure), values of the member and reference groups, and knowledge of professional development activity possibilities. Life Transitions Cross (1981) when describing point D of her COR Model, life transitions, presented two rather different streams of research and theory: phases of the life cycle and developmental stages of growth and maturity. Life phases she described as qualitatively different periods through which people pass from birth to death. These phases were usually related to age and changing social expectations and could be viewed as a horizontal progression through life situations. Developmental stages, however, referred to an adult's continuous flow toward growth and maturity and involved vertical progression from simple to complex capacities.

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-39While many researchers and theorists on adult life cycles presented mixed images of these two streams, Cross emphasized the distinctions because of the profoundly different implications [for education] depending on whether one is talking about developmental stages or life-cycle phases. Whereas an educator might legitimately wish to help or encourage an individual to achieve a more advanced stage of ego development, the same case cannot be made for an educational goal of phasic development. The more likely role for an educator in phasic development is to assist with transitions and to help individuals adapt to the phase of the life cycle that is appropriate for their age and social role. (1981, p. 169) There was not much written on life transitions by the researchers whose works Cross credited as the foundations of the COR Model. Rubenson and Miller described life transitions and the role they played in motivation toward adult education very briefly while this construct was not mentioned by Boshier or Tough. Rubenson (1977) explained that the identification of the individual's position in the life cycle and the demands the individual was subjected to in his or her particular role determined the needs which the individual experienced as dominating. Miller (1967) claimed not only that there was congruence between Maslow's need hierarchy and the pattern of participation in adult education and with social class differentiations but also that Maslow's need hierarchy showed congruence with age and the life cycle. He argued that the early stages of adulthood are primarily concerned with satisfaction of the three lowest stages — getting established in a decent, stable job and beginning a family. As the cycle proceeds, the older person begins to devote energy to achieving status . . . , and to achievement in his field of work (the highest level of productivity is not reached until the forties and fifties). It is the rare person who begins to think about the meaning of his own life as the value of selfhood before he reaches his forties. (1967, p. 7)

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-40Cross's presentation on this construct was much more thorough than her presentation of the constructs previously discussed. She summarized numerous studies before presenting her matrix titled Descriptions of Life-Cycle Phases (see Table I) which was her synthesis of classification schemes that used chronological age as a rough index to life-cycle phase. Cross also presented a series of studies that have resulted from developmental stage research. Because Cross did not synthesize the developmental stages nor is there one widely recognized scheme, Loevinger's (1976) concept of ego development was selected to be presented in this study. Her concept was chosen because she defined stages of growth of the individual's personality and the concept was more inclusive than the schemes of moral or intellectual development. Loevinger's scheme also was appropriate because it focused on selfevaluation and paralleled Maslow's hierarchy of need. Her scheme titled "Milestones of Ego Development" is included as Table 2. Even though Cross (1981) pointed out the relationship between the gradual transitions of developmental stages and the more dramatic transitions of life-cycle phases, she included only life-cycle phases under point D of her model. She saw developmental stages as too gradual to be termed life transitions. In this study, the reason for identifying an individual's current life cycle phase was to determine if the individual was undergoing a transition. Cross postulated that sudden transitions serve as forces for learning. The constitutive and operational definitions of life transitions follow.

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-4160 O *H Q 1) *w p Tj ,n -J ni Co \j w •J ^1 to i[ 1 C3 C (U c n) •H 4.) CO (U d C M eu o o 3 CO JJ O o (U s >^ •H u 1-1 u 03 x: CO u •H 3 CO CO c p •H (0 3 o >-l e T3 CO C U-i CO >. O a M O U-l c O (U « •U O -H 3 C u CO (U C x: c TJ ca (1) -H •H a, iH 0) 0) XI T3 C , C -H CO CO -H (U >, -H CO 4-1 C •H 60 O CO rH C 4J XI ^ CO CO 4-10 1-1 CO O CO 60 (U Q . CO 0) 4J CO O C 3 O U •H 4-1 4J CO CO i-l (U (U <4-l U -H iH C T-l CO U 4-1 CO (0 cu 3 iH (3 CO >. CO T-l O 1-1 u T-l 4J X5 C CO O 4-1 O CO u >, O 4-1 t-l tH J= 3 O O ^ lU CO CO 4.| V ^ I-l 4-1 U > CO 01 U 0) CO 4-1 4-1 CO rH 0) CO C 4-1 (U h3 W W W W ^ 4J O CJ CO 4-J >, T-l 4J 3 tH cr c 3 OJ 0> a 4-1 u O O c tH o re o CO 4J CO a c tH I-l tH r-l . X5 a XI u V4 CO o o CO TP ho d u o T-l o d* CO c o o 0) (U •H u u 01 60 T3 I-l c CO c r-l CO CO I-l u tH u x: CO 3 x: o O. <: o s 00 «M I CO CM U o t4H x: CJ u CO 0) CO TH ^ ^ cn CO I 4-1 a\ CO CM

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-42u o 0) o a c O to •H 4J •U CO CO B 00 •H C n -H CO 3 T5 U > 00 -u 4-1 C U 0) V S 01 OJ CO o J= .c CO U 4J 4.1 S-l 01 CO O C M M-l O T3 o OO 00 c c CO .« c C CO (U 0) 4J > j: jr S CO CO 4J U EC CO 4J O 1-1 CO 4J » 14-1 B O 0) o a CO CO u £ CO 0) CO l-l +-l -d c CO DO 00 d 1-1 00 (U c (U CO 1-1 >t-i a CO •H CO O CO c OO o C -H 4J CO 4-l a tl (U T) o a CO XI C c o , l-l j: •H 4J r-t CO 3 a. (u S s O -H CJ 4J CJ C CO CO CO U O Q. O c O (U S B o Q. 4-1 •H iH S CO •H Jli O CO 3 4-i a U CO T5 <4-l 1-4 4J tH rH o a H 1-4 X) 4J 00 CO •H CO C 4J CO Wi -H C e ^ o 4-4 3 D. 13 1 •a c CO CO o 0) a a CO 1 cx S o o CO a o 01 0) 1-1 i c s U3 1-1 o J3 CJ O CO c 0) J= c o x> •o lo tl c 4J CO a CO CO Cu CO 0) C 0 u 1-1 4-1 l-l u O TJ a o CO 0) u m u CO iH o c: c 4J a 1-1 01 0) CO 1-1 4-1 > U OJ iH U 0) CO M CO a 0) f-i a, >, •a 4J CO w C C U 01 1-1 « iH iH > c l-l CO -H 3 00 3 >, -u a 0) x: CJ z CL, <: 4J e 4-i CO rH O XI c HOC U 1-1 0) O. u l-l CO j: u •H AJ CO CO iH Q, CO CO OJ O
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-43CO 1 4J 0) B u (U o (U o c e > c « T> . 4-1 o 00 o O 3 00 o •<-) tH o o c k4 , to (U S-l i-H •H 0) to O 4-1 u > CO CO to to 14-1 OJ O Xi CO 4J •H CO •H «-( iH !^ to -s CO 60 tu (U 3 (fl > M-i •H c 60 10 (U o to CO to CO to J2 U 3 c U CO a c to o o u lU (U V a •H •T3 u tn to CO (U tj tH CO to Q a: •H B > (id 0) l-i to tlO < n to tt) to to x; |X| to 4-1 c d) e CO 0) tu ao (U u c c H to c o a> M-i 4J T3 (K e c c a) i-i -H -H e to > (U O 0) -H •H 00 C •U >, 10 S 0) J (U eei PO 2 3 3 4) O CO 3 O >^ a, ^ CO 1-1 ^ 10 to -a c c 1) 1-1 •H U 4J <4-l U-l > ai oj in u-l vo

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-441 h >, o 1 jj C/3 60 iH 0) c «0 > •H 3 r-l •> •r-l a 4-1 rt >^ 4-1 3 u •H 4J 0) O 4-> tA c O, U 00 v d 00 (U -H o )-i O 3 O fH u 0) O >4-l c o. 4-1 o w o 0) c o CO 1-1 3 4J o CO o. o 3 DO o d u o (U CO l-l r-l (U 3 4J a u s « M V4 (8 J= 60 CO >% « 3 i< CO CO >% CD 1-1 0) o cd 60 4J 60 O 0) « 60 CO cd o CO 10 iH > 3 -O CO iH CO O V n u 60 u a 3 c 4-1 I o r-t -a , 60 O CO CO O 4J C U C CO 'i-l -H Q. O tH i-( f-t CD 4J « -H e « ^4 >-i 0) CO CO 4J CO O I CO 60 a V c cj c rH « , 4J 3 4-) 4J 4-1 tH CO y rH >*H c a o o CO U C ^ CD S 3 dJ O <0 14H ^ <4H e 00 o •H > 00 •rl CO 4J o. 01 Q) CO CO CO E 60 £ c O u > CO iH XI 1 0) 4J rH <4H •H iH (U S-i rH x: CO 1 CO CO en cx U CO iH > 3 0) a T) •H 3 iH CO o o 4J o. 4J tH CO CO •H CO « c IH O 60 4J c 4J 60 rH rH 60 -H 0) CO •H H a Q. C CJ 4J •H X3 0) X >, >> lU CO 0) rH d o •H •H CO 3 C a CO 3 4H (U 4J a JZ CO 60 rH 3 XI CO y 60 y d iH 60 -H 4J d N CD 0) CO > -H tH rH CO CO rH iJ 3 •H 4-1 -H y o CO O -H rH CO XI 3 a o> n >> a PH CO M CO (U y 0) 4J o u a I UH rH 0) CO d 3 4J o o. a, o CO 4-1 d rH CO •v4 0) 0) 3 rH t4H 4J 60 3 o X ^ 0) d a> 60 o CO o a d •rl rH 4-1 CO 4J CO CO O >^ CO CO •H 60 4.1 OJ 4J iH d a CD XI 4-1 y CD CO CO e* d iH 3 CO

•H 0) d 4J CO a 1 CO •H d i-i <4H 4-1 o 0) rH CD y y 4J 4J CO •H e C3 C(H d o u I 00 3 o d 0> •H y CO d o o a m o I4H d o y CO 00 3 o d 0) y CO d o CJ

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-Asia 3 O •H O 09 c o u Vi > c o u w c o a u o o u (U >. CO CO e o to o o 0) 0) I-I iH -i U 4J 4J CO ^ M-l o 4J CO 3 a 3 a o o a >-i 4-1 u-i O. J3 to O O (U r-{ U U % 3 to aJ -H >> T3 to > xi c a. C Oi to O CO O 60 y-l rH rH 3 O to to >. -H O CJ CM 4-1 rH rH 3 I-I to to x; O lU •H ^ 60 O '4H t-l o u •H > I I CM 4J >4H rH X rH 0) 0) , CJ rH 01 to O. 3 to -o 0) -H OS > to 3 o T3 3 O 0) IM 4-1 3 4J -H CJ 0> 0) « O C3. >, 3 CO S 01 0) O T3 OS 3 3 O 0) 4J O. 3 OJ to I CO 3 T3 O 01 CJ 0) 3 4-1 W •H 0) 3 3 3 60 -r-l 3 3 O 60 -H Q. 3 4J O -H to U 4J U 60 C >^ •H 4J o > •H TJ 3 U <0 I V 3 to iH 3 -H ^ iH o 10 3 3 60 3 -H 3 3 to iH (U 4J -I M 4-1 tH to O • 3 3 CO 3 O 4J O CJ MH o 00 3 i o e o CM 3 3 O O -H O 4-1 0) 4-1 to 60 > CO 3 o fH > (U u a. 3) J3 O 4J 60 3 a. a. to 3 O l4 o CO T3 0} o 4-1 3 O T3 CO to 3 to OJ o k4 o; CJ u 3 O CO

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-46Constitutlve definition. Life transitions are gradual or dramatic periods of change which require adjustments to new positions in life. Operational definition. For this study, the individual's position in life is described using the life-cycle phases described by Cross. A faculty member was considered in transition if he or she had experienced within the past 18 months one of the "marker events" listed in Cross's descriptions of life-cycle phases. Opportunities and Barriers Cross (1981) postulated that motivation to participate in learning activities depended largely on points A through D of the COR Model. Point E, opportunities and barriers, became important after an adult was motivated to participate. Adults with strong motivation, she claimed, were likely to seek out educational opportunities and overcome modest barriers. Conversely, modest barriers were likely to preclude the participation of weakly motivated adults. Cross claimed, however, that establishing new opportunities for adult learners was "just as important to adult participation as removing barriers, especially over the past ten years" (1981, p. 147). She mentioned new programs which were established to meet special needs and interests of mature learners (e.g. , the open university and elderhostel); she also noted other new opportunities which were made available by more convenient schedules and locations, more efficient delivery systems, and more appropriate content and teaching methods (e.g., telecourses and weekend colleges). Cross pointed out that many of the most successful new opportunities were not a direct response to

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-47consumer demand. "Positive forces will be generated at point E in the COR Model to the extent that imaginative educators can formulate new programs, perhaps undreamed of by potential learners, that strike people as a better way to do things" (1981, p. 149). Relatively little was written on opportunities (compared to their discussions of barriers to participation) by Cross or the other four researchers. Boshier focused on how to increase participation in educational opportunities by working with people in organizations to which they already have ties (e.g., industry, labor unions). Rubenson emphasized that opportunities are not enough; the intended participant must also expect that participation will have positive consequences. Boshier's and Tough's research included individuals who were already involved in educational activities and did not address other opportunities . Cross summarized research data on obstacles to participation in adult learning activities. The barriers which individuals said prevented them from participating were categorized under three headings: situational, institutional, and dispositional barriers. Situational barriers were those which arose "from one's situation in life at a given time" (1981, p. 98). Lack of time, lack of money, lack of child care, and lack of transportation were considered situational barriers. Institutional barriers included "all those practices and procedures that exclude or discourage working adults from participating in educational activities—inconvenient schedules or locations, full-time fees for part-time study, inappropriate courses of study . . ." (1981, p. 98). Classified under dispositional barriers were negative attitudes and self-perceptions about oneself as a learner.

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-48Cross suggested that "the barriers people identify on surveys should be viewed with healthy skepticism" (1981, p. 146). However, she thought it helpful to summarize the major barriers identified (in descending order of mention): (a) lack of time, (b) costs, (c) scheduling problems, (d) assorted institutional requirements/red tape, (e) lack of information about appropriate opportunities, (f) problems with child care or transportation, (g) lack of confidence, and (h) lack of interest. Rubenson (1977) classified educational barriers under two headings: psychological impediments and external environmental obstacles. His psychological Impediments equated roughly to Cross's dispositional barriers and his environmental obstacles included Cross's remaining categories — situational and institutional barriers. Boshier described the barriers to participation in terms of social, psychological, and institutional incongruence. He contended that the variables usually described as the reasons for discontinuing an educational activity were actually mediating variables which "trigger dropout if intra-self or self/other incongruence has developed" (1973, p. 261). Miller (1967) did not classify what he saw as barriers to participation but he did present "forces" within the social class structure which he believed discouraged participation in educational activities. These negative forces are listed in the force field diagrams of Appendix A. Tough did not discuss barriers. Cross treated barriers to participation differently than the other researchers. Those dichotomous dispositional factors which could positively or negatively influence participation were treated as

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-49separate constructs in her model. For example, lack of confidence (a psychological impediment under Rubenson's scheme) she Included under construct A, self-evaluation: Self-confidence was viewed as a motivator and lack of confidence was believed to result in lack of motivation to participate. Thus, barriers in this study refer to the barriers which were categorized by Cross as situational or institutional. The two elements of point E in the COR Model are presented separately. Construct; opportunities Constitutive definition. An opportunity is a chance for an adult learner to participate in a learning activity. Operational definition. For this study, an opportunity to participate in a learning activity is any structured activity which is available to a faculty member that enables the faculty member to acquire computer skills and/or information that he or she does not already possess. The structured activities available to the faculty through their academic departments, professional organizations, or other campus organizations were considered opportunities. Construct; barriers Constitutive definition. A barrier is a hindrance which discourages an adult from participating in a learning activity. Operational definition. For this study, a barrier is anything which discourages a faculty member from participating in a structured learning activity on computer skills. Examples of barriers include

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-50the scheduling of learning activities which conflicts with teaching schedules, transportation problems, prohibitive demands on time, and family responsibility. Information Lack of information about educational opportunities was treated as a barrier to participation by Rubenson (1977), Boshier (1973), and Miller (1967); however. Cross thought it was important enough to identify it as a separate construct. Information was included as point F in her model. She emphasized the importance of accurate information for providing the link between motivated learners and appropriate opportunities. "Without accurate information," she said, "point E in the model is weak because opportunities are not discovered and barriers loom large" (1981, p. 127). Constitutive definition . Information is an awareness of the individual's opportunities for educational activities. Operational definition. For this study, information is a faculty member's awareness of structured professional development activities on computer technology. The individual's knowledge of activities was compared to descriptions of opportunities which were disseminated to the faculty by the sponsoring organization or department at the University of Florida (i.e.. Office of Instructional Resources, Center for Instructional and Research Computing Activities, Northeast Regional Data Center, Sponsored Research, Office of Academic Affairs, and professional organizations).

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-51Partlcipatlon Cross (1981, Ch. 3), while laying the foundation for her COR Model, discussed the different criteria used in various research studies to define "participation" in adult education. When the broadest definition — "sustained deliberate efforts to learn" — is used, investigators generally agree that virtually everyone can be classified as a participant. . . . When the definition is limited to "receipt of instruction" or "organized learning," participation rates vary from roughly 12 to 30 percent of the adult population. . . . Figures from numerous state studies conducted in the early 1970s suggest that a more realistic estimate would be one of three adults participating in some form of organized learning activity. (p. 52) Cross (1981, p. 53) described the adults depicted by her COR Model as part-time learners in "organized instruction." These learning activities were usually non-credit, and they usually were offered to groups of learners in classlike formats. While completely self-directed learning projects were excluded, tutorials and professionally prepared courses of instruction that were independently pursued (i.e., television and correspondence courses) were included. These learning activities were offered by organizations such as continuing education and extension divisions of colleges and universities, industry, community agencies, and labor unions. The definitions of participation by the four scholars whose works Cross utilized as she designed her model did not all coincide with her definition. Tough (1978), for example, focused on self-directed learning projects rather than enrollment in organized classes. Rubenson (1977) viewed adult education as one of many forms of social participation which are often aimed at some form of achievement. Boshier (1973) defined a participant as an adult who attended at least

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-52two sessions of an organized class. He further defined a dropout as a person who, after attending the first two classes, was absent from the mid-point session and four successive sessions. Miller (1967), whose definition comes closest to that of Cross, examined the voluntary involvement of adults in learning activities; and he presented their "level" of participation as a product of positive and negative forces which are both psychological and situational. Constitutive definition . Participation is the act of taking part in an organized learning activity. Operational definition . For this study, participation is defined as enrolling in a professional development activity related to computer skills and/or information. Three levels of involvement were noted. Level 1 (the lowest level) denoted the faculty member who attended four seminars on computer technology but had not applied what he or she learned. Level 2 indicated that the faculty member attended more than four seminars on computer technology but had not applied what he or she learned, or that the faculty member attended only four seminars but also had applied what he or she learned. Level 3 indicated that the faculty member had participated in more than four seminars and also had applied what he or she learned. The level of participation was determined from attendance records kept by the organizations sponsoring the learning activities and by self-report. Cross (1981) postulated that faculty members who voluntarily participate in structured learning activities and evaluate their participation positively are more likely to have a positive selfevaluation and attitude about education. Thus, the cycle begins again which results in participation.

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-53Summary In summary, Cross based her Chain-of-Response Model primarily on the works of four researchers in adult education: Miller, Rubenson, Boshier, and Tough. She proposed her COR Model to explain participation in adult learning activities. While her model included all adults involved in adult learning activities, this study focused on those adults who were faculty at a postsecondary educational institution. The seven constructs included in Cross's model were self-evaluation, attitudes about education, importance of goals and expectation that participation will meet goals, life transitions, opportunities and barriers, information, and participation. The constitutive and operational definitions of her constructs served as a basis for assessing the utility of the model for describing college and university faculty members who participate in structured professional development activities on computer technology.

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CHAPTER III THE DEVELOPMENT OF THE INTERVIEW SCHEDULE An interview schedule was designed to assess whether the respondent, a University of Florida faculty member, could be described by the constructs in the adapted COR Model. In order to move from construct definitions (given in Chapter II) to interview questions, an intermediate step was necessary. Thus, statements which could be used to describe faculty members who fit Cross's constructs were written for each construct, and decision rules were established by which the degree of congruence could be measured. These descriptive statements were submitted to Cross along with the construct definitions for her approval and/or revision. Descriptive Statements of COR Model Constructs Self-Evaluation Descriptive statements . Faculty members who perceive themselves positively and have confidence in their own abilities may be described by the statements that follow. The corollaries which arise in statements with opposite meanings are descriptors of faculty with poor self-evaluations . 1. Consider themselves well prepared for their present position. 2. Rank themselves as instructors in the top quartile of their department . -5A-

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-553. Rank themselves as researchers in the top quartile of their department . 4. Describe themselves as good at learning new things. 5. Describe themselves as enjoying new learning experiences. 6. Have or would participate in professional development activities because of a concern for self-development, apart from any status these confer. Decision rule . Individuals who can be described by at least five of the descriptive statements will be placed in the highest of three levels of self-evaluation. Individuals who can be described by two or less of the descriptive statements will be placed in the lowest level. Attitudes about Education Descriptive statements . Faculty members who have positive attitudes toward professional development activities may be described by the statements that follow. The corollaries which arise in statements with opposite meanings are descriptors of faculty with negative attitudes toward professional development activities. 1. Believe professional development activities are needed or helpful to them personally. 2. Believe professional development activities are important to their institution. 3. Perceive that their reference groups value professional development activities. 4. Have enjoyed past adult education activities. 5. Have enjoyed past professional development activities.

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-566. Look forward to this kind of association with faculty colleagues . Decision rule . Individuals who can be described by at least four of the descriptive statements will be placed in the highest of three levels of attitude. Individuals who can be described by two or less of the statements will be placed in the lowest level. Goals and Expectations Descriptive statements . Faculty members who are motivated to participate in professional development activities have the following characteristics with respect to goals and expectations: 1. Have a goal that is related to the professional development activities (at least indirectly) . 2. Believe participation in the professional development activities will lead to the achievement of the goal. 3. Believe they are sufficiently prepared to successfully complete the professional development activity. 4. Believe achievement of the goal will satisfy a need, associated with academic class. Decision rule . Individuals will be categorized into two levels — positive and negative— for each of the two constructs under goals and expectations. Both statements "1" and "h" must describe the individual if the person is to be classified as fulfilling the requirements for a positive goal orientation. Both statements "2" and "y must describe the individual if the person is to be classified as having positive expectations. In order to receive a positive

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-57rating for the combined construct (goals and expectations), the individual must receive positive ratings for each of the categories. Life Transitions Descriptive statement. Faculty members who participate in professional development activities may be described by the statement that follows concerning life-cycle phases. Describe themselves as experiencing a dramatic change. Decision rule. Three levels of life transitions will be designated. Individuals who have experienced at least six events in their lives which would fit into Cross's list of events which bring about life transitions (see Table 1) will be placed in the highest level. Individuals who have not experienced any of the lifechanging events will constitute the lowest level. Opportunities and Barriers Descriptive statements. Faculty members who participate in professional development activities may be described by the statements that follow concerning opportunities and barriers. 1. Identify themselves as eligible to participate in structured activities on computer technology sponsored by their academic departments, professional organization, or other campus organizations .

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-582. Can identify several structured activities on computer technology which they believe would benefit them professionally. 3. Believe they can overcome any situations which they identify as barriers. Decision rule. All three statements must describe the individual if the person is to be classified with a positive orientation toward opportunities and barriers. Information Descriptive statements. Faculty members who have an awareness of their opportunities for professional development in computer technology may be described by the statements that follow: 1. Can identify several structured activities on computer technology which are available. 2. Can describe existing opportunities for professional development activities on computer technology. Decision rule. Individuals can be categorized into three levels of awareness of professional development opportunities on computer technology. The highest level indicates the person is aware of organizations who are sponsoring such activities and can describe more than one activity. The lowest category indicates the person cannot describe any opportunities for professional development in computer technology nor can he or she identify organizations who sponsor such activities. The person who can n£ime at least one sponsoring organization and/or can describe at least one offering will be categorized on the second level.

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-59Participation Descriptive statements . Faculty members who are participators may be described by these statements: 1. Are/have attended professional development activities voluntarily. 2. Are/have attended professional development activities on computer technology voluntarily. 3. Evaluate their participation in professional development activities positively. 4. Evaluate their participation in professional development activities on computer technology positively. Decision rule . Individuals will be placed in one of five levels to indicate the number of descriptive statements that describe the individual. The highest level indicates that all four statements are true for the individual while the lowest level indicates none of the statements are true. Interview Schedule Construction The descriptive statements for the constructs of the COR Model served as a guideline for the development of interview questions and of statements to be used on the Likert-style instrument which was administered at the end of the interview. The Likert-style instrument (entitled Faculty Questionnaire) was used as a second method of measuring the constructs of the model. Care was taken during the development of both the interview questions and Likert-style statements on the Faculty Questionnaire to include at least one

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-60question or statement which addressed each facet of the constructs. (See Appendix E for a list of descriptive statements cross-referenced to the COR Model Interview Schedule and the Faculty Questionnaire.) During instrument development, the writer adhered to the following recommendations of Parten (1950) on the wording of questions: 1. Use simple words which are familiar to all potential [respondents] . 2. Make the questions as concise as possible. 3. Formulate the questions to yield exactly the information desired . 4. Avoid "double-barreled" or multiple-meaning questions. 5. Avoid ambiguous questions. 6. Avoid leading questions. 7. Avoid "danger words," catchwords, stereotypes, or words with emotional connotations. 8. [Where appropriate] include indirect questions. 9. Be cautious in the use of phrases which may reflect upon the prestige of the [respondent]. 10. Allow for all possible responses. 11. When a long check-list is used, use card questions or see that the items are rotated on different runs of the schedules . 12. Keep to a minimum the amount of writing required on the schedule . 13. Plan to include a few questions that will serve as checks on the accuracy and consistency of the questions as a whole . 14. Avoid questions that call out responses toward socially accepted norms or values. 15. Avoid apparently unreasonable questions by using a brief explanation justifying the question. 16. Plan to compare the responses to other questions which put the same issue in different contexts, (pp. 200213) Before conducting a pretest of the interview schedule, the schedule was submitted to an expert in social research with experience in interview schedule construction. This person was asked to critique the schedule, paying special attention to the following areas: (a) the wording of the questions (especially number three from Parten's recommendations—formulation of the questions to yield exactly the information desired), (b) the sequencing of the questions, (c) the

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-61physical form of the schedule, (d) the coding of responses to the questions, and (e) the interview guidelines for persons who would be administering the schedule. The recommendations of the expert in social research were incorporated before the pretest was run. Interview Guideline Development To insure that the data obtained on the adapted version of the COR Model would be worth analyzing, the processes by which the information was obtained was controlled. Therefore, all significant elements of the interview situation — the interviewer, the surroundings of the interview, the respondent, and the process of questioning and recording — were described in the interview guidelines. A preliminary listing of interview guidelines was submitted to an expert in social research along with the interview schedule for the expert's suggestions. The guidelines were revised as necessary based on the expert's suggestions and based on problems experienced during the pretest of the schedule. (See Appendix F for Interview Guidelines.) Pretest of the Interview Schedule Bailey (1978) in his book Methods of Social Research (pp. 129132) described what he considered to be one of the most important stages in interview schedule development— the pretest. This study incorporated his recommendations. A rough draft of the schedule was used with a few respondents so that flaws could be identified and corrected. The sample used for the pretest was three faculty members with backgrounds which were similar to the target group of this study.

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-62Members of this initial sample were asked for their critical analysis of all aspects on the questionnaire (such as question wording, question order, redundant questions, inappropriate or confusing response categories, items that were poorly scaled, and any other aspects of the questionnaire that they found inadequate) in addition to answering the questions as instructed. Priority in analyzing pretest information was given to the respondents' marginal comments and opinions. All of the respondents' recommendations did not result in schedule changes; however, all comments were examined for needed revisions. Following the analysis of critical comments, nonresponses, patterns of response, and questions that were answered with qualifications, came the analysis of questions that did yield useful data. Appropriate changes in the interview schedule were made. (See Appendices G and H for a copy of the COR Model Interview Schedule and the Faculty Questionnaire, respectively. )

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CHAPTER IV DATA COLLECTION AND ANALYSIS The problem addressed by this study was to determine whether it was possible to describe college and university faculty members who participated in organized professional development activities using Cross's Chain-of-Response Model. The focus of the study was narrowed to participation in organized professional development activities on computer technology. Computer technology was selected because the need for development of computer knowledge and skills transcended alt disciplines and because records of faculty participation in educational activities related to computers were available through the Faculty Support Center for Computing at the University of Florida. Population Studied The population included in the study were assistant, associate, and full professors who were home based at the University of Florida (UF) . The faculty who met these criteria were divided into participants and non-participants in structured professional development activities in computer technology. Records kept on attendance at computer seminars sponsored by the Faculty Support Center for Computing at the University of Florida were used for the initial separation of participants from non-participants. In order to identify faculty with strong participation, only faculty who had visited the Faculty Support Center at least four times (the mean -63-

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-64number of visits of all faculty who had visited the Center as of January 1985) were assigned to Group I. A sample of 15 faculty members was randomly taken from this group to be interviewed. The faculty who were in the same departments as the sample for Group I and who had not visited the Faculty Support Center were initially considered non-participants and assigned to Group II. Again, a random sample of 15 faculty members was selected for the study. In cases when the faculty member randomly selected from either group was outof-town on sabbatical, declined to participate in the study, or was unavailable for other reasons, a replacement was randomly selected from the appropriate group. Data Collection Faculty members selected for the study were sent letters apprising them of the study before they were contacted to schedule an interview. (See Appendix I for a copy of the letter.) Approximately one week, later the faculty member was called for an appointment time. During the telephone conversation, additional information concerning the purpose of the study was given, the amount of time and setting needed for the interview were discussed, and the interview was scheduled. (See Appendix J for the Initial Telephone Contact Guide.) Faculty responses to the initial contacts (letter and telephone call) were positive with only one person declining to participate in the study. However, some difficulty was experienced in contacting faculty members by phone and in scheduling interviews around their busy schedules. As a result, the interview process extended over a three-month period.

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-65All interviews were arranged and conducted by the same person. In each case, care was taken to control the setting of the interview to prevent disruptions. The interview schedule was administered first; then, the written questionnaire was completed while the interviewer waited. In one case, however, the respondent was leavingthe country and only had time for the oral portion of the interview. He requested that he be allowed to return the written Faculty Questionnaire by mail, which he did within one week of the interview. Steps of Data Analysis The data gathered for this study were both qualitative and quantitative, but primarily qualitative. The procedures for analysis of qualitative data which were outlined by Miles and Huberman (198Aa, 1984b) were utilized. The analysis of data consisted of three concurrent activities: data reduction, data display, and conclusiondrawing/ verification . Data Reduction Data reduction is a form of analysis that sharpens, sorts, focuses, discards, and organizes data so that conclusions can be drawn and verified. The design of the interview schedule, the selection of data to be recorded as field notes, and the simplification and coding of the raw data from field notes are examples of anticipatory data reduction. By actively preplanning the kind of data to be collected, internal validity and manageability of the data were emphasized.

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-66In many instances, but not all, the data were converted into numbers or ranks (quantification). Where qualitative data were quantified, the numbers and the words used to derive the numbers were kept together during analysis. (See Appendix L for the Code Book. ) Data Display Particularly useful in organizing the qualitative data so that conclusions could be drawn were the development of matrices, graphs, networks, and charts. The design of the data display, an important step in analyzing qualitative data, helped prevent the tendency to overly simplify or jump to hasty, partial conclusions, a danger when using only narrative text. Conclusion-Drawing/Verification Conclusion-drawing began with data collection as the researcher noted regularities, patterns, explanations, possible configurations, causal flows, and propositions. Initially, the conclusions were vague and tentative. They became increasingly explicit and grounded as data reduction and display revealed a logical chain of evidence and conceptual/ theoretical coherence . Several techniques suggested by Miles and Huberman (1984a, 1984b) were used for drawing meaning from data displays. Counting was used to help the researcher get an overview of the data more easily and rapidly and to facilitate generalization. Patterns or themes within

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-67the data were noted, data were clustered, and plausible conclusions were carefully examined for discrepancies. In a few instances, the researcher found it necessary to differentiate between parts of constructs in order to draw a clearer understanding of the relationship between the construct and participation in professional development. Particulars of the research were subsumed into the study's conceptual framework and relations between variables were noted. Because the purpose of this study was to collect information which would confirm or call to question the credibility of a conceptual framework, the researcher critically examined the data for a logical chain of evidence which would support Cross's theory. Conclusion-verification techniques included making contrasts/comparison, checking the meaning of outliers, looking for negative evidence, and recording discussion and review to develop intersub jective consensus. The researcher conducted all interviews; a second person with no vested interest in the outcomes of the research coded the data gathered. Also, methodological triangulation was used for verification by comparing the data given in response to the questions asked orally from the interview schedule to the data from the written responses of the Likert-style instrument which measured the same constructs. Statistics which were used to differentiate between the two groups were median scores, percentile rank, and Spearman rank correlations. The chi-square test was used to determine statistical significance .

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-68Analysls and Discussion of Data Characteristics of the Respondents The respondents of Group I were randomly selected from University of Florida faculty members who had participated in four or more structured educational activities at the Faculty Support Center for Computing. Group II was randomly selected from faculty who were matched to Group I for college and department but had not participated in structured educational activities at the Faculty Support Center. After sample selection, the researcher determined the level of participation through interview. None of the members of Group II had attended any Faculty Support Center activities; however, four faculty members from Group II had attended one session on computer technology which was sponsored by another organization. Because participation for this study by definition required attendance at a minimum of four sessions on computer technology, the four remained in Group II nonparticipants. The demographic characteristics of both groups are found in Table 3. Evaluation of Data by Construct Data were gathered about the respondents from several sources, the primary source being the respondents themselves during the interview. Other sources of data were catalogues of the various colleges (consulted for college, departments, and title of faculty members) and records of the Faculty Support Center (consulted for attendance). The data gathered were coded and computer sorted according to construct for each individual and group.

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-69Table 3 Demographic characteristics of respondents by group Characteristics Group I (n = 15) Group II (n = 15) Number of colleges represented Number of departments represented Sex Male faculty members Female faculty members Academic rank Assistant professor Associate professor Full professor Distinguished professor Graduate research professor Administrative title No Yes Primary assignment Teaching Research Service Administration Teaching and administration Years at the University of Florida Range Mean Appointment 9 months/year 12 months/year 9 14 11 4 3 5 6 0 1 14 1 3-23 years 11.27 years 5 10 Prior participation in learning activities on computer technology Non-participants 0 Level 1 (4 sessions) 1 Level 2 (4 sessions + application) or (> 4 sessions) 4 Level 3 (> 4 sessions + application) 10 9 14 13 2 4 4 7 0 0 13 2 8 2 2 3 0 2-34 years 12.53 years 7 8 15 0 0 0

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-70The Statistical Analysis System (SAS) was used to run statistical tests on the data. Also, SAS was used to generate tables and graphs so that the data could be more easily understood. Construct; self-evaluation Treatment of data from COR Model Interview Schedule . Selfevaluation is the general or global value which a person ascribes to himself. Operationally, this translates into how the respondent describes himself /herself as a professional educator. During the interviews, the faculty members were asked questions about their job preparation, teaching and research performance, and aptitude for learning new things. (See Appendix G for the COR Model Interview Schedule.) Each faculty member's responses to the interview questions were used to determine whether the descriptive statements, which were approved by Cross as characteristic of faculty with positive selfevaluation, could be appropriately used to describe the faculty member. A decision was then made concerning the individual's overall self-evaluation relative to the self-evaluation of others included in the study. Table 4 lists the decision rule used to categorize faculty into positive, less positive, and least positive levels of selfevaluation and indicates the appropriateness of the descriptive statements by individual and group. Self-evaluation levels in both Group I (participants) and Group II (non-participants) ranged from "positive" to "least positive," with the median score for Group I being three, "positive," and the median score for Group II being two, "less positive."

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-71Table 4 Breakdown of construct stance by descriptive statements Construct; Self-evaluation (data source = interview) Respondents 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Group yes Summaries no 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Group Summaries yes no Descriptive Statements Individual 1 2 3 4 5 6 Summary* -s) yes yes yes no yes no less positive yes yes yes no yes yes positive yes yes yes yes yes yes positive no yes yes yes yes yes positive yes yes no yes yes no less positive yes yes yes yes yes yes positive yes yes yes yes yes yes positive yes yes no yes yes yes positive yes yes yes no yes no less positive yes yes yes yes yes no positive yes yes no yes yes yes positive yes yes yes yes yes no positive no yes no yes no no least positive yes yes no yes yes yes positive yes yes no no yes yes less positive 13 15 9 11 14 9 10 positive 2 0 6 4 1 6 4 less positive 1 least positive ipants) yes yes no yes yes yes positive no yes yes no yes no less positive yes yes no yes no yes less positive yes yes no no yes yes less positive yes yes no no yes no less positive yes yes no no yes yes less positive yes no no yes yes no less positive yes yes yes yes no yes positive yes no yes yes yes no less positive yes yes yes yes no no less positive yes yes no yes yes yes positive no no no yes yes no least positive yes no yes yes yes yes positive yes yes no yes no yes less positive yes yes yes yes yes yes positive 13 11 6 11 11 9 5 positive 2 4 9 4 4 6 9 less positive 1 least positive Decision rule: Individuals who could be described by at least five of the descriptive statements were placed in the highest of three levels of self-evaluation. Individuals who could be described by two or less of the descriptive statements were placed in the lowest level.

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-72Comparison of data from interview schedule to data from Faculty Questionnaire . The Faculty Questionnaire, administered at the end of the interview, consisted of several statements which were closely tied to the descriptive statements of the seven constructs in the model (see Appendix H) . The same decision rule that was used to categorize faculty into the three levels of self-evaluation based on interview data was used to categorize faculty based on questionnaire data. Again, a full range of self-evaluation levels was found for each group; however, both groups evaluated themselves less positively on the written questionnaire than they did orally. The median level for both groups on the questionnaire data was two, "less positive." Figure 3 plots the level of self-evaluation by the frequency of individuals in each level by group and by source of data. Extent to which findings support COR Model . Cross (1981), in her COR Model, asserts that adults who perceive themselves positively and have confidence in their own abilities are more likely to participate voluntarily in structured learning activities. Thus, one would expect that the faculty at the University of Florida who perceive themselves positively and have confidence in their own abilities would be more likely to participate voluntarily in structured learning activities on computer technology. One null hypothesis relative to self-evaluation which was tested by this study was as follows: Hypothesis A-1 . There is no difference between selfevaluation and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was

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Figure 3. Level of self-evaluation by frequency.

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-74no significant difference at the p =< .10 level between Group I and Group II on the self-evaluation data gathered by use of the interview schedule or the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) A second null hypothesis relative to self-evaluation which was tested by this study was as follows: Hypothesis A-2. There is no difference among selfevaluation and the levels of participation in professional development activities on computer technology by faculty at the University of Florida To test the hypothesis, the level of self-evaluation was compared to the level of participation. Only Group I respondents were used because Group II respondents were non-participants by definition. The level of participation was defined as follows: Level 1 (the lowest level) denoted the faculty member who attended four seminars on computer technology but had not applied what he or she had learned. Level 2 indicated that the faculty member attended more than four seminars on computer technology but had not applied what he or she learned, or that the faculty member attended only four seminars but also had applied what he or she learned. Level 3 indicated that the faculty member had participated in more than four seminars and also had applied what he or she learned. There was no significant difference at the p =< .10 level among self-evaluation and levels of participation for the data gathered by use of the interview schedule; however, written questionnaire data showed a significant difference (p = 0.0291) and a negative Spearman correlation of -0.663. Because of conflicting data, the researcher failed to reject the null hypothesis A-2.

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-75The fact that the researcher found no significant difference between Group I and Group II on self-evaluation nor a significant relationship among self-evaluation and levels of participation neither adds support for or against the applicability of the COR Model. Several constructs are included in Cross's model which she said led to participation. The minimum criterion for acceptance of the model — a positive self-evaluation by participants — was met. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) Construct; attitudes about education Treatment of data from COR Model Interview Schedule . A person's attitude about education is the interest of a certain intensity that he or she has in participating in educational activities. Operationally, this translates into the faculty member's expressed opinion about professional development activities on computer technology. The individual's perception of other faculty members' opinions of his or her participation is also an indicator of the intensity of the attitude. During the interviews, the faculty members were asked questions about the usefulness and pleasure derived from participation in professional development activities. (See Appendix G for the COR Model Interview Schedule.) Each faculty member's responses to the interview questions were used to determine whether the descriptive statements, which were approved by Cross as characteristic of faculty with positive attitudes about education, could be appropriately used to describe the faculty member. Table 5 lists the decision rule used to categorize faculty into "positive," "less positive," and "least positive" levels of attitudes about

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'I -76Table 5 Breakdovm of construct stance by descriptive statements Construct: Attitudes about education (data source = interview) Descriptive Statements Individual Respondents 1 2 3 4 5 6 Sunmary* Group I (participants) 1 yes ves no yes yes yes positive 2 no yes no ves yes yes positive o J IIU no no yes yes no least positive 4 yes no yes yes yes no positive 5 yes no yes yes no yes positive 6 yes no ves ves yes ves positive 7 yes no yes yes yes yes positive o o yes yes yes yes yes no positive Q yes no yes yes yes no positive yes no ves yes yes ves positive yes yes ves yes yes yes positive 1 9 1^ no yes ves ves ves yes positive yes no no no no no least positive 1 A If yes no ves ves ves yes positive 1 c yes no ves ves yes ves positive Group yes 12 5 11 14 13 10 13 positive C I imiTt o T* 1 o c DUIUlUdL J-Cb no 3 10 4 1 2 5 2 least positive uroup 11 ^non -participants) 16 yes yes yes yes yes ves positive 17 no no ves yes ves yes positive 18 yes no no no no ves least positive 1 Q l7 yes yes yes yes yes yes positive 20 yes yes yes yes yes yes positive 21 yes no yes yes yes yes pUb X L X Vc 22 yes yes ve yes no ve <5 yea no ^ i ^ "i VP 23 yes no yes no no yes less positive 24 yes yes yes yes yes yes positive 25 yes yes yes no no yes positive 26 yes yes yes yes yes yes positive 27 no no yes yes yes no less positive 28 no no yes yes yes yes positive 29 no no no no no no least positive 30 yes no yes yes yes yes positive Group yes 11 7 13 11 10 13 11 positive Summaries no 4 8 2 4 5 2 2 less positive 2 least positive *Decision rule: Individuals who could be described by at least four of the descriptive statements were placed in the highest of three levels of attitude. Individuals who could be described by two or less of the statements were placed in the lowest level.

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-77education and indicates the appropriateness of the descriptive statements by individual and group. Attitude levels in both Group I (participators) and Group II (non-participators) ranged from "positive" to "least positive," with the median score for both groups being three, "positive." Comparison of data from Interview schedule to data from Faculty Questionnaire . The same decision rule that was used to categorize faculty into the three levels of attitude about education based on interview data was used to categorize faculty based on questionnaire data. Again, a full range of attitude levels was found for each group; however, both groups reported themselves as more positive on the written questionnaire than they did orally. The median level for both groups on the questionnaire data was three, "positive." Figure 4 plots the level of attitude about education by the frequency of individuals in each level by group and by source of data. Extent to which findings support COR Model . Cross (1981), in her COR Model, asserts that adults who have positive attitudes about education are more likely to participate voluntarily in structured learning activities. Thus, one would expect that the faculty at the University of Florida who have positive attitudes about professional development activities would be more likely to participate voluntarily in structured learning activities on computer technology. The null hypothesis relative to attitudes about education which was tested by this study was as follows: Hypothesis B-1. There is no difference between attitudes about education and participation in professional development activities on computer technology by faculty at the University of Florida.

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-78GROUP LEVEL I I LEAST POS 73 ITIVE LESS POS I T I VE POS I T I VE LEAST POSITIVE LESS POS I T I VE POS I T I VE FREQUENCY OF INDIVIDUALS DATA FROM INTERVIEW DATA FROM QUESTIONNAIRE Figure 4, Level of attitudes about education by frequency.

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-79To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was no significant difference at the p =< .10 level between Group I and Group II on the attitudes data gathered by use of the interview schedule or the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis. A second null hypothesis relative to attitudes about education which was tested by this study follows: Hypothesis B-2. There is no difference among attitudes about education and the level of participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, the faculty members' attitudes about education which were determined by interview and written questionnaire were compared to the levels of participation. There was a significant difference (p = 0.0272) between levels of participation on the attitudes about education data gathered by use of the interview schedule. (The Spearman correlation was 0.246.) No significant difference was found on the written questionnaire. The data gathered by the interview and questionnaire were inconsistant; therefore, the researcher failed to reject the null hypothesis. The fact that the researcher found no significant difference between Group I and Group II on attitudes about education nor a relationship among attitudes about education and levels of participation neither adds support for or against the applicability of the COR Model. Several constructs are included in Cross's model which she said lead to participation. The minimum criterion for acceptance of the model—a positive attitude toward education by

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-80particlpants — was met. (See Appendix M for the Summary of Statistcal Data by Hypothesis and Data Source.) Construct; goals and expectations Treatment of data from COR Model Interview Schedule . Point C in Cross's model (importance of goals and expectation that participation will meet goals) actually included two different but interdependent constructs — goals and expectancy. Faculty member responses to questions concerning goals were compared to the descriptive statements about goals and each individual was rated positive or negative. The individual was then rated positive or negative on expectancy, again by comparison to descriptive statements. In order to receive a positive rating for the combined construct, the individual had to receive positive ratings for each of the categories. Table 6 lists the decision rule used to categorize faculty as positive or negative for goals and expectations. The table also indicates the appropriateness of the descriptive statements by individual and group. The median position on the combined construct for Group I (participants) was positive and the median position for Group II (nonparticipants) was negative. Comparison of data from interview schedule to data from Faculty Questionnaire. The same decision rule that was used to categorize faculty on goals and expectations based on interview data was used to categorize faculty based on questionnaire data. Again, the median position for Group I was "positive" and the median position for Group II was negative. Figure 5 plots goals and expectations by the frequency of individuals in each position by group and by source of data.

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-81Table 6 Breakdown of construct stance by descriptive statements Construct: Goals and expectations (data source = interview) Descriptive Statements Goals Expectations Combined Respondents 1 4 Overall 2 3 Overall Construe Group I (participants) 1 ves yes positive yes yes positive positive 2 no no negative yes yes positive negative 3 yes yes positive no yes negative negative 4 yes no ne»ff at i ve yea yea fin Q 1 1" 1 VP 5 yes yes positive yes yes positive positive 6 yes yes positive yes yes positive positive 7 yes yes positive yes yes positive positive 8 yes yes positive no yes negative negative 9 yes no negative yes yes positive negative 10 yes yes positive no yes negative negative 11 yes yes positive yes yes positive positive 12 yes yes positive yes yes positive positive 13 yes yes positive yes yes positive positive 14 yes yes positive yes yes positive positive 15 yes yes positive yes yes positive positive Group yes 14 12 12 12 15 12 9 Summary no 1 3 3 3 0 3 6 Group II (particip. ants) 16 yes yes positive yes yes positive positive 17 yes yes positive no yes negative negative 18 yes yes positive no yes negative negative 19 no no negative no yes negative negative 20 yes yes positive no y-es negative negative 21 no no negative no yes negative negative 22 yes no negative no yes negative negative 23 no no negative no yes negative negative 24 yes yes positive no yes negative negative 25 no no negative no yes negative negative 26 yes yes positive no yes negative negative 27 no no negative no yes negative negative 28 yes yes positive no yes negative negative 29 yes no negative no yes negative negative 30 yes no negative no yes negative negative Group yes 10 7 7 1 15 1 Summary no 5 8 8 14 0 14 *Decision rule: Both statements "l" and "4" described the individual if the person was classified as fulfilling the requirements for a positive goal orientation. Both statements "2" and "3" described the individual if the person was classified as having positive expectations. In order to receive a positive rating for the combined construct (goals and expectations), the individual had to receive positive ratings for each of the categories.

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Figure 5. Level of goals and expectations by frequency.

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-83Extent to which findings support COR Model . Cross (1981) asserts that motivation to participate in educational activities is strong only if the individual believes a goal important to him/her is likely to be achieved through participation in the activity. Thus, one would expect that the faculty at the University of Florida who have goals which are related to computer technology and who expect that participation in the learning activity on computers will help them achieve their goals would be more likely to participate voluntarily in structured learning activities on computer technology. One null hypothesis relative to goals and expectations which was tested by this study was as follows: Hypothesis C-1. There is no difference between goals and expectations and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was a significant difference (p = 0.0019) between Group I and Group II on the goals and expectations data gathered by use of the interview schedule and there also was a significant difference (p = 0.0002) between groups on the data from the Faculty Questionnaire. Therefore, the researcher rejected the null hypothesis. A second null hypothesis relative to goals and expectations which was tested by this study follows: Hypothesis C-2. There is no difference among goals and expectations and the level of participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, the level of goals and expectations which was determined by interview and written questionnaire was compared to the

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level of participation. There was no significant difference at the p =< 0.10 level between levels of participation on the goals and expectations data gathered by use of the interview schedule or written questionnaire. Therefore, the researcher failed to reject the null hypothesis. The rejection of the null hypothesis C-1 relating goals and expectations to participation/non-participation does lend support to Cross's COR Model. Faculty who participated in professional development activities related to computer technology did have a significantly more positive stance on the construct than faculty who did not participate. The Spearman correlation between goal-expectancy and group was -0.566 using interview data and the correlation was even higher using questionnaire data. That there was no significant difference among goals and expectations and levels of participation neither adds support for or against the COR Model. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) Construct: life transitions Treatment of data from COR Model Interview Schedule . Life transitions are gradual or dramatic periods of change which require adjustments to new positions in life. Operationally, a faculty member was considered in transition if he or she had recently experienced a "marker event" from Cross's descriptions of life cycle phases. During the interviews, the faculty members were asked questions about life transitions they had experienced in the previous 18 months. Each faculty member's responses to the interview questions were used to determine whether the descriptive statement, which was approved by

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-85Cross as characteristic of faculty who had experienced a life transition, could be appropriately used to describe the faculty member. Table 7 lists the decision rule used to categorize faculty into three levels of life transitions and indicates the level of each person included in the study. Life transition levels in both Group I (participants) and Group II (non-participants) ranged from three to one with the median score for both groups being level two. Comparison of data from interview schedule to data from Faculty Questionnaire. Data from the Likert-style questionnaire divided the faculty into two categories — those who had experienced at least one life transition in the past 18 months (level two) and those who had not. The median response by both groups was level one, "no life transitions." Figure 6 plots the level of life transitions by the frequency of individuals in each level by group and by source of data. Extent to which findings support COR Model . Cross (1981), in her COR Model, asserts that adults who have experienced life transitions are more likely to participate voluntarily in structured learning activities. Thus, one would expect that the faculty at the University of Florida who have experienced life transitions would be more likely to participate voluntarily in structured learning activities on computer technology. One null hypothesis relative to life transitions which was tested by this study follows: Hypothesis D-1. There is no difference between life transitions and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center

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-86Table 7 Construct: Life transitions (data source = interview) Group I Level of LifeGroup II Level of Life(participants) Changing Events (non-participants) Changing Events* 1 2 16 2 2 2 17 1 3 2 18 2 4 3 19 1 5 3 20 2 6 3 21 2 7 2 22 1 8 3 23 3 9 1 24 2 10 3 25 2 11 2 26 2 12 3 27 1 13 2 28 2 14 1 29 2 15 1 30 3 Group Summary 6 Level 3 6 Level 2 3 Level 1 Group Summary 2 Level 3 9 Level 2 4 Level 1 *Decision rule: Individuals who had experienced at least six events in their lives which would fit into Cross's list of events which bring about life transitions were placed in Level 3. Individuals who had not experienced any of the life-changing events constituted Level 1.

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-87GROUP LEVEL LEVEL 1 LEVEL 2 LEVEL 3 1 1 LEVEL 1 LEVEL 2 LEVEL 3 7 7Z I I I I — I I t I — I — I — I — i I I I — ; 2 4 6 8 10 12 14 16 FREQUENCY OF INDIVIDUALS DATA FROM INTERVIEW DATA FROM QUESTIONNAIRE 22 Figure 6. Level of life transitions by frequency.

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-88(Group I) were compared to faculty who had not (Group II). There was no significant difference at the p =< O.IO level between Group I and Group II on the life transitions data gathered by use of the interview schedule or the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis. A second null hypothesis relative to life transitions which was tested by this study follows: Hypothesis D-2. There is no difference among life transitions and the levels of participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, the level of life transitions was compared to the level of participation. There was no significant difference at the p =< 0.10 level between levels of participation on the life transitions data gathered by use of the interview schedule or the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis. There was, as reported, no significant difference between groups or among levels of participation on life transitions — whether using data gathered by interview or written questionnaire; however, opposite findings were determined by the two methods. Data gathered by Interview showed that 77% of all respondents had experienced at least one change in life-cycle phase during the 18 months prior to the study. When asked on the written questionnaire if he/she had "experienced a dramatic change in [his/her] life" during the past 18 months, 73% of all respondents said they had not. The failure to reject both null hypotheses related to life transitions neither adds support for or against the applicability of the COR Model. Life transitions. Cross said, serve as additional

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-89forces for learning and the individual influenced toward participation by a life transition would have had a positive motivation toward participation in learning activities even before the transition. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) Construct; opportunities and barriers Treatment of data from COR Model Interview Schedule. Point E in Cross's model (opportunities and barriers) actually included two different but interdependent constructs — opportunities and barriers. Faculty member responses to questions concerning opportunities and barriers were compared to the descriptive statements about each area and each individual was rated "positive" or "negative" for each statement. In order to receive a positive rating for the combined construct, the individual had to receive positive ratings for each of the categories. Table 8 lists the decision rule used to categorize faculty as positive or negative for the combined construct. The table also indicates the appropriateness of the descriptive statements by individual and group. The median position on the combined construct for Group I (participants) was positive and the median position for Group II (non-participants) was negative. Comparison of data from interview schedule to data from Faculty Questionnaire. The same decision rule that was used to categorize faculty on opportunities and barriers based on interview data was used to categorize faculty based on questionnaire data. Again, the median position for Group I was "positive" and the median position for Group II was "negative." Figure 7 plots opportunities and barriers by the frequency of individuals in each position by group and by source of data .

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-90Table 8 Breakdown of construct stance by descriptive statements Construct; Opportunities and barriers (data source = interview) Descriptive C t" O ^ Am i^r\ maiviaua± 1 2 J Summary* Group I (participants) 1 yes yes yes posx Live 2 yes yes yes positive 3 yes yes yes positive 4 yes yes yes positive 5 yes yes yes positive 6 yes yes yes positive 7 yes yes yes positive 8 yes yes yes positive 9 yes yes yes positive 10 yes yes yes positive 11 yes yes yes positive 12 yes yes yes positive 13 yes yes yes positive 14 yes yes yes positive 15 yes yes yes positive Group yes 15 15 15 15 positive Summaries no 0 0 0 0 negative negative negative negative negative negative negative negative negative negative negative negative negative negative negative negative 0 positive 15 negative Group II (non-participants) 16 yes yes no yes yes no yes no no yes yes no yes no no yes yes no 17 18 19 20 21 22 no 23 24 25 26 27 no 28 29 30 no no yes yes no yes no no yes no no yes yes no no no yes yes no yes yes no no no no Group yes 12 8 0 Summaries no 3 7 15 *Declslon rule: All three statements had to describe the individual if the person was classified with a positive orientation toward opportunities and barriers.

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Figure 7. Level of opportunities and barriers by frequency.

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-92Extent to which findings support COR Model . Cross (1981) claimed that adults with strong motivation to participate in learning activities were likely to seek out educational opportunities and overcome modest barriers. Conversely, modest barriers were likely to preclude the participation of weakly motivated adults. Thus, one would expect that the faculty at the University of Florida who have participated in learning activities on computer technology (Group I) to be aware of opportunities and minimize barriers, while the nonparticipants (Group II) would be expected to be unaware of opportunities and emphasize barriers. One null hypothesis relative to opportunities and barriers which was tested by this study follows: Hypothesis E-1. There is no difference between opportunities and barriers and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was a significant differece (p = 0.0001) between Group I and Group II on the opportunities and barriers data gathered by use of the interview schedule and there also was a significant difference (p = 0.0034) between groups on the data from the Faculty Questionnaire. Therefore, the researcher rejected the null hypothesis. A second null hypothesis relative to opportunities and barriers which was tested by this study follows: Hypothesis E-2. There is no difference among opportunities and barriers and the levels of participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, the level of opportunities and barriers which was determined by interview and written questionnaire was compared to

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-93the level of participation. There was no difference between levels of participation on the opportunities and barriers data gathered by use of the interview schedule and there was no significant difference at the p =< 0.10 level between levels on the data from the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis. The rejection of the null hypothesis E-1 relating to opportunities and barriers does lend support to Cross's COR Model. Faculty who participated in professional development activities related to computer technology did have a significantly more positive stance on the construct than faculty who did not participate. The Spearman correlation between opportunities and barriers and groups was -1.00 using interview data and -0.535 using written questionnaire data. The lack, of a positive relationship between opportunities and barriers and levels of participation does not add support for or against the COR Model. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) Construct: information Treatment of data from COR Model Interview Schedule. Information is an awareness of the individual's opportunities for educational activities. Operationally, this translates into the faculty member's awareness of structured professional development activities on computer technology. During the interviews, the faculty members were asked questions about opportunities which were available through various agencies on the University of Florida campus. Their responses were compared to information which has been disseminated to the faculty by the sponsoring organization or department. Each faculty

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-94member's responses to the interview questions were used to determine whether the descriptive statements, which were approved by Cross as characteristic of faculty with accurate information, could be appropriately used to describe the faculty member. A decision was then made concerning the individual's overall information. Table 9 lists the decision rule used to categorize faculty into three levels of awareness. Group I (participants) all were categorized in the "highest awareness" level. Only the bottom two levels were found in Group II (non-participants). The median score for Group II was level two, "less aware." Comparison of data from interview schedule to data from Faculty Questionnaire. The data gathered on the Faculty Questionnaire allowed for only two levels of information — "aware" and "unaware." The distribution of scores for Groups I and II on the written questionnaire were the same with "aware" as the median score for each. Figure 8 plots the level of information by the frequency of individuals in each level by group and by source of data. Extent to which findings support COR Model . Cross (1981) emphasized the importance of accurate information for providing the link, between motivated learners and appropriate opportunities. Individual who were motivated to participate in learning activities would notice and remember information about opportunities that were available to them. Thus, faculty at the University of Florida who can accurately describe learning activities on computer technology which are available to them would be more likely to participate voluntarily in structured learning activities on computer technology. One null hypothesis relative to information which was tested by this study follows:

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-95Table 9 Breakdovm of construct stance by descriptive statements Construct; Information (data source = interview) Descriptive Statements 1 2 Individual Summary* Group I (participants) 1 yes yes highest awareness 2 yes yes highest awareness 3 yes yes highest awareness 4 yes yes highest awareness 5 yes yes highest awareness 6 yes yes highest awareness 7 yes yes highest awareness 8 yes yes highest awareness 9 yes yes highest awareness 10 yes yes highest awareness 11 yes y^s highest awareness 12 yes yes highest awareness 13 yes yes highest awareness 14 yes yes highest awareness 15 yes yes highest awareness P yes 15 15 15 highest awareness Summary Group II (non-participants) 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Group Summaries yes yes yes yes yes yes no yes yes yes yes no yes yes no yes 12 no 3 no no no no no no no no no no no no no no no 0 15 less awareness less awareness less awareness less awareness less awareness less awareness unaware less awareness less awareness less awareness less awareness unaware less awareness less awareness unaware 12 less awareness 3 unaware Decision rule: The highest level indicates the individual was aware of sponsoring organizations of professional development opportunities on computer technology and could describe more than one activity. The lowest category indicates the individual could not describe any opportunities nor any sponsoring organizations.

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-96GROUP LEVEL UNAWARE AWARE H I GHEST AWARENESS UNAWARE AWARE H I GHEST AWARENESS FREQUENCY OF INDIVIDUALS DATA FROM INTERVIEW DATA FROM QUESTIONNAIRE Figure 8. Level of information by frequency.

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-97Hypothesis F-1. There is no difference between information and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was no significant difference at the p =< 0.10 level between Group I and Group II on the information data gathered by use of the Faculty Questionnaire; however, there was a significant difference (p = 0.0001) between groups on the data gathered by use of the interview schedule. (The questionnaire asked respondents if they were aware of learning activities on computer technology and the interview required respondents to name and describe the activities.) The researcher failed to reject the null hypothesis because of conflicting data. A second null hypothesis relative to information which was tested by this study follows: Hypothesis F-2. There is no difference among information and the levels of participation in professional development activities on computer technology for faculty at the University of Florida. To test the hypothesis, the level of information which was determined by interview and written questionnaire was compared to the level of participation. There was no significant difference between levels of participation on data gathered by interview, even though there was a significant difference between levels of participation on the data gathered by questionnaire (p = 0.0272). Therefore, the researcher failed to reject the null hypothesis because of conflicting data .

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-98The failure to reject the null hypotheses F-1 and F-2 lends support neither for or against the COR Model. (See Appendix M for the Sunnnary of Statistical Data by Hypothesis and Data Source .) Construct; participation Treatment of data from COR Model Interview Schedule . Participation is the act of taking part in an organized learning activity. Operationally, this translates into the faculty member's voluntary participation in professional development activities on computer technology. The individual's evaluation of his or her participation experience is an indicator of the level of participation one could expect. During the interviews, the faculty members were asked questions about past participation in professional development activities in general and specifically about participation in activities on computer technology. Each faculty member's responses to the interview questions were used to determine whether the descriptive statements, which were approved by Cross as characteristic of faculty who are participants, could be appropriately used to describe the faculty member. A decision was then made concerning the individual's overall participation experience. Table 10 lists the decision rule used to categorize faculty into five levels of participation

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-99Table 10 Breakdown of construct stance by descriptive statements Construct: Participation (data source = interview) Descriptive Statements Individual 12 3 4 Summary* Group I (participants) 1 yes yes yes 2 yes yes yes 3 yes yes yes 4 yes yes yes 5 yes yes yes 6 yes yes yes 7 yes yes yes 8 yes yes yes 9 yes yes yes 10 yes yes yes 11 yes yes yes 12 yes yes yes 13 yes yes no 14 yes yes yes 15 yes yes yes Group yes 15 15 14 Summaries no 0 0 1 yes four yes four no four yes four yes four yes four yes four yes four yes four yes four yes four yes four yes three yes four yes four 14 14 four 1 1 three p II (nonparticipants) 16 yes no yes no two 17 yes no yes yes three 18 yes no no no one 19 yes no yes no two 20 yes no yes no two 21 yes no yes no two 22 yes yes yes no three 23 yes no no no one 24 yes no yes no two 25 yes no no no one 26 yes yes yes no three 27 yes no yes no two 28 yes yes yes yes four 29 yes no no no one 30 yes yes yes no three Group yes 15 4 11 2 1 four 6 two Summaries no 0 11 4 13 4 three 4 one *Declsion rule: Individuals were placed into one of five levels to indicate the individual's attitude toward participation. Each level (4-0) corresponds to the number of descriptive statements that described the Individual. The highest level Indicated that all four statements were true for the individual while the lowest level indicates none of the statements was true.

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-100experlence ("four" through "zero") and indicates the appropriateness of the descriptive statements by individual and group. The participation experience of Group I (participants) included only the two highest levels, with the median score being the highest level, "level four." Participation experience for Group II (nonparticipants) ranged from "level one" through "level four" with the median score being "level two." Comparison of data from interview schedule to data from Faculty Questionnaire. The same decision rule that was used to categorize faculty into the five levels of participation experience based on interview data was used to categorize faculty based on questionnaire data. The range of levels for Group I was "level four" through "level one"; Group II had all five levels represented. The median scores for both groups remained the same as determined by interview — "levels four" and "two" for Groups I and II, respectively. Figure 9 plots the level of participation experience versus the frequency of individuals in each level by group and by source of data. Extent to which findings support COR Model . Cross (1981), in her COR Model, asserts that adults who voluntarily participate in structured learning activities and evaluate their participation positively have a positive self-evaluation and attitude about education, thus, beginning the cycle again which results in participation. As a result, one would expect that the faculty at the University of Florida who have had positive experience in professional development activities related to computer activities would be more likely to participate voluntarily in additional structured learning

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-101GROUP LEVEL LEVEL 0 LEVEL t LEVEL 2 LEVEL 3 LEVEL 4 I I LEVEL 0 LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 z < — ' — I — I — I — I — I — I — I — I — I — 1 — i2 4 6 a 10 12 14 t 6 FREQUENCY OF INDIVIDUALS iZZl DATA FROM INTERVIEW DATA FROM QUESTIONNAIRE Figure 9. Level of participation experience by frequency.

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-102activities on computer technology. One null hypothesis relative to participation which was tested by this study follows: Hypothesis G-1. There is no difference between participation experience and participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, faculty members who participated in a minimum of four sessions on computer technology at the Faculty Support Center (Group I) were compared to faculty who had not (Group II). There was a significant difference (p = 0.0004) between Group I and Group II on the participation experience data gathered by use of the interview schedule. There was also a significant difference (p = 0.0001) between Group I and II on data gathered by use of the Faculty Questionnaire. Therefore, the researcher rejected the null hypothesis. A second null hypothesis relative to participation which was tested by this study follows: Hypothesis G-2. There is no difference among participation experience and the levels of participation in professional development activities on computer technology by faculty at the University of Florida. To test the hypothesis, the level of participation experience was compared to the level of participation. There was a significant difference (p = 0.0821) between levels of participation on the participation experience data gathered by use of the interview schedule. There was not, however, a significant difference between levels of participation on data gathered by use of the Faculty Questionnaire. Therefore, the researcher failed to reject the null hypothesis because of conflicting data.

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-103The rejection of the null hypothesis G-1 relating participation experience to participation/non-participation does lend support to Cross's COR Model. Faculty who participated in professional development activities related to computer technology did have a significantly more positive stance on past participation experiences. The Spearman correlation between participation and group was -0.751 on interview data and -0.586 on data from the written questionnaires. The failure to reject null hypothesis G-2 neither adds support for or against the COR Model. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source.) Summary of Statistical Data A summary of the statistical data is presented in table format in Appendix M in order to facilitate the comparison of data between data sources, constructs, and hypotheses. The researcher rejected three null hypotheses: C-1 goal-expectancy by group, E-1 opportunities and barriers by group, and G-1 participation by group. Conflicting tests of significant differences and, thus, failure to reject the null hypotheses were found for five null hypotheses. Both data sources for the remaining six hypotheses failed to determine a significant difference between groups and/or levels of participation. (See Appendix M for the Summary of Statistical Data by Hypothesis and Data Source . )

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CHAPTER V SUMMARY, CONCLUSIONS, IMPLICATIONS, LIMITATIONS OF THE STUDY, AND SUGGESTIONS FOR FURTHER RESEARCH In this final chapter an overview of the study is given. The chapter is divided into six sections which follow in this order: summary and discussion of the study, conclusions drawn from the study, theoretical and practical implications of the study, limitations of the study, suggestions for further research, and a final observation. Summary and Discussion The research reported was an investigation of the applicability of Cross's Chain-of-Response Model for explaining faculty participation in structured professional development activities. The purpose of the study was to contribute to the accumulation of knowledge in adult education — particularly to the educator's understanding of the motivations of adult learners. An assumption of the study was that the individual has control over his or her destiny, and that his or her participation in learning activities is voluntary. The study was completed in three phases. During the first phase, the COR Model was adapted to describe faculty who participate in structured professional development activities by defining the model's constructs both constitutively and operationally. The constitutive -104-

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-105and operational definitions were approved by Cross, as were the descriptive statements for each construct. The second phase included the development of instruments which could be used to determine the utility of the adapted model for distinguishing between participating and non-participating faculty. The instruments developed were the COR Model Interview Schedule with guidelines and the Faculty Questionnaire. The descriptive statements of the constructs which were approved by Cross were used as the basis for developing the instruments. During the third phase, the interview schedule and questionnaire were administered to two groups of University of Florida faculty — participants and non-participants in structured professional development activities on computer technology. The data gathered from the faculty were analyzed and compared to the COR Model. The statistics used to analyze the data were median scores, percentile rank. Spearman rank correlations, and the chi-square test of significance . Instrumentation Evaluation of design . While the interview schedule used to gather data was adequate to address the questions included in this study, several ways to improve the schedule were revealed. Two major format changes would be beneficial to the recording and coding the data. (See Appendix K for an example of the suggested revisions to the interview schedule.) First, the data categories established should be listed below each question along with space for responses which do not fit in the listed categories. This change would enable

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-106the data to be recorded more rapidly and the categories would serve as a reminder of the type of response sought. If the question on the interview schedule does not elicit the kind of response which was expected, the interviewer could reword the question or probe deeper. Appropriate responses which were not covered by the data categories would be written in the blank spaces. A second format change, leaving space on the left or right margin of the interview schedule for subsequent coding of data, would improve the efficiency of coding data. Some questions included in the revised schedule did not generally elicit the kind of response intended. The questions with suggested changes follow: Il.l.b. Describe your work assignment (responsibilities) for a typical academic year in that position . appointment: 9 month 12 month yrs. at UF [Add after space for description " 7o teaching % research % administration % service 7o other (specify) "] 11.16. Under what circumstances are you willing to participate in ed. activities related to your teaching or research? (e.g. own time, own expense, reward) [Change to "Under what circumstances are you NOT willing to participate in ed. activities related to your teaching or research? (e.g. own time, own expense, reward)"] 11.17. b. Please divide these cards into two stacks: motivators for you to participate and non-raotivators. Rank the motivators in order of importance. [Change to "Listed on these cards are needs which are believed by some educators to be motivators to participate in educational activities. Please divide the cards into two stacks: one stack for those that would motivate you to participate in structured educational activities and another stack for those that would not. It is possible that all cards would belong in one stack. . . . Now, please rank the motivators in order of importance to you."] Questions II.lA.b. and IV.25.C. and d. received such widely diversified answers (e.g., four hours/week, three weeks/year, two conferences per year) that they could not be used to directly compare

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-107time spent in educational activities. The questions were useful-, however, because the discussion about the amount of time spent gave the interviewer insight into what importance was placed on the activities . The Likert-style "Faculty Questionnaire" which was used as a check against the interview interpretation would have been easier to administer if the directions were different. Instead of directing the respondent to indicate when a question was not applicable by writing "N/A" in the blank, "not applicable" should have been included for each question as the last choice: "f. not applicable." Consistency of instruments . Categorization of individuals for each construct was consistent between instruments except for two constructs. The responses to the written questionnaire on selfevaluation were generally one category lower than responses to the oral portion of the interview questions on the same construct. The responses to questions on life transitions were generally positive during oral interview and negative on the written questionnaire. (See Table 11 for a comparison of construct stance generated by the COR Model Interview Schedule with the stance generated by the Faculty Questionnaire . ) Significant Findings of the Study The course of the research was guided by two questions: 1. Does the operationally defined model provide adequate information to explain participation or non-participation?

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-108Table 11. Comparison of construct stance from Interview Schedule with Faculty Questionnaire Self-Evaluation Attitude about F.ducntlnn Most Leaa Least Positive Positive Posit I vo Most Pos 1 t Ive Pnq I f I vc I.nnpt Pot 1 1 ! vo Goals and Expectations Pos I t I ve Npgat Ivo Group I I Q I 1 <} 2 I Q I q 3 1 Q q 4 I q I q 5 I q I q 6 1 Q I q 7 q I q 8 Q I q 9 1 q I q 10 Q I q 11 { Q I q 12 Q I q 13 I q 14 I Q I q 15 I q t q Group II 16 I q I q 17 Q I q 18 0 (1 19 t q 20 q I q 21 q I q 22 'J I q 23 I q I q 24 q I q 25 Q I q 26 I q I q 27 I q q I 28 I q t q 29 I q 30 I q I q Legend : I Interview Schedule ; q ' F.Tritl ty QtiPflt lonnn 1 rn . *0n the Interview Schedule, Level 1 ' "no transitions," Lovol 2 "<6,' I.cvrl 1 Faculty Questionnaire, Level 1 "no transitions," Lnvol 2 ^ "> n t rans ) 1 1 onr: . " "> 5"; on the **0n the Interview Schedule, "Highest Awareness" reqiilrrd respondrnt to des'-rlhr professional development activities, "Leas Awnr«!iipss " IndlrateH the respondent rould Idrnrify spnnsorliiR agencies only, "Least Awareness" Indicated no awareni>ns of artlvltles or sponsorliip agenrlpq. The Faculty Qries t lonna I re did not ask the respondent to di-'Jrrlbe profefistonal drvnlopment activities, thus the "Highest" and "I, ns-; Awarmess" reoponch'iil nrr Rronped (irnrlmr.

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-109Table 11. extended Opportunl ties Life Transitions* and Barriers Information** Participation Level Level Level Highest Less Least Level 3 2 1 Positive Negat Ive Awareness Awareness Awareness 3 2 I Q I q I q IQ I Q I q I q IQ I Q q 0 q I I Q I q I q iq I Q I Q I q q I I Q I q I q iq Q 1 I q 1 q IQ I Q 1 q I q IQ I Q q I 0 iq I Q t q I q iq I Q I q I q I q I Q I q I q iq Q I q I q I q I q I q I q . I q I q I q I q iq Q I q q iq I q I q q I q Q I I q q q I I Q I q q iq I q I q q iq I Q I q q iq I q I q I q iq t Q I q q iq I q I q q I q I q I q q q I Q I I q q iq I q I q I q q I I q I q q iq q I q q iq I q q q t I q

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-1102. Does the operationally defined model provide adequate information to explain the level of participation for those who participate? A series of hypotheses for each construct were generated to determine if there was a difference between groups on each construct (question "1") and if there was a difference among levels of participation for each construct (question "2"). A summary of the data for each hypothesis is displayed in Appendix M. Participants versus non-participants . Statistical analysis of the data obtained from faculty members who had participated in at least four sessions of structured activities on computer technology (Group I) and faculty members who had not (Group II) resulted in the following significant findings: 1. Faculty members who were classified as participants believed goals which were important to them were likely to be achieved through participation in educational activities related to computer technology. Faculty members classified as non-participants did not have this expectation. 2. Faculty members who were classified as participants were aware of opportunities to participate in structured activities on computer technology which they believed would be of benefit to them, and they believed they could overcome any situations which they perceived as barriers to their participation. Faculty members who were classified as non-participants were not aware of opportunities which they believed would benefit them and/or they did not believe they could overcome situations they perceived as barriers to their participation.

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-1113. Faculty members who were classified as participants could describe several existing opportunities for professional development on computer technology. Faculty members who were classified as nonparticipants were not aware of any opportunities or could only minimally identify opportunities which were available. 4. Faculty members who were classified as participants had participated in professional development activities (including both computer and non-computer related activities) and evaluated their experiences in both computer related and non-computer related activities positively. Faculty members who were classified as nonparticipants had participated in professional development activities other than ones on computer technology and the majority had evaluated their experiences positively. Levels of participation . Statistical analysis of the data obtained from faculty members who had been classified into levels of participation (1 = least participation, participation in a minimum of four sessions on computer technology with no application, through 3 = greatest participation, participation in more than four sessions and application of at least one) resulted in no significant findings. Data were found to support the rejection of the null hypotheses for the constructs self -evaluation, attitude about education, information, and participation using one of the data collecting methods; however, the rejection was not supported by the second method that was used to evaluate the constructs. Even so, findings concerning three of the constructs are given here because of their high correlations. 1. There was a negative correlation between self-evaluation and level of participation.

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-1122. There was a positive correlation between attitude about education and level of participation. 3. There was a positive correlation between information and level of participation. The reader is reminded that these findings were deemed as significant by only one of the two methods used to gather the data. Other Findings of the Study In the overall model, there appeared to be a positive relationship between the number of constructs which were positive descriptors of the respondent and the level of participation of the respondent. See Figure 10 and Appendices N and 0. Conclusions The research reported was an effort to determine whether it was possible to describe university faculty members who participate in organized professional development activities using Cross's Chain-ofResponse Model. The results of the study provided support for the following conclusions: 1. Motivation of faculty members to participate in learning activities related to computer technology depended largely on point C, goals and expectations. Faculty members who were motivated to participate were likely to seek out educational opportunities and overcome modest barriers. Conversely, modest barriers were likely to preclude the participation of weakly motivated faculty members. Motivated faculty members remembered more detailed information about

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-1137 (Q) 1 1 (5) d) (i) 6,7,12 6 1,8,10 (DO <2) 2,4,14 5 (6) © 1 5,15 NUMBER OF DESCRIPTORS i, m 2 8 1 o (5) 3 (LO) (9) 9 13 m FTT 2 6,30 1 3 LU 1 7 2 2 0,21 ,23 2 4,25 LEGEND 0 = # of FSC 1 sessions 18,19 2 2,29 Q= # of sessions with other sponsors # = respondent q 2 7 1 i 1 1 1 0 12 LEVEL OF PARTICIPATION Figure 10. Relationship of the number of constructs which were positive descriptors with the level of participation.

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-114professional development opportunities on computer technology which were available to them. Thus, participants differed from nonparticipants primarily on their stance on three constructs which lead up to participation: goals and expectations, opportunities and barriers, and information. 2. A high level of participation in professional development activities is an indication that the majority of the constructs in the COR Model are positive descriptors of the faculty member. Conversely, low or non-participation in such activities indicates that few if any of the constructs are positive descriptors of the individual. Implications Theoretical Implications The adapted constructs of Cross's COR Model did describe faculty at the University of Florida who participated in professional development activities related to computer technology. Thus, this study lends support to her model. However, this study did not distinguish between participants and non-participants on three of the constructs: self-evaluation, attitudes about education, and life transitions. Two of the constructs, self-evaluation and attitudes about education, seemed important to the model in order to understand the motivation for participation even though this study indicated no significant difference between participators and non-participators on the two constructs. Perhaps the composition of this subpopulation of adults, through prior selectivity into the ranks of university faculty, is predominantly composed of Individuals who are positive in

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-115their self-evaluation and who view education as a way of life. Since the results reported here provide empirical evidence that a portion of Cross's model of motivation is valid, additional evidence on individuals who apparently do not have a positive self-evaluation or who view education negatively would provide empirical evidence for more fully testing and developing the model. The construct life transitions presented several problems to the researcher. During the interviews almost all respondents (both participants and non-participants) identified some recent lifechanging event which they had experienced. However, on the written questionnaire the respondents indicated they had not experienced a dramatic change in their lives. The reason for this discrepency within the data is not understood by the researcher. No matter which data source is used, this construct still did not distinguish between participant and non-participant. Assuming that the interview data were more accurate, perhaps the lack of discrimination was due to the limited nature of learning activities (computer technology) addressed in this study. A broader study which examines learner participation on a variety of topics may find empirical data to support the retention in the COR Model of the construct life transitions . Strong empirical evidence was found to support the construct goals and expectations as a motivator toward participation. If one's goals and expectations can be changed, then perhaps whether one would participate or not would change also. Virtually the same information was available and the same opportunities and barriers were found for

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-116both participants and non-participants. The way the individual responded to these factors seemed dependent on construct C, importance of goals and expectation that participation will meet goals. Practical Implications Very little discrepency between instruments was found on conclusions drawn about an individual's construct stance, except for the construct life transitions. The implication then is that the shorter, less involved instrument could be used to quickly identify a faculty member's stance on the constructs of the COR Model. Administrators or others responsible for planning professional development activities for their faculty should be aware of the goals of their personnel. The choice and design of learning activities offered to the faculty should be such that faculty would expect to be better able to reach his or her goal because of participation in the activity. Care should be taken during the dissemination of information concerning professional development opportunities to sliow the relevance of the activity to the achievement of goals. Administrators who are responsible for faculty renewal may be able to influence goal setting in some instances. They may be more successful at influencing goal setting if they are cognizant of the needs of the .faculty member in his or her academic class. Perhaps sessions on career planning, written professional development plans, or other methods which cause faculty to consider their goals could be implemented . While a broad range of opportunities and accurate information about the opportunities are important to participation, the

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-117inforaation and opportunities available to both participants and nonparticipants in this study were virtually the same — as were the barriers to participation listed by each group. Attention should be given to the possibility that disinterest, not lack of information or opportunity, is the reason for lack of participation when evaluating attendance in professional development activities. Limitations of the Study The limitations of the instruments and techniques used to measure the constructs are limitations of the study. The development procedures used for the COR Model Interview Schedule and the Faculty Questionnaire perhaps resulted in certain limitations. The comments and recommendations of the expert in social research and the faculty members involved in testing the instruments might be different from the comments and recommendations of others who could have participated in their roles. Perhaps the questions on the interview schedule and the Likert-style statements on the written questionnaire were interpreted differently by different respondents. Perhaps the respondent interaction with interviewer resulted in varying responses. The lack of a representative sample of faculty across the nation was a limitation. Although a random sample of faculty who had participated in a minimum of four professional development sessions on computer technology was selected and randomly matched to faculty in their same departments who had not participated, the results reported here cannot be generalized to be representative of all college and university faculty because all respondents were at the University of Florida.

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-118Two statistical limitations were the qualitative nature of the data and the size of the sample (n = 30). Any limitations inherent in the use of non-parametric statistics are limitations of this study. Suggestions for Further Research The results of this study suggest questions for additional research if the understanding of faculty participation in professional development activities is to be advanced. 1. The COR Model did describe faculty members who participated in professional development activities on computer technology and distinguished between participants and non-participants on four of the seven constructs. Would the model be as accurate in distinguishing between participants and non-participants if the content of the learning activities were expanded to include other types of professional development? Would it be as accurate if expanded to include structured learning activities that would not be classified as professional? What percentage of the faculty could typically be considered as non-participants? Does the stance toward participation change over time? 2. Motivation of faculty members to participate in learning activities related to computer technology depended largely on goals and expectations. Is there a set of goals that is universal for all faculties that can be used for planning professional development activities? Can administrators influence the goals set by faculty members? Should they attempt to influence the faculty member's goals? What methods would be effective for causing faculty to set or clarify their short and long range goals? Given a faculty who have

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-119communicated their goals to their administrator, what is the most effective way to build expectation that participation in a learning activity will aid in the achievement of the goal? 3. The researcher had difficulty measuring the construct life transitions. Is there a way to define the construct operationally so that a valid measure of this construct can be made? Does the construct distinguish between participants and non-participants? Do certain types of transitions stimulate involvement in corresponding learning activities (e.g. new baby — parenting classes, new job — professional development)? 4. No conclusive evidence was found to show a relationship between the individual constructs and level of participation. Would the results of the two methods of data collection be congruent for levels of participation if the sample were larger? If the level of participation did not include application of information as one criterion for high participation, would a significant relationship be evident? 5. The faculty members studied were a sub-population of the total population of adults for whom Cross designed her model. Can the technique used to evaluate the model among faculty be adapted to evaluate the model's utility with the broader population? Can the model be used to predict participation in adult learning activities? How do faculty differ with respect to adult learning activities from the general public?

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-120A Final Observation The findings of this study add to the accumulation of knowledge in adult education — particularly to the understanding of the motivation of university faculty members toward participation in structured professional development activitiesAdministrators with responsibility for faculty growth and renewal can use information learned through this study to improve their planning for and increase faculty participation in professional development activities; however, further study is needed before the full benefit of Cross's Chain-ofResponse Model for understanding participation in adult learning activities can be utilized.

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APPENDIX A FORCE FIELD DIAGRAMS OF MOTIVATIONAL FORCES TOWARD EDUCATION AFFECTING MIDDLE CLASS ADULTS Education for Vocational Competence Lower-Middle Class Level POSITIVE NEGATIVE 1. Satisfied survival need 2. Satisfied safety need 3. Strong status need 4. Changing technology 5. Access through organizational ties 6. Acceptance of middle class career drives 7. Familiarity with educational processes 1 2 3 4 /\ 5 /\ 6 7 From Participation of Adults in Education: A Force-Field Analysis by Harry L. Miller, 1967, p. 23. Copyright unknown. -121-

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-122Education for Vocational Competence Upper-Middle Class Level POSITIVE 1. Satisfied survival and safety needs 2. Strong status needs 3. Strong achievement needs 4. Change forces in professions and business NEGATIVE Threats to executive groups implicit in changing definition of business roles 6. 7. Growth of professional and executive positions in the economy Familiarity with education Acceptance of middle class career values Strong organizational identification From Participation of Adults in Education: A Force-Field Analysis by Harry L. Miller, 1967, p. 24. Copyright unknown.

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-123Education for Personal and Family Competence Lower-Middle Class Level POSITIVE 1. Satisfied belonging need 2. Strong status need (leading to anticipatory taking over of upper-middle values) 3. Child-centered, nuclear family 4. Openness to mainstream value influences NEGATIVE 5. Traditional value orientation (Puritan ethic vs. emergent values) 6. Stratification of family roles 7. Mass media satisfaction of needs in this area 5 6 7 1 2 3 4 From Participation of Adults in Education; A Force-Field Analysis by Harry L. Miller, 1967, p. 27. Copyright unknown.

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-124Education for Personal and Family Competence Upper -Middle Class Level POSITIVE 1. Satisfaction of lower needs 2. Strong self-realization needs 3. Nuclear, child-oriented family structure 4. Active, associational life 5. Openness to mainstream value influences NEGATIVE 6. Traditional orientation of business uppermiddle males 7. Mass media satisfaction of needs in this area 6 7 1 2 3 4 5 From Participation of Adults in Education: A Force-Field Analysis by Harry L. Miller, 1967, p. 28. Copyright unknown.

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-125Education for Citizenship Competence Middle Class Level Generally POSITIVE 1. Middle class status and recognition needs 2. Cosmopolitanism of upper-middles 3. High level of associational activity and identification with community Middle class objectorientation, abstractions are important NEGATIVE 5. Personal career orientation as a satisfaction of status needs 6. Traditionalist values of lower-middles and executive uppermiddles — resulting in attitude crystallization on community and national concerns Mass media satisfaction of information needs From Participation of Adults in Education: A Force-Field Analysis by Harry L. Miller, 1967, p. 30. Copyright unknown.

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-126Education for Self-Development Middle Class Level Generally POSITIVE NEGATIVE 1. Upper-middle value ' emphasis on satisfaction of self-development needs 2. Frustration of selfdevelopment needs among upper-middle women 3. Social mobility drives of lower-middles 4. Emphasis on self-development in the educational experience of many middle class children 7. Strong emphasis on career, and domination of time by it 8. Family orientation of lower-middle women 9. Increased availability of informal educational means of satisfying needs in this area Upper-middle professional domination of training agencies for business and executive groups Increasing availability of means of self-development From Participation of Adults in Education: A Force-Field Analysis by Harry L. Miller, 1967, p. 32. Copyright unknown.

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APPENDIX B RUBENSON'S PARADIGM OF RECRUITMENT

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c u o o l-l o ao o s -r-l O. o CO to s tu o a o 60 o X 1-1 c c iH ^ to o 4J o o (U OB c 73 (U to 4-1 (U u u < Q. I lU V X i-l 4J a u •H 0) O a. d o IJ T3 4J (U c (U to > to d 09 T3 a d -H 1-1 u tu «10 Q. a d o U X o u Pu (U o a « CO U X> 60 iH d d a CO 0) U-l iH (U l-l 0) CO a O J= l-l (U o o CO d O 3 XI d Q. u o , 4J 1-1 u u 3 a 0) CJ > 00 t-i M-l 3 CO d 4J T3 d d 0) 1-1 l-l 3 ^ U 4J 0) u d (U oi x: o u CO CO ^ 4-1 T3 d td o me 4-1 d a d o o 3 ij a to 0) 60 OS (U l-( d d (U to 1-1 Q d d l-l o o CO iH •H d 4J 4J o CO to 1-1 a, 4-1 0) 1-1 CO O. o Z O 1-4 o 4-1 4-1 u o CO u _ai 60 -H d a ~-i o a 4-1 d o
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APPENDIX C A MODEL TO EXPLAIN ADULT EDUCATION PARTICIPATION AND DROPOUT

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APPENDIX D ANTICIPATED BENEFITS FROM LEARNING

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APPENDIX E DESCRIPTIVE STATEMENTS FOR CONSTRUCTS CROSS-REFERENCED TO THE COR MODEL INTERVIEW SCHEDULE, FACULTY QUESTIONNAIRE, AND CODE BOOK Self-Evaluation Descriptive Statements Interview Schedule Faculty Questionnaire Code Book Consider themselves well prepared for their present position. II. 2 #1-21,22 Rank themselves as instructors in the top quartile of their department . II. 3 #1-23 3. Rank themselves as researchers in the top quartile of their department . II. 4 #1-24 Describe themselves as good at learning new things . II.5;II.6; II. 7 15 #1-29; 26 Describe themselves as enjoying new learning experiences . II.5;II.6; II.7;II.14 16 #1-44 6. Have or would participate in professional development, apart from any status these confer. II.9;II.ll; 11.17 10 #1-33; 38 #2-60,61 -133-

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-134Attitudes about Education Descriptive Interview Faculty Statements Schedule Questionnaire Code Book 1. Believe profesII.ll;II.l4 17 #l-38,39;42 sional development activities are needed or helpful to them personally. 2. Believe profes11.11 18 #1-36,37 sional development activities are important to their institution. 3. Perceive th^t 11.12 21 #1-40 their reference groups value professional development activities. 4. Have enjoyed past 11.14 23 #1-44 adult education activities . 5. Have enjoyed past 11.14 24 #1-44 professional development activities . 6. Look forward to 11.17 25 #1-48 this kind of #2-54 association with faculty colleagues.

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-135Goals and Expectations Descriptive Interview Faculty Statements Schedule Questionnaire Code Book 1. Have a goal that 11.10 26 //1-31;32 is related to the professional development activities (at least indirectly) . 2. Believe particiIII. 22 28 #2-32,33; pation in the pro#2-34,35; fessional develop#2-47 ment activities will lead to the achievement of the goal. 3. Believe they are II.16;IH.20; 27 #1-45-47; sufficiently preIV. 26 #2-30,31; pared to success#2-43 fully complete the professional development activity. 4. Believe achieveII.1;II.10; 8-14 #l-8;30; ment of the goal 11.17 #1-33,34; will satisfy a #2-50-61 need, associated with academic class .

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-136Lif e-Transitions Descriptive Statements Interview Schedule Faculty Questionnaire Code Book 1. Describe themselves as experiencing a dramatic change. V.29 29 #2-62-79; #3-3-17 Information Descriptive Statements Interview Schedule Faculty Questionnaire Code Book 1. Can identify several structured activities on computer technology which are available . III.18;IV.23 30 #2-24,25; #2-38 2. Can describe existing opportunities for professional development activities on computer technology. III.18;IV.23 #2-38; #2-24,25

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-137Opportunltles and Barriers Descriptive Interview Faculty Statements Schedule Questionnaire Code Book 1. Identify themIII. 18;III.19; 32 //1-3; selves as eligible IV. 24 #2-38 to participate in structured activities on computer technology sponsored by their academic departments, professional organizations, or other campus organizations. 2. Can identify III. 18; IV. 24 31 #2-38; 39 several structured activities on computer technology which they believe would benefit them professionally. 3. Believe they can III.20;III.21; 33 #2-43;44; overcome any IV. 26 #2-45,46; situations which #2-30 they identify as barriers.

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-138Participatlon Descriptive Statements Interview Schedule Faculty Questionnaire Code Book 1. Are/have attended professional development activities voluntarily. 2. Are/have attended professional development activities on computer technology voluntarily. 3. Evaluate their participation in professional development activities positively. 4. Evaluate their participation in professional development activities on computer technology positively. II. 14 24 #1-42 III.19;IV.24 36 #2-24,25; #2-41 11.14 35 #1-44 II. 14;IV.25; III. 18,19 36 #2-26,27; #2-42

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APPENDIX F INTERVIEW GUIDELINES To insure that the data obtained during the interview is worth analyzing, all significant elements of the interview situation should be controlled in order that the data represent what the interview schedule was designed to describe. Topics to be addressed by these guidelines are the interviewer, the respondent, the surroundings of the interview, and the process of questioning and recording. The Interviewer Parten's (1950, pp. 138-140) list of characteristics which the "ideal" interviewer should possess have been adapted for the current study and are given in the following list. 1. Ability to talk easily to university faculty. 2. Ability to analyze situations and people quickly and accurately. 3. Keen observational skills. 4. Persistence and thoroughness. 5. A genuine interest in people. 6. Conscientiousness, honesty, and reliability. 7. A good memory. 8. A legible handwriting. 9. An interest in research and ideas. 10. A confidence building appearance and manner. -139-

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-14011. Ability to grasp and follow instructions precisely. 12. Ability to sunnnarize the information obtained and to record the information objectively and accurately. The Respondent The sample to be interviewed (and alternates in case individuals refuse to participate or cannot be reached) should be selected before beginning the interview process. Letters of introduction which present the project should be sent five to seven days prior to a follow-up telephone call. The purpose of the telephone call is for the interviewer to introduce himself /herself , to answer any questions which may have arisen as a result of the letter, and to schedule the interview. During the call, the interviewer should also identify a location (preferably in the proximity of the faculty member's office) which would be conducive to a good interview. If the interviewer plans to tape the interview, permission to do so should be requested at this time. A written telephone conversation guide should be used to assure that the telephone contact accomplishes its purposes and that there is consistency between phone contacts. Environment of Interview Favorable interviewing conditions include the following: 1. The interview should be held in private. The presence of friends or office mates is not conducive to a frank, uninhibited response .

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-1412. There should be no distracting or disturbing interruptions such as ringing telephones or people coming and going. 3. The setting should be comfortable to the respondent and chairs should be placed so that the individuals can have eye contact but not violate the respondent's personal space. 4. If the interview is to be recorded, the interviewer should check the batteries and tapes prior to the interview to make sure everything is working properly. (Do not plan to use electrical plugin for the recorder as the outlets may be inconvenient to your seating arrangement.) Place the tape recorder out of the way in order to minimize its effect on the interview. Also, arrive at the interview location early so that you may be set up and ready for the interview at the appointed time. 5. A positive atmosphere should prevail, with interviewer expectations that the respondent has the time and is willing to assist with the study. Conducting the Interview Asking the questions. The interviewer should follow the schedule order of questions, asking every question unless otherwise specified. The interviewer should ask the questions as written in order to allow comparison of answers from all respondents. Even the interviewer's voice inflections should be the same for each respondent, if possible. In cases where one of several alternative answers is to be chosen by the respondent (see the second part of questions Il.l.b. and II. 5. on the interview schedule), the interviewer should read the "possible" answers out loud and let the respondent choose the one with which he

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-142agrees. If the interviewer has reason to believe the respondent misunderstood a question, he or she should repeat the question. The Interviewer should clarify the question only if the respondent clearl cannot understand the question or sees more than one meaning in the question. Care should be taken, by the interviewer, not to "bias" or "lead the respondent by his/her remarks either before or after asking a particular question. In a case where the interviewer has asked an open-ended question and the respondent gives a vague or general answer, no answer at all, or a statement that he does not know, the interviewer should follow with a neutral probe. Neutral probes suggested by Bailey (1978) include the following: 1Repeating the question. This is done whenever the respondent hesitates or appears not to understand the question. With lengthy questions it is often necessary to repeat two or three times before the respondent has it clearly enough in mind to begin concentrating upon an answer . 2. Repeating the answer . This type of neutral probe can be used by the interviewer who is not certain that he or she understood the respondent's answer correctly. Repetition of the answer can correct errors and assure both respondent and interviewer that the answer is recorded correctly. Repetition also gives the respondent an opportunity to think about elaborating it further. 3. Indicating understanding and interest . The Interviewer's Manual (University of Michigan, 1969) recommends that the interviewer indicate that he or she has heard the answer and approves of it, thus stimulating the respondent to continue. 4. Pause . The Manua 1 also recommends that the interviewer pause and say nothing if the response is obviously incomplete. This indicates that the interviewer knows the respondent has begun to answer and is waiting for him or her to finish. 5« A neutral question or comment . "How do you mean that?" or "Tell me more" indicate to the respondent that his or her answer is on the right track but that more information is desired, (p. 173)

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-1A3There are. several shifts in questioning in the COR Model Interview Schedule: between sections designated by Roman numerals and before questions 11, 29, and 30. Introductory statements such as "The next group of questions asks for your opinion on . . ." may be necessary in order to change the mental "set" of the respondent when a shift of subject occurs on the schedule. Recording the information . The interviewer should write legibly and keep the schedule as neat as possible; schedules should not be copied over. There should be an entry for every item on the schedule except for either section III or IV. Questions in section III are for Group II (non-participants) while section IV questions are appropriate for participants only. The interviewer should listen "attentively to what the respondent says — the words he uses, the way she phrases her response — and record them as closely as possible. The entire answer need not be recorded but the statements/phrases that are pertinent to answering the question must be. If the interviewer needs additional time for recording an answer, "fill-in" questions may be asked, such as, "Why do you think so?" or "What do you mean by that?" Sometimes a respondent cannot align himself with any one of the alternatives presented in opinion questions without specifying the condition under which he holds a given view. In addition to checking the most appropriate answer, the interviewer should also note the conditions of the qualified response. Notes should be made to explain entries which may appear to be inconsistent or unreliable. Finally, the interviewer should add his own appraisal of the respondent and/or situation to the interview schedule, if he believes the supplementary observations would be useful to the

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-144study. These comments should be clearly marked as those of the Interviewer . Further Information A more detailed presentation concerning interview procedures in general can be found in Chapter X of Parten's 1950 book Surveys, Polls, and Samples or Chapter 8 in Bailey's (1978) Methods of Social Research. Specific questions related to the COR Model Interview Schedule should be referred to the director of the study.

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APPENDIX G COR MODEL INTERVIEW SCHEDULE

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COR MODEL INTERVIEW SCHEDULE I. Introduction of interviewer and study II. Questions for respondent I. The U: catalogue lists your position as • Is that correct? no — a yes— » b a. '.-.7131 is the correct title o£ your position? b. Describe your work assignment (responsibilities) for a typical academic year in that postitlon. ^ appointment: 9 month 12 month yrs. at UF > How do vou rate your preparation (training and experience) for your present' assignment on a scale of 1 to 5? poor 12 3 4 5 excellent 3. Within vour college, where would you rank yourself as a teachertop quartile? top half? bottom half? bottom quartile? 4. Within your college, where would you rank yourself as a researchertop quartile? top half? bottom half? bottom quartile? What kinds of research do you do? What do you have to do to do that kind of research? How do vou analyze your data? . . Do you do the analysis or does grad. assts., etc.? 5. How would you like Co change your assignment?_ Please indicate the i.-nportance of Che assignment change on a scale of 1 to 5. Not very important 12 3 4 5 Very important 6. If you were given a sabbatical for Che up-coming semester with full pay, what would you do? Why? 7. '."nat would you like Co be doing — say 10 or 15 years from now? 8. .Are there any intermediate steps you are working on in order to reach chat goal? 9. Different people are motivated by different things or needs to achieve certain goals. What do you expect to accomplish by achieving these goals? 10. Does accomplishing your goal(s) involve the use or understanding of computers — eicher directly or indirectly? If so, how? How do you see computers as relating to your job? Ranae Coals Need Conouter -146-

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-14711. In your opinion, is ic inportanc Co the University of Florida for you to participate as a learner in structured activities related to teaching and research? 3y structured activities I mean activities that were preplanned by your department, another departnent, your professional associations, etc. Please rate on a scale of I to 5. Definitely not important 12 3 4 5 Very important Please e; YES-> a a. Describe some recent educational activities that you have been involved in. b. .Approximately how many hours over what period of time did you spend learning about the subject? c. Did you enjoy the activities? Period Pro. Subject Hrs./of tine Eniov -r K Y N 13. '.'.'ould you classify any of the above activities as directly related to your teaching or research? If so, which ones? 16. Under wh.TC circumstances are you willing to participate in ed. .ictivities rdlaced to your teaching or research? (e.g. own time, own expen.se, reward) 17. Do you attend seminars arranged by your dept. on recent developnents in your discipline? No — IvTiv no t ? Yes — .»>.at beneiics do yoa anticipate '.^ill result from your particisaciJn? (Rank benefits in order of importance i: there is more than one.) Ple.ise divide these cards into to stacks: motivators for you to part, and n >n-n,-.c i V ! r . R-'.nk the motivicors in order of imoortance.

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-USUI. Questions for NOM-PARTICIPAKTS (Group II) 18. Are you aware of any scruccured activities on computer technology which have been or are being sponsored by your department, professional organizations, or other campus organizations? NO— ^ V Yes— ^ a a. Describe them. b. Identify anv that you believe would benefit you professionally. Benefit Activities Attended 19. Have you voluntarily attended any of these activities? N0-^> 20 YES — Wliich ones? SKI? TO SECTION IV FOR PARTICIPANTS 20. If not, why not? 21. Do you believe you will be able to (overcome whatever they identified in "20") within the next six months and participate in the (activity you identified as beneficial in "13")? Indicate the strength of your answer on a scale of I to 5. l=not at all 2»sli§ht chance 3 = 50'; chance i»strong possibility 5=very sure barrier can be overcome 22. In an earlier question (.1110) you said that the use or understanding of computers would help you accomplish at least one of your professional goals. Would participation in (activities identified in "13") help you achieve your goal(s)? NO-^ Section V YES— > If you do complete the computer activity just mentioned (see #18), will you then be able to achieve your goal(s)? Indicate your answer on a scale of I to 5. very unlikely 12 3 4 5 very likely CO TO SECTION V. IV. Questions for PARTICIPANTS (Group I) 23. You did (not) mention earlier that you have participated in educational activities on computer technology as a student. I would like to focus the next few questions on that area. Please identify and describe the structured activities in shich you are eligible to participate on computer technology which have been or are being offered by your department, professional organizations, or other campus organizations. I'-t. Did you voluntarily participate in any of these activities? NO— > ISb YES— > Please identify which ones. 25. Please answer the following questions for each computer technology activity you have participated in: a. Miat was your objective? b. Were you successful? If not, why not? c. How much structured time did you spend on this activity? (class time, etc.) d. How much additional time did you spend on your own on this activity? (application, additional practice, etc.) e. Are you currently using the information/skill you gai.-.ed from

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-149Accivicv Oblectlve Successful — If noc, why? S-hrs. U-hrs. L'se-hov 26. What difficulties did you have Co overcome in order to participate in the professional development activities on conp. technology? 27. Did or will your successful completion of the(se) activities on comp. tech. contribute to your achieving the goals you identified in Q-10? (Please indicate how helpful on a 3-poinc scale . ) No help at all 12 3 4 5 Virtually assures its achievement 23. Have any of your colleagues participated in ed. activities on computer tech.? Yes No Questions for all respondents 29. Life transitions are gradual or dramatic periods of change which require adjustments to new positions in life. These changes are roughly related to one's age and social role. Please identify from this list any changes you have experienced in the past 18 months: 30. Please respond to this written questionnaire which will be used as a check on the interpretation of inf orTnacion gained from the interview. 31. Have you thought of anything related to your participation (or nonparticipation) in structured ed. activities chat is relevant to this studv but we have not discussed? Closure — thanks, confidentiality, share results if intecesced— > Y

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-150knowledge of subject matter economic reasons (maintenance of or advancement on job, etc.) assoclatlonal reasons (relationships u/members of dept. etc.) recognition of your efforts and accomplishments achievement needs self-development Marker Events Leave home Establish new living arrangements Enter college Start first full-time job Select mate Marry Establish home Become parent Get hlred/flred/quit job Enter Into comnmnity activities Establish children In school Progress In career or consider change Possible separation, divorce, remarriage Possible return to school Crucial promodoa Break with mentor Responsibility for three-generation family; I.e., growing children and aging parents For women: empty nest; enter career and education Cap career Become mentor Launch children; become grandparents New interests and hobbies Physical limitations; menopause Active participation in community events Possible loss of mate Health problems Preparation for retirement Retirement " " Physical decline Change in finances New living arrangements Death of friends/spouse Major shift in dally routine Age Group 25 and below 26-35 36-45 46-55 56-64 65+

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-151Card Questions In addition to the five pages of interview schedule, six 3x5 index cards were used with the last part of question 11.17. On each card was listed either knowledge of subject matter, economic reasons (maintenance of or advancement on job, etc.), associational reasons (relationships with members of department, etc.), recognition of your efforts and accomplishments, achievement needs, or self-development. The interviewer shuffled the cards before handing them to the respondent. The respondent divided the cards into one stack, of motivators to participate and one stack of non-motivators. (All cards could have been placed into one stack if the respondent so chose.) The respondent then ranked the cards in order of importance. While the respondent completed the written Faculty Questionnaire, the interviewer transferred the information from the cards to the summary sheet. Marker Events Following the explanation of what was expected in Question V.29, the respondent was given the list of "marker events" to check ones which were appropriate. The respondent was asked to check his/her age group after finishing with the marker events.

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APPENDIX H FACULTY QUESTIONNAIRE Please indicate how strongly you agree or disagree with the following statements by writing the appropriate letter in the blank to the left of each question. Should a statement not apply to you, place N/A (not applicable) in the blank. 1. Because of my past training and experience, I am well prepared for the tasks required of me in my present position at the university. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 2. If I ranked the faculty in my department based on their instruction, I would rank myself in the top quartile. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 3. If my colleagues ranked the faculty in our department based on their instruction, I would be ranked in the top quartile . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 4. Students in my department would rank me in the top quartile of all faculty in the department if the ranking was based on instruction. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 5. If I ranked the faculty in my department based on their research, I would rank myself in the top quartile. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 6. Colleagues in my department would rank me in the top quartile of all faculty in the department if the ranking was based on research. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree -152-

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-1537. If I had an opportunity to participate in a learning experience involving an instructional or research technique that was totally new to me, I would choose to participate . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 8. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because my colleagues went to the trouble to plan the seminar . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 9. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because I find this type of association with colleagues pleasureable . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 10. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because of a concern for self-development. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 11. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because I believe it is important for my colleagues to recognize that I am "keeping up with" current developments in the field. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 12. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because it is important for me to keep up with current developments in the field. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 13. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because other faculty members would expect me to participate. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 14. If a committee of my colleagues arranged a seminar on a recent development in my discipline, I would attend because my participation is important for me if I am to advance in my position in the department. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree

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-ISA15. I am good at learning new things. a. strongly agree b. agree " c. no opinion d. disagree e. strongly disagree 16. I enjoy learning new things. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 17. Structured educational activities which focus on research/ instruction are needed or helpful to me personally. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 18. Structured educational activities which focus on research/ instruction are important to the University of Florida . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 19. My dean values structured educational activities which focus on research/ instruction. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 20. My department chair values structured educational activities which focus on research/ instruction. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 21. The faculty in my department value structured educational activities which focus on research/ Instruction . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 22. My spouse supports my participation in structured educational activities on research/ instruction . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 23. I have enjoyed participation as a student in educational activities since completing my last degree. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 24. I have enjoyed participation as a student in educational activities related to research/ instruction since my last degree . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree

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-15525. Associating with faculty colleagues in educational situations where we are both students is enjoyable, a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 26. I have a professional goal which is related to the use or understanding of computers. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 27. I am/was sufficiently prepared to complete successfully educational activities on computer technology which are/were available to me. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 28. Participation in educational activities on computer technology has/will lead to the achievement of a professional goal of mine. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 29. Within the past 18 months, I have experienced a dramatic change in my life (e.g. new job, crucial promotion, divorce, health problems, etc.). a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 30. I am aware of several structured activities on computer technology which are being or have been sponsored by departments on campus or professional organizations. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 31. I am aware of several structured activities on computer technology which have or would benefit me professionally, a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 32. I am eligible to participate in the structured activities on computer technology. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 33. I can/have overcome any difficulties (e.g. prohibitive demands on time, transportation problems, etc.) which would hinder my participation in structured activities on computer technology. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree

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-15634. My present understanding of and skills in computer technology are adequate for someone in my position at this university. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 35. My participation as a student in structured educational activities has been a positive experience. a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree 36. My participation as a student in structured educational activities on computer technology has been a positive experience . a. strongly agree b. agree c. no opinion d. disagree e. strongly disagree

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APPENDIX I LETTER OF INTRODUCTION As part of future planning for the Office of Instructional Resources, we have sent a questionnaire to a random sample of faculty at the University of Florida to solicit their views and opinions of various professional activities which the Office should provide. In addition, we pulled a very small sample of faculty which we would like to personally interview. You were chosen in that sample. Would you be willing to give us 30 minutes of your time for the interview? Someone from OIR will be calling you in the next few days to arrange an appointment. I hope you will be willing to help. Sincerely, Jeaninne N. Webb Director Office of Instructional Resources JNWrmrh -157-

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APPENDIX J INITIAL TELEPHONE CONTACT GUIDE Time/Date Initial Telephone ConCacc • This is Winnie Cooke, and I am calling you in reference co a letter you received from the Office of Instructional Resources concerning a study we are doing on professional activities Did you receive the letter? Let my give you some background data about the studv. You were selected to participate because of your position in your career development and your past participation in professional activities. You have information that we ne" in order for us to understand what motivates faculty to continue to develop professionally. A considerable amount of time has already been invested bv several persons We have researched the literature on the topic and have used IT". T '""'^ ""^ "^he information y" can supply through an in-depth interview to either confirm, refute or otherwise alter our hypotheses concerning why faculty members do or do not participate as a student in structured educational activities related to their The intormation you and the other faculty members supply will be compiled and presented in a report. This report will be used for planning of profession^ activities in the future. This part of the study is actually an attemprto i:en^^^^u"^:h":^^"^^''"H'" ^ ^'^--^^^^ and"i;?;r::tion given by all of the faculty members will be presented in a manner that will not reveal the identity of the persons who participated in the JCdy. ^o";'i'o?:d\°rJo:::er"o" ""'^^ °" "^''^ ''^^ '^"-'^ ^^^^^ The interview should take about 30-45 minutes of uninterrupted time. Do you wi'ou lurATT'^ ^""-^ "'^"^ ^"^^ -° °f ""Id meet ' without the telephone ringing or other faculty wandering in and out? When is a good time for you? -158-

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-159OPT I ONAL I would like to record Che interview so that I can listen more intently (without having to Cake so many notes) and can refer back to the Cape if I need to later. Would that bother you? If NO really don't expecc that we will touch on any topic that you would not want recorded; buC if we did, I would turn the recorder off at your request or we could edit it out at the end of our session. (PAUSE) Well, if you are still uncomfortable with the recorder, I won't use it. It is your open response to the questions that I need anyvay — not the recording. The recorder would have just made my job a little easier. Well, have we covered everything? The interview is scheduled for . — . • (Should I reserve that room, and if so, whom should I contact to make Che reservacion?) Do you have any questions I b^ve noc answered about the study or what I need from you? As I mentioned earlier, the purpose of the interview is to decermine what motivates faculty to participate or not participate as a student in structured educational activities related to their prof ession, and I'm gald you have agreed to participate in the study because we really believe examining the topic from your perspective is important to out getting an accurate understandir of what's happening. I look forward to talking with you Bye

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APPENDIX K SUGGESTED REVISIONS FOR CODING OF THE INTERVIEW SCHEDULE

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SUGGESTED REVISIONS TO THE INTERVIEIJ SCHEDULE I. Introduction of interviewer and study \ II. Questions for respondent 1. The UF catalogue lists your position as . Is that correct? no-4 a yes--) b _ a. What is the correct title of your position? b. Describe your work assignment (responsibilities) for a typical _ academic year in that postition. appointment: 9 month 12 month yrs. at Ur 2. How do you rate your preparation (training and experience) for your present assignment on a scale of I to 5? poor L 2 3 4 3 excellent 3. Withiw yovjr college, where would you rank yourself as a teacher — top quartile? top half? bottom half? bottom quartile? 4. Within your college, where would you rank yourself as a researcher — top quartile? top half? bottom half? bottom quartile? What kinds of research do you do? What do you have to do to do that. kind fii research.? How do you analyze your data? Do you do Che analysis or does grad. assts., etc.? 5. How would you like to change your assignment? Please indicate the importance of the assignment change on a scale of 1 to 5. Not very important 12 3 4 5 Very important 6. If you were given a sabbatical for the up-coming semester with full pay, what would you do? Why? 7. What would you like to be doing — say 10 or 15 years from now? 8. Are there any intermediate steps you are working on in order to reach that goal? 9. Different people are motivated by different things or needs to achieve certain goals. What do you expect to accomplish by achieving these goals 10. Does accomplishing your goal(s) involve the use or understanding of computers — either directly or indirectly? If so, how? How do you see computers as relating to your job? Range Goals Need Connuter S L i 1 ; -161-

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* APPENDIX L CODE BOOK FOR COR MODEL INTERVIEW SCHEDULE Card 1 1 __ ID# 3 _ Group ; 1 = participant, 2 = non-participant A _ College : 1 = Agriculture, 2 = Architecture, 3 = Education, 4 = Engineering, 5 = Health Related Professions, 6 = Law, 7 = Liberal Arts and Sciences, 8 = Medicine 5 Dept. ; 1 = Agricultural Engineering, 2 = Architecture, 3 = Entomology and Nematology, 4 = Food and Resource Economics, 5 = Foundations of Education, 6 = Geology, 7 = Health and Hospital Administration, 8 = Home Economics, 9 = Law, 10 = Pediatrics, 11 = Psychiatry, 12 = Psychology, 13 = Physiological Sciences, 14 = Zoology 7 _ Sex ; 1 = M, 2 = F 8 _ Rank ; 1 = assistant professor, 2 = associate professor, 3 = full professor, 4 = distinguished research professor, 5 = graduate research professor 9 _ Administrative title : 1 = no, 2 = yes 10 % teaching 12 % research 14 % service and other 16 % administration 18 _ Appointment ; 1=9 months, 2 = 12 months 19 Years at UF : actual (round to nearest whole) 21 Preparation ; 1.0-5.0 23 _ Teacher : 1 = top quartile, 2 = top half, 3 = bottom half, 4 = bottom quartile, 0 = does not apply -162-

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-163Researcher ; 1 = top quartile, 2 = top half, 3 = bottom half, 4 = bottom quartile, 5 = not applicable Statistical data ; 1 = none, 2 = others have primary responsibility for analysis, 3 = interviewer has primary responsibility for analysis Role change : 1 = minor, 2 = dramatic, 3 = no change Change importance ; 1.0-5.0, 00 = N/A Sabbatical ; 1 = does not want, 2 = would use to improve knowledge/skills, 3 = would use to raise his/her status, 4 = to get away from it all, 5 = does not want now, but would consider later when circumstances change, 6 = complete current/proposed projects, 7 = already had one Long range goal ; 1 = promotion in dept. or field; 2 = improved reputation; 3 = major change in career direction; 4 = no change, continue doing current assignment; 5 = personal; 6 = advancing knowledge in his chosen field through research; 7 = continue academic career and also establish private practice/consultation; 8 = improved artistic skills in his discipline; 9 = achieve balance between work and artistic pursuits LR goal/computer : 1 = related directly, 2 = related indirectly, 3 = not related Short range goals ; 1 = none, 2 = increased/ improved research, 3 = increased/ improved teaching, 4 = increased/ improved service, 5 = increased/ improved computer skills, 6 = win recognition in national contest in his discipline, 7 = decrease current work load, 8 = career advancement to next step, 9 = other Goals-needs (first two given); 1 = status, 2 = economics, 3 = keep up to date, 4 = advancing the body of knowledge in chosen field, 5 = personal satisfaction, 6 = power/ influence over decision making, 7 = needs are satisfied, 8 = stay active, 9 = other Computers — job related : 1 = major importance, 2 = minor importance, 3 = not important Learner importance: 1.0-5.0 Learner importance — why (first two given): 1 = no, usually not specific to my area; 2 = yes, to stay current; 3 = yes, more efficient way to learn; 4 = yes, to set example for other faculty; 5 = yes, depending on relevance to area; 6 = yes, funding for structured activities is usually contingent on grants (i.e., competitive); 7 = yes, provides validation for college; 8 = yes, personal satisfaction; 9 = other

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-164Attitude — colleagues : 1 = do not know, 2 = negative, 3 = mixed, 4 = positive Relationship to rank; 1 = do not know, 2 = none or mixed, 3 = higher rank correlates with more participation, 4 = higher rank correlates with less participation, 5 = participation correlates with factor other than rank, 6 = other Voluntarily participated since degree : 1 = no; 2 = yes, teaching; 3 = yes, research; 4 = yes, teaching and research; 5 = yes, other; 6 = teaching, research and other; 7 = teaching and administration; 8 = post-doctoral work Degree of participation — other : 1 = none, 2=1 class or conference or equivalent, 3 = "everything else," 4 = heavy participation: completion of 3 courses or equivalent (much time commitment) Enjoyment : 1 = no, 2 = yes, 3 = not applicable, 4 = some of the time Circumstances limit participation ; 1 = personal cost, 2 = time constraints, 3 = setting, 4 = content, 5 = parking problems, 6 = must personally be interested — not as part of job or for benefit of UF, 7 = not a priority, 8 = ability to achieve goals of program, 9 = other Department seminars : 1 = no, none offered; 2 = no, offered but do not attend; 3 = sometimes; 4 = yes, to increase awareness of what is going on; 5 = yes, to increase knowledge of subject matter; 6 = yes, to make professional contacts within and without the department; 7 = yes, social reasons; 8 = yes, important to institution; 9 = respondent organizes seminars himself Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no, 2 = yes, 3 = somewhat Information applied : 1 = research, 2 = teaching, 3 = word processing

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-16555 Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1 , 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortrap, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA 57 Objective : 1 = learn how to use computer, 2 = to become ~ familiar with software, 3 = to learn programming, 4 = understand microcomputer 58 _ Objective achieved : 1 = no , 2 = yes , 3 = somewhat 59 _ Information applied : 1 = research, 2 = teaching, 3 = word processing 60 Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA 62 _ Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer 63 _ Objective achieved ; 1 = no, 2 = yes, 3 = somewhat 64 _ Information applied : 1 = research, 2 = teaching, 3 = word processing 65 Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA 67 _ Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer 68 _ Objective achieved : 1 = no, 2 = yes, 3 = somewhat

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-166Information applied : 1 = research, 2 = teaching, 3 = word processing Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no, 2 = yes, 3 = somewhat Information applied : 1 = research, 2 = teaching, 3 = word processing Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no , 2 = yes , 3 = somewhat Information applied : 1 = research, 2 = teaching, 3 = word processing Card #1 Card 2 ID# Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic

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-167Programraing 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no , 2 = yes , 3 = somewhat Information applied : 1 = research, 2 = teaching, 3 = word processing Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no , 2 = yes , 3 = somewhat Information applied : 1 = research, 2 = teaching, 3 = word processing Computer activity : 01 = Intro to IBM, 02 = Word Processing 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA Objective : 1 = learn how to use computer, 2 = to become familiar with software, 3 = to learn programming, 4 = understand microcomputer Objective achieved : 1 = no, 2 = yes, 3 = somewhat Information applied ; 1 = research, 2 = teaching, 3 = word processing

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I -16818 Computer activity : 01 = Intro to IBM, 02 = Word Processing ~ 1, 03 = Word Processing 2, 04 = Visicalc 1, 05 = Visicalc 2, 06 = Lotus 1, 07 = Lotus 123, 08 = Data Based Management Systems, 09 = CMS 1, 10 = CMS 2, 11 = CMS 3, 12 = CMS 4, 13 = Basic Programming, 14 = Basic Programming 2, 15 = Basic Programming 3, 16 = Basic Programming 4, 17 = Statistical Analysis System, 18 = TCP, 19 = 4 courses in basic at Tandy Corp., 20 = Fortran, 21 = Easywriter, 22 = Intro to computers at NERDC/CIRCA 20 Objective : 1 = learn how to use computer , 2 = to become ~ familiar with software, 3 = to learn programming, 4 = understand microcomputer 21 _ Objective achieved : 1 = no, 2 = yes, 3 = somewhat 22 _ Information applied : 1 = research, 2 = teaching, 3 = word processing 23 _ # of additional computer activities 24 Total of computer activities 26 Total # of objectives achieved 28 Total # of info, applied 30 Difficulties (list first two): 1 = none, 2 = amount of time, 3 = location, 4 = workload, 5 = scheduling conflicts, 6 = fear of computer technology, 7 = (for Circa classes) boredom, 8 = parking 32 Contribution to goals : 1= positive comment, 2 = negative comment, 3 = no comment or neutral comment 34 Contribution — rank (actual): 1.0-5.0 36 _ Colleague participation : 1 = no , 2 = yes, 3 = don't know 37 _ Did this respondent already have computer skills ? 1 = none, 2 = minimal, 3 = considerable 38 _ Awareness of computer activities : 1 = not aware of any, 2 = can name sources vaguely, 3 = can name sources but not describe offerings clearly, 4 = can name sources and describe several offerings, 5 = can name sources and describe one offering 39 _ Beneficial : 1 = no; 2 = unsure; 3 = marginal; 4 = yes to at least one; 5 = yes, to his staff; 0 = not applicable ^0 _ Attendance : 1 = no; 2 = yes, FSC sponsored; 3 = yes, other sponsor 41 _ Total // of activities attended

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-169Total # of activities with objectives achieved Barriers (first two): 1 = none, 2 = location, 3 = work load, 4 = time, 5 = low priority, 6 = crowded, 7 = class was filled, 0 = not applicable Believe you can overcome barrier (actual): 1.0-5.0, 00 = not appliable Contribution to goal : 1 = yes, 2 = not, 3 = not sure, 0 = N/A Rank of contribution : 1.0-5.0, 00 = no importance to goal Knowledge of subject matter : 1st blank 1 = no , 2 = yes; 2nd blank, actual rank Economic reasons : 1st blank 1 = no, 2 = yes; 2nd blank, actual rank Associational reasons : 1st blank 1 = no, 2 = yes; 2nd blank, actual rank Recognition of accomplishments : 1st blank 1 = no, 2 = yes; 2nd blank, actual rank Achievement needs : 1st blank 1 = no, 2 = yes; 2nd blank, actual rank Self-development : 1st blank 1 = no, 2 = yes; 2nd blank, actual rank Marker events : 1 = no, 2 = yes Card #2 Card 3 ID# Marker events (beginning with Cap career): 1 = no, 2 = yes Age group : 1 = 25 and below, 2 = 26-35, 3 = 36-45, 4 = 4655, 5 = 56-64, 6 = 65+ Questionnaire : 1 = strongly agree, 2 = agree, 3 = neutral/no opinion, 4 = disagree, 5 = strongly disagree, 6 = not applicable Made suggestions : 1 = no, 2 = yes (itemize on white sheet) # of sessions at Faculty Support Center (FSC) (actual count from OIR records)

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-170Applied ; 1 = no , 2 = yes Participation rate : 0 = no sessions at FSC, 1=4 sessions at FSC but none applied, 2 = more than 4 sessions at FSC but not applied or 4 sessions with at least one applied, 3 = more than 4 sessions at FSC and at least 1 applied

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APPENDIX M SUMMARY OF STATISTICAL DATA BY HYPOTHESIS AND DATA SOURCE

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1-H fH fH rH fH rH iH J r< M c i-< EW c 4-* O o U o O CJ u a; o I ^ >. •H > !U 1-1 > 1-1 > a> 1-1 > (U •rH £ 4J u J= 4J 1.1 jC tl x: 4-1 1-1 x: 4-1 u 4J u .c 4J . 4J fc] XI 4J I o c a. CD 3 4-1 O a u 0) CJ3 I a ^ X >» (fl tJ XI o o I to >, H G. 3 O O -H ij U-l 4J CJ iH rJ I Q to CO (U (U 1-1 tH 4-> )J O, 1-1 Vj 3 d cfl O 3 m 4-1 O 14 T3 O d >^ a (Tj xi o I d o d •H a o a. 4J d a. 1-1 3 « 01 3 4J O O. •i-i O (0 u iH u 1-1 H o CJ a; CJ 1-1 eo > U X >. U-l XI u w XI d to M 04 I Ck I CJ -172-

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-173iH I— ( 1— 1 iH 1— 1 ?H iH 3 3 3 3 C C C C C 4J LJ 4-1 O o o o o -) .—1 •>-) •r-l •>-) "-) Q) 1— ( ID OJ u u 0) T-l )-i 4-1 0) T-l l-l J= 4-1 0) cj tn 4J CO 0) C 3 3 0) ^ 3 •a > o tn 4-1 CO 0) -H IJ £ 4J 0) a CO u CO a c 3 M O" (U CO c c o (U 3 •H T3 > o (U 40 > o > 01 •H T5 CO 0) •w (U J 4-1 3 o 4-1 1 4-1 3 u to 1-1 T3 to 4-1 bJ 0) 4-1 CO <: CM CM 1 < 1 oa I c o >> o o C r-t to 0) 4-1 > O 0) cu u X >^ 10 CO U ^ 0-1 o o CM I u to H c: o iH 4J to >% <4-l D. O 1^ o to iH 1-1 t: 0) 4J o > u H 4) to 4J P-l I Q to tn Vj CM OJ 0) c o o c t.1 l-l CO n 01 J 0 4J CO l-l o. 01 1-1 > o S-i >^ to O, to .Q CUi a o CM I c o H-l -H O 4J C CO o l-l a 0) 1-1 4-1 > O CO O; --I a hJ 4-1 t-l S-I o to >4-l ^ Ol c I c o c o O 4-1 CO o; CJ 4-1 C l-l CO 0) OJ CI. -H > O •f-l Sj 0) 1-1 O OJ 4-1 •HO. U 4-1 X i-i a j3 PL, C3

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APPENDIX N SUMMARY OF CONSTRUCT STANCES FOR ENTIRE COR MODEL BY INDIVIDUAL AND GROUP (DATA FROM INTERVIEW SCHEDULE)

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Sclf-EvaluacioQ Attitude about Education Coals and Expectations Most Less Lease Positive Positive Positive Most Less Lease Positive Positive Positive Positive Negative Croup I I 2 3 4 S 6 7 8 9 10 U 12 13 14 15 Total 10 Croup 66 . 6 Percentage X X X X X X X X X 4 26.66 1 6.66 X X X X X X X X X X X X X 13 86.66 2 13.34 9 60.00 6 40.00 Croup II 16 X 17 18 19 20 21 22 23 X 24 23 26 X ?7 28 X 29 30 X Total 5 Group 33.14 Percentage 9 60.00 66 X X X X X X X X X 11 73.34 2 13.34 2 13.34 66 X X X X X X X X X X X X X X 14 93.34 -175-

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-L76"1 Opportunl dcs Life Transition and Barriers Information Participation Level Level Level Highest Less Least Level 3 2 1 Positive Negative Awareness Awareness Awareness i 3 2 10 X X X X X X X X X X X X X X X X X X X X X X X X X. X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X 6 6 3 15 0 15 0 0 12 3 40.00 AO. 00 20.00 100.00 0 100.00 0 0 80 20 X X X X X X X X X X X X X X X 2 13.34 9 60.00 4 26.66 15 100.00 12 80.00 3 20.00 2 2 7 — — X-

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1 APPENDIX 0 SUMMARY OF CONSTRUCT STANCES FOR ENTIRE COR MODEL BY INDIVIDUAL AND GROUP (DATA FROM FACULTY QUESTIONNAIRE)

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Self-Evaluation Attitude about Education Goals and Expectations Hos c Less Positive Positive Least Positive Most Less Positive Positive Least Positive Positive Negative Group I I 2 3 4 5 6 7 8 9 10 U 12 13 14 15 Total 2 Group 13.34 Percentage 8 53.34 5 33.34 14 93.34 66 11 73.34 4 26.66 Group II 16 X 17 18 19 X 20 21 22 23 24 2S X 26 27 28 29 30 Total 3 Group ' 10.00 Percentage X X X 6 40.00 6 40.00 12 80.00 2 13. 34 1 6.66 1 6.66 X X X X X X X X X X X X X X 14 93.34 -178-

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-1791 Life Transition Opportunities and Barriers Information Participation Level Level 2 1 Positive Negative Highest Least Awareness Awareness Level 3 2 1 3 20.00 12 80.00 11 73.34 4 26.66 13 36.66 2 13.34 12 80.00 1 2 6.66 13.34 X X X X X X X X X X X X 5 33.34 10 66.66 3 20.00 12 80.00 13 86.66 2 13.34 14 7 2 6.66 26.66 46.66 13.34 1 6.66

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REFERENCES Bailey, K. (1978). Methods of social research . New York: Macmillan. Boshier, R. (1971). Motivation orientations of adult education participants: A factor analytic exploration of Houle's Typology Adult Education , 21^, 3-26. Boshier, R. (1973). Educational participation and dropout: A theoretical model. Adult Education , 23 , 255-282. The Carnegie Commission on Higher Education. (1972). The fourth revolution: Instructional technology in higher education . New York: McGraw-Hill. Cattell, R., Radcliffe, J., & Sweney, A. (1963). The nature and measurement of components of motivation. Genetic Psychology Monographs , 68 , 49-211. Cross, K.P. (1981). Adults as learners . San Francisco: JosseyBass. Hall, C, & Lindzey, G. (1957). Theories of personality . New York: John Wiley £e Sons. Huberman, A., & Miles, M. (1983). Drawing valid meaning from qualitative data: Some techniques of data reduction and display Quality and Quantity , 17 , 281-339. Kerlinger, F. (1973). Foundations of behavioral research (2nd ed.). New York: Holt, Rinehart, and Winston. Loevinger, J. (1976). Ego development: Conceptions and theories . San Francisco: Jossey-Bass. Mezirow, J. (1971). Toward a theory of practice. Adult Education , n, 135-147. Miles, M., & Huberman, A. (1984a). Drawing valid meaning from qualitative data: Toward a shared craft. Educational Researcher , 13^(5), 20-30. Miles, M., & Huberman, A. (1984b). Qualitative data analysis . Beverly Hills: Sage. -180-

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-181Miller, H.L. (1967). Participation of adults in education; A force field analysis . Boston: Boston University, Center for the Study of Liberal Education for Adults. (ERIC Document Reproduction Service No. ED Oil 996) O'Banion, T. (1977). Developing staff potential . San Francisco: Jossey Bass. Parten, M. (1950). Surveys, polls, and samples: Practical procedures New York: Harper. Patton, M. (1980). Qualitative evaluation methods . Beverly Hills: Sage. Rubenson, K. (1977, March). Participation in recurrent education; A research review . Paper presented to national delegates at a meeting on Developments in Recurrent Education, Paris. Tough, A. (1971). The adult's learning projects; A fresh approach to theory and practice in adult learning . Toronto: Ontario Institute for Studies in Education. Tough, A. (1978). Major learning efforts; Recent research and future directions. In K.P. Cross (Ed.), The adult learner: Current issues in higher education (pp. 9-16). Washington, D.C.; American Association for Higher Education. (ERIC Document Reproduction Service No. ED 171 887) Tough, A. (1979). The adult's learning projects: A fresh approach to theory and practice in adult learning (2nd ed.). Austin, Texas; Learning Concepts. Tough, A., Abbey, D., & Orton, L. (1980). Anticipated benefits from learning (preliminary report). Toronto; Ontario Institute for Studies in Education, Department of Adult Education. (ERIC Document Reproduction Service No. ED 201 746)

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BIOGRAPHICAL SKETCH Winifred Buchanan Cooke was born in Harmony, North Carolina, in 1944. She attended Lumberton Senior High School in Lumber ton. North Carolina, and was graduated in 1962. She then attended Evangel College in Springfield, Missouri, and, in 1965, received a Bachelor of Science degree with a major in biology and a minor in chemistry. For five years (1965 through 1970), she taught chemistry and advanced biology at Terry Sanford Senior High in Fayettevil le, North Carolina. The last four of those years she served as coordinator of the chemistry department (four teachers). In 1969 she was awarded a National Science Foundation grant and began work on a master's degree. During the summer of 1969, she took courses in botany from both Duke University and the University of North Carolina at Chapel Hill. She enrolled full-time at the University of North Carolina, Chapel Hill, in 1970. She was awarded a Master of Arts in College Teaching with a major in biology in 1971. She joined the faculty of Southeastern Community College in Whiteville, North Carolina, in January of 1972. Between 1972 and 1982, she taught biology, chemistry for nurses, and student orientation courses at Southeastern. During 1974, she became director of Resources for Student Learning and her role became primarily administrative. During her years as administrator, the programs under -182-

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-183her supervision were awarded several national, state, and private foundation grants. The developmental studies program she directed was recognized in 1976 by the Fund for the Improvement of Postsecondary Education as one of the top 10 exemplary programs in the nation. Other programs under her supervision when she took educational leave in 1982 included a program for advanced students, the on-campus branch of an adult high school and adult basic education program, emergency medical training, all telecommunication courses, and faculty and staff development. Between 1978 and 1981, she took several courses from North Carolina State University in adult and community education. In 1982 she was accepted by the College of Education at the University of Florida to complete work toward a Doctor of Philosophy degree in educational leadership. During this time she served as manager of the Teaching Center under the Office of Instructional Resources. She is married to Charles Lynn Cooke of Lumberton, North Carolina. With their two children, Ryan and Elizabeth, they currently reside in Gainesville, Florida.

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. James L. Wattenbarger , CHairman Professor of Educational/Leadership I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. John M. Nickens v^rofessor of Educational Leadership I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. TTT Albert B. Smith, HI Professor of Educational Leadership This dissertation was submitted to the Graduate Faculty of the College of Education and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. May 1986 Dean, College of Education Dean, Graduate School



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AN I^rv'ESTlGATIGlI OF COGNITIVE STYLE AND CONSERVATION ABILITY IN FIRST-GRADE BOYS By GLEN H0V7ARD REDIEHS DISSERTATION PRESE"NTED TO THE GRADUATE COUNCIL THE UNIVERSITY 0? FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 1973

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ACKNOWLEDGMENTS Many people have helped in the completion of this study. The School Board of Folk County, Florida, Mrs. Genevieve Curry, Principal of Lime Street Elementary School, Lakeland, Florida, and her first-grade teachers and students made it possible to test the sample used. The testing procedure and data collection were completed with the assistance of Mrs. Betty Mason, Professor of Educational Psychology, Florida Southern College, Lakeland, Florida, and nine of her students. Two of the author's students in a child psychology class at Valencia Community College, Orlando, Florida, helped in scoring the tests. A class in cognitive development under Dr. Jacqueline Goldman, Professor of Psychology, the University of Florida, Gainesville, Florida, provided the original idea for the research. The author's committee members assisted in writing the original proposal and in revising the full dissertation. Dr. R. Emile Jester, co-chairman, was particularly understanding and helpful in producing this document. Dr. Irving E. Sigel, Professor of Psychology, State University of New York at Buffalo, permitted the use of the Sigel Cognitive Style Test (SC3T) in this study. He

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provided further information relative to the SCST as it was needed. The help and cooperation of these people is ackncv/ledged and gratefully appreciated by the author of the present study .

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TABLE OF CONTENTS Page ACKNOWLEDGMENTS H LIST OF TABLES V ABSTRACT vi CHAPTER I INTRODUCTION AND REVIEW OF THE LITERATURE , 1 Statement of the Problem. , 1 Review of the Literature 4 Rationale 42 Hypotheses 45 Summary ......... 46 II METHOD AND PROCEDURES 48 Sample 48 Instrumentation 48 Assistants 50 Procedure 51 Data Collection and Analysis, 56 III RESULTS 60 IV DISCUSSION AND CONCLUSION 72 APPENDICES A SCORING CATEGORIES FOR SCST 95 B SIGEL COGNITIVE STYLE TEST ITEM DESCRIPTIONS 101 REFERENCES 102 BIOGRAPHICAL SKETCH 108 iv

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LIST OF TABLES Table Page 1 Conservation of Number Studies ........ 14 2 Conservation of Length Studies 20 3 Conservation of Substance Studies 22 4 Conservation of Weight Studies 25 5 Extraneous Variables in Conservation Studies. 27 6 Stepwise Discriminant Function Analyses ... 63 7 Stepwise Multiple Regression Analysis , , , . 67 8 Means and Standard Deviations 68 v

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Abstract of Dissertation Presented to the Graduate Council of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy AN INVESTIGATION OF COGNITIVE STYLE MJD CONSERVATION ABILITY IN FIRST-GRADE BOYS By Glen Howard Rediehs August, 19 73 Chairman: Dr. William Watson Purkey Co-chairman: Dr. Robert Emile Jester Major Department: Foundations of Education The purpose of this study v;as to investigate the relationship, if any, between cognitive style as measured by the Sigel Cognitive Style Test (SCST) and intellectual m.aturity as measured by success on Piagetian number, length, substance, and weight conservation tasks. Building a rationale on Halford's (1970) model for conservation training and on experiments by Yeatts and Strag (1971), Peters (1970), Garrettson (1969), and Orpet and Myers (1970), this author hypothesized that there would be a relationship among cognitive style preference and/or flexibility and conservation ability. Scores were obtained from 37 first-grade boys for cognitive style preference, flexibility and fluency; conservation ability; Peabody Picture Vocabulary Test (PPVT) IQ; and age in months. Four major categories of style in which the subjects could score were on the SCST: Descriptive partwhole (DPW) , Descriptive-global (DG) , Relational-contextual (RC) and Categorical-inferential (CI) . The four major vi

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categories contained twenty subcategories , These subcategories were indicated by an abbreviation for the major style plus a number (e.g., DPWl, RC4 , etc.). To screen the independent variables , stepwise discriminant function analyses were completed. The variables which demonstrated predictive ability were then used in a stepwise multiple regression analysis. Cognitive style was scored according to initial preference (first response for each item on the SCST) and total preference (total frequency of responses in each style category). Statistically significant results (a=.01) were obtained. Subjects' scores for their initial preference on two independent variables accurately predicted their conservation score (p<.05). Those two variables were cognitive style categories that used comparison between figures {RC4) and age categories (DG5) as the basis for pairing items on the SCST. The best equation (p<.01) used a combination of seven variables. Those variables were cognitive style categories that used comparison between figures (RC4) , age categories (DG5) , common role or attribute (CI 2) , age and sex (DG7) , thematic interaction or interdependent function (RC1&5) , family or other relationship (RC6) and physical attributes (DPWl) as the basis for sorting. The Descriptive part-whole and Categorical-inferential style categories were positively related to conservation scores. Descriptive-global style was negatively related to the dependent variable. vii

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Interpreting these results as they apply to the hypothesized relationship between cognitive style preference and conservation ability was difficult. The research cited in the literature review did not provide an explanation for these results. An explanation of the findings was offered on the basis of the nature of the correlations between the independent and dependent variables and the fact that subjects who scored high on conservation ability tended to use more style categories than the subjects who scored low. This suggested that subjects who obtained higher conservation scores used the Descriptive-global style infrequently and simultaneously enlarged their use of the other style categories. Subjects who scored lower on conservation preferred the Descriptive-global style and exhibited a more limited repertoire of cognitive style. The results gave a clear answer to the hypothesized relationship between cognitive style flexibility and conservation. Flexibility of style, fluency of response, PPVT IQ and age in months did not relate. In summary, this study produced evidence establishing the role of cognitive style in conservation ability — a general expansion in the use of part-whole (analytical) and inferential styles and a decreased use of global style. It did not, though, indicate that one particular style preference related to conservation ability. Nor did it find flexbility of style to relate to conservation. viii

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CHAPTER I INTRODUCTION AND REVIEW OF THE LITERATURE Statement of the Problem Jean Piaget, a Swiss psychologist, has proposed a theory of intellectual development. His theory has described changes in cognitive functioning, as they emerge, one after another, during the life of a child. Many researchers have tried to move children through the stages of intellectual development at an accelerated pace. To do this, they have attempted to discover what abilities or knowledge were necessary for a child to possess in order to proceed from one stage to the next. Then they trained children in those abilities or that knowledge. Most studies that have sought to discover the abilities or knowledge necessary for stage transition have focused on change from the "preoperational" stage to the "operational" stage. Basically, this change is distinguished by a child's emerging ability to make logical or "operational" judgments about problems rather than perceptual or "preoperational" ones. An example of this is found in "conservation" ability, A "conserving" child knows that the amount, weight, length. 1

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2 number, etc. , of an item or set of items remains the same even if the shape of the item is changed or if the set of items is moved around. As long as nothing is added or subtracted, it must, logically, still be the same. A nonconserver is deceived by the change in shape or arrangement and concludes that the amount, weight, length, number, etc., have changed because the item or set of items looks different. The question is, "What helps a child become a conserver?" Despite many experiments which have identified one or another ability or knowledge or a combination of abilites and knowledge, no one has provided a complete answer to the question. Piaget has offered some explanations and other researchers have provided others. The nature of transition from one stage to another and the experiences that help induce conservation ability have remained elusive. Individual differences among children have been shown to have a role in the emergence of operational thought. The present study was designed to determine the degree of relationship, if any, between cognitive style and conservation ability. "Cognitive style" has been used to refer to the manner in which children have perceived the elements of a stimulus or problem. In some cases children have concentrated on the details of the stimulus or problem. In other cases, children perceived things as a whole. Or, they may have seen the relationships between the elements in the stimulus or problem. There have been a number of ways of 1

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3 describing and measuring cognitive style. Some examples have been Kagan's Analytical — Non-analytical {or Relational) (Kagan, Rosman, Day, Albert and Phillips, 1964); Witkin • s Field-dependent — Field-independent (Witkin, Dyk, Faterson, Goodenough and Karp, 1962); and Sigel's Descriptive, Relational and Inferential dimensions (Sigel, Jarman and Hanesian, 1967) . On the basis of research evidence, there was reason to believe that individual differences in cognitive style affected the ability to acquire conservation ability and an operational level of thought (Garrettson, 1969; Orpet and Myers, 1970; and Peters, 1970). The purpose of this study was to investigate the relationship, if any, between preference and flexibility of cognitive style as measured by the Sigel Cognitive Style Test (SCST) and intellectual maturity as measured by a compos j.te score on number, length, substance, and weight conservation ability. If such a relationship could be shown, this would contribute to a better understanding of antecedents to conservation ability and the nature of the child's transition to conservation ability. Such knowledge could aid in the development cf learning situations designed to induce conservation ability and promote overall intellectual functioning as Piaget has described it (Piaget, 1966).

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4 Review of t he Literature There are five portions to the review of the literature. First, conservation is briefly explained. Research dealing with the same question as the present study, "What helps a child become a conserver?" is then cited. Theoretical models and experimental methods of training for conservation are included in this research. The models and the methods have identified factors that researchers claim have helped children become conservers. Cognitive style is explained in the next section. Finally, literature linking cognitive style and conservation is reviewed. This last portion of the literature review concerns those experiments that are most important for the rationale behind the hypotheses of the present study, : , There are, therefore, five sections to the literature review: (a) a brief summary of Piaget's theory as it relates to conservation, (b) short explanations of ten theoretical models that have attem.pted to account for transition between Piaget's stages, (c) studies of attem.pts to train conservation, (d) theories and studies of cognitive style, and (e) literature linking cognitive style and conservation, Piaget's Theory as it Relates to Conservation Intelligence has been described by Piaget as being dependent on the process of growing by interacting with the environment (Piaget, 1966) . Intellectual growth has been

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5 set forth by the same theorist as a number of stages through V7hich a child must necessarily and sequentially pass. Each stage has been characterized by an organized set of ways in which a child interacts with the environment, Piaget has identified ten such stages children encounter between birth and sixteen years of age. These stages have been conceptualized as the smaller steps within three larger periods: (a) Sensorimotor Period (birth to 2 years) , (b) Preoperational Period (2 to 7 years) , and (c) Operational Period (7 to 16 years) . The present study was concerned with the movement of the child from the Preoperational Period to the Operational Period. Piaget has maintained that the ability to conserve was evidence that a child was moving into the Operational Period. Conservation ability has not appeared in an all or none fashion; it has emerged gradually. Children have demonstrated partial and vacillating success befo?-e they exhibited consistently correct conservation judgments.^ -. Piaget has shown that at about seven years of age the average child is capable of keeping track of two characteristics of an item or a set of items simultaneously while those characteristics are changed. As a result of this ability, a child can recognize that a given property of an item or a set of items, such as mass or number, remains the same, or is "conserved," even though it is reshaped or moved. The same principle applies to conservation of number, )

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'"V6 length, height, substance, weight, volume, density, etc. — some of which appear later than others in the child's life. Conservation of substance, for example, indicates the ability to see the equality of mass between two equal substances, such as two balls of Play-Doh, even after the shape of one has been altered. In conservation of substance, a conserving child can see that changes in one dimension, such as height, of an item are offset by compensating changes in another dimension, such as width. Conservation of weight would assert a like equality, this time of weight, in spite of other changes in the object, A number conserver iden-tifies equality in the nxamber of items in two initially equal sets, such as two rows of pennies, despite changes in their arrangement. This same principle applies through all kinds of conservation. In a typical test for conservation, the experimenter establishes, to the satisfaction of the subject, initial t.^.equivalence of substance, weight, number, etc., between two items or sets of items, transforms one of them, and then asks if the transformed item or set is "more," "less," or "the same" as the nontransf ormed item or set of items. A conserver would assert that they are still "the same" and offer a logical reason for his judgment. A logical reason would be, "because you didn't add or subtract , anything, 'L.-or "I could make it back like it was before," .. .

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7 Ten Theoretical Models of Conservation Researchers have proposed at least ten theoretical models attempting to account for transition between Piaget's stages, i. e. , what variables help a child acquire conservation ability. All have had some theoretical reasoning and some empirical evidence behind them. None has proven itself as the only correct explanation. The ten theoretical models reviewed are: (a) Piagetian, (b) cognitive conflict, (c) operational reversibility, (d) computer analogue, (e) information processing, (f) S-R, (g) social learning, (h) learning set, (i) semantic, and (j) cue constraint. The first nine models are explained briefly. The last, "cue constraint," is dealt with more thoroughly since it was important for the rationale behind the hypotheses of the present study, Piaget has named four factors that combine to account for the movement from one stage to the next: (a) maturation, (b) physical experience, (c) social experience, and (d) equilibration (Ginsberg and Opper, 1969), Equilibration has been Piaget's prime explanation of stage transition. Equilibration refers to an ongoing, cyclical process of intellectual balance and imbalance which a grov/ing child experiences. As he interacts with his environment, new experiences throw him into cognitive "imbalance." This imbalance requires him to change in order to comprehend and handle the new situation and return to a state of cognitive

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8 balance. Despite the different environment each child experiences, his interaction with its novelty forces the equilibration process into action and propels him along, from one stage to the next in Piaget's theory, in a predictable fashion. Two other models, "cognitive conflict" and "operational reversibility," have had similarities to Piaget's model. Smedslund's (1961a) "cognitive conflict" model was built on the Piagetian model. A subject was presented with conservation trials in which it was possible for him to see a change in both shape and arrangement and also subtraction or addition of some of the material. He had to decide whether he would use perceptual cues , the change in shape or arrangement; or logical cues, the fact that some material was taken away or added, as the basis for his conservation judgment. Smedslund claimed this conflict created the cognitive imbalance that fosters the equilibration process and intellectual growth. The "operational reversibility" model also uses a Piagetian concept. Brainerd and Allen (1971) asserted that the one common feature in successful attempts to train children to conserve was repeated exposure to "object-bound reversibility. This is a Piagetian term that refers to the realization that if one changes an object, such as the shape of a piece of Play-Doh, it can be restored or reversed to what it was before.

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9 The remaining seven models for conservation acquisition do not have any unifying themes around which to group them and are simply other ways of explaining what it is that helps children acquire the ability to conserve, i. e., other ways to answer the question the present study seeks to answer. Klahr and Wallace (1970) described learning to conserve as similar to programming a computer. The visual and verbal data the child receives from a conservation task are supposedly encoded, a computer-like routine constructed in the mind, and the program then executed, Bruner (1964) viewed the ability to conserve as the result of growth in techniques of information processing in which language was the key. The use of language to make sense out of experience, that is, to process the information one gets from experience, enables the child to conserve. He is less dominated by perceptual cues and more able to use symbolic or logical processes as a result of this use of language. In one theory it has been claimed that there are three steps in a typical conservation task: (a) initial equivalence between two items or sets of items, (b) a change in one item or set of items, and (c) a comparison between the two items or sets of items. An S-R analysis (Sigel and Hooper, 1968) considered these three steps to be three stimuli. The second step was the important one. If nothing

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10 was added or taken away from the items during the change step, step (b) , then that was the cue, or the discriminative stimulus, for the answer "the same" when the experimenter asked the subject whether the two items or sets of items were still the same or not. If the second step included addition and/or subtraction of material from the items , then that was the cue for a "more" or "less" response to the experimenter's question. Waghorn and Sullivan (1970) found that their originally nonconserving subjects began to exhibit conservation ability as a result of viewing a film in which an experimenter and subject modeled conservation ability. They considered this support for a social-learning theory of the acquisition of conservation. Kingsley and Hall (1967) and Rothenberg and Orost (1969) concluded that conservation ability was dependent on mastery of a sequence of component abilities. Each of these had to be learned, one after another, to a criterion level of performance. A "semantic model" for conservation has been advanced by Braine and Shanks (1965) . They pointed out that when an experimenter tests for conservation, the child has to produce the correct verbal response in order to be considered a conserver. An understanding of conservation is in the child's mind before it shows up in a test for conservation, according to Braine and Shanks, and all that a typical

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11 conservation task shows is whether the child has learned adult definitions for such words as "same," "more," "less," etc. The last of the conservation models described here is labeled "cue constraint." Halford (1970b) examined the equilibration and learning theory explanations for the acquisition of conservation and decided the truth was somewhere in-between. For him, conservation ability was partly the result of using the right cues. Using the right cues focuses on discrimination between stimuli and is consistent with a learning theory position. But, in consonance with equilibration, he proposed that there must also be "constraint" between the available cues. For instance, there must be constraint between quantity, height, and breadth in a conservation of substance task; or between the number of items and the spacing of items in a conservation of number task. The ability to conserve rests on the use of ' all cues in "truth table" fashion and in noting their com" pensatory relationships. One of the hypotheses of the present study anticipated a relationship between flexibility of cognitive style and conservation ability. Part of the rationale for this hypothesis came from Halford's "cue constraint" model." ' 'If a child could see both the details in~the' items of a conservation task, which was characteristic of one type of cognitive style, and also the whole or relationships between the items

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12 in a conservation task, which was characteristic of another type of cognitive style, thus demonstrating flexibility of cognitive style, he should have recognized the constraint between cues more easily and demonstrated conservation ability more readily. The models reviewed above have all attempted to explain how a child grov/s from a nonconserver to a conserver. Since all of the models have a theoretical basis and some empirical evidence, the search for a single variable which helps a child attain conservation ability was very difficult. Since there was reason to believe the cognitive style preference or flexibility a child used may have helped him become a conserver (Halford, 1970b) , the present study sought to find those relationships. Studies of Attempts to Train Conservation In the statement of the problem, it was mentioned that many researchers have tried to move children through the Piagetian styles of development at an accelerated pace. The training programs they designed to make conservers out of nonconservers all shared the concern of the present study: "What is it about the individual differences among children, or the different experiences they have, that predisposes them to move from preoperational to operational thought?" In order to cite some answers thar have been offered to this question, literature describing studies of attempts to train conservation are reviewed here. The review has five

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13 parts: comments on successful and unsuccessful methods used to train children in the four types of conservation tasks used in this study (n\mber, length, substance and weight) and, last, a summary of other variables (e.g., IQ, socioeconomic class, conservation task complexity) that make a difference in whether a child can demonstrate conservation ability. In each of the first four sections, the reader is referred to the appropriate table which summarizes the methods used and the success or failure they produced. The review briefly explains each of the training methods that appears in the tables. , Studies dealing wi t h conservation of number Various training methods used in an attempt to foster the acquisition of conservation of number are summarized in Table 1. The effectiveness of thirteen different training procedures was explored in the studies reviewed here. These methods were tabulated according to success or failure and briefly defined in the following review. The objective of reversibility training was to get the subject to realize that a transformation could be reversed. For example, a lengthened row of pennies that appeared to have more pennies could be shortened again to show one-toone equivalence with the standard, nontrans formed, comparison row. Halford and Fullerton (1970) designed a procedure which has been labeled "cue constraint." In the training sessions,

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14 0) u H n3 m 0) o u to o Q) c < c3 to IS -P P O ^ ru ^ U (0 VO o CN CO vO er M , 1 VI/ •s< ni /II rr\ OA in 0 a^ 1-^ rH in C iH VO H oa IS ni vL' rH rH rH tn , 1 ^ ^ riH -H O VO c; i> i> tO — 1 ( — 1 rH M r* r* rH — ' r-l n n trt » S « in 0 m fn VO 3 in rH a> W VO — l3 rH OA a) rH rH rH rH rH 5^ C o •r^ -rH C a) •H C C x: rH (3 0) rH rH rH -p 4-> 3 0 0) to M 0 0 CO S IS CN VO 0) o t9 •H x: in VO c 0) M O VO >1 •H 0) -P CO rH 0) e M 0) s VO 0) >. (U in G VD •H •H tcS U 4J CO c O o a> U to •H -P •H ;^ 4-1 d Q) c o g O U c o •H -p u u -p CO C H 0) rH to U > \ <1) -P u C -H 0) -P e u a; to u n o m TJ c 0) •H U QJ Jh O m +J c U -r^ U D3 •H Q O •H P U to u +J X! 3 O H -P H n p c e O o ip G H to > I c 0 2 T3 lO Q) rH CO CO •H Q) S 3 u >p O rH to OJ 3 CO +J D a, (U 0) o (0 a; U 04 3 O u c: CO -H •H Q u •H iH IH c o u > •H -P -H C CP o u c o •H +J fO o •H MH •H CO CO to rH u 0) rH •H -p rH 3 2 G 0 •H J-> (0 > •H -P U < Q) cn to 3 Cn C to C 0 •r^ to +j G •r^ M o to Si u (1) > G O •H P to u XI •H iH •H 3 to o H •P CO H crtio 4J CO a) -p H CN in 00 CT> CN O rH *

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15 a subject was repeatedly asked to select from several rows of items of varying lengths the one row that had the same number of items as a standard row — despite the fact that it wasn't necessarily the same length as the standard row. This method was supposed to lead a child to recognize that length of the rov; and spacing of the items were the important facts and that they had a compensatory relationship. Component abilities refers to a sequence of probable steps or component skills that Rothenberg and Orost (1969) considered the antecedents to conservation. The component abilities necessary for number conservation were: (a) rote counting, (b) counting attached to objects, (c) "same" number, (d) the "sam.e" versus "more" distinction in terms of number, (e) addition and subtraction, representing a change in number, (f) one-to-one correspondence, (g) reversibility, and (h) the distinction of "more," referring to the actual number of objects, versus "longer," referring to their arrangement in space. Each of these abilities was learned, in sequence, to a criterion level of performance. At that point, conservation ability was supposed to emerge as a result of the mastery of the prior skills. Verbal rule instruction indicates that the subject was orally told the logical reason for a conserving response during the training procedure. He was then expected to learn it and apply it correctly.

PAGE 24

16 Direct reinforcement consisted of the subject counting the two sets of items immediately after the conservation judgment to see if his prediction of the two rows being "the same" or one row "more" or "less" was correct. Success of this method was viewed as support for a learning theory model of conservation acquisition. In the addition-subtraction procedure, one or more items were added or subtracted after initial equivalence was established between two rows of items and before one set of items was rearranged. The subject was to recognize the addition or subtraction as the important cue in making his conservation judgment. Beilin (1965) used a non-verbal reinforcement procedure when presenting subjects with a traditional number conservation task. A correct, conserving response produced a buzzer and red token as reinforcement. An incorrect response yielded neither buzzer nor tokeii^^ J ^: c. -i;.rWohlwill and Lowe (1962) trained subjects to pay attention to the number cue, the number of items, instead of the length cue , the length of the array . This supposedly . led to a better basis for conservation judgments and has been labeled "discourage use of misleading perceptual cues," Smedslund's cognitive conflict procedure required that in at least -some of a series of conservation tasks, the transformation of one set of items included rearrangement of the items and addition-subtraction of some items. The subject had to choose between a perceptual or a logical basis

PAGE 25

17 for his conservation judgment; he had to decide if the two sets of items were still the same or not because of the way they looked or because of the addition or subtraction of items (Gruen, 1965). Multiple classification has been shown to be a prerequisite to conservation according to Piaget. This training procedure consisted of a series of sessions in which subjects were trained to identify multiple attributes of various objects, that is, multiple ways in which objects were the same and different. With this prerequisite further developed, the child was supposedly more likely to demonstrate conservation ability. The language activation procedure was modeled on Bruner's (1964) theory. This method focused on the linguistic aspect of the conservation test situation — hopefully decreasing the child's reliance on deceptive perceptual cues. In the verbal orientation reinforcement, the subject was told the number concept in the instructions so that he would be verbally oriented to the relevant attribute. The subjects in this procedure were also reinforced with a token for a correct response. Beilin (1965) attempted to imitate the equilibration procedure Smedslund (1961a) used to train weight conservation. The spatial arrangement of the items in Beilin *s (1965) equilibration method underwent transformation without the addition or subtraction of items , This was supposed to

PAGE 26

produce "cognitive uncertainty," which then forced internal reorganization of schemata and resulted in new cognitive certainty or equilibrivm and, as a result, number conservation ability. Mermelstein and Meyer (1969) attempted to replicate the training methodologies of cognitive conflict (Smedslund, 1961d) , verbal rule instruction (Beilin, 1965), language activation (Bruner, 1964) and multiple classification (Sigel, Roeper and Hooper, 1966) and test for conservation along more rigid criteria. The results were, as the authors predicted, nonsignificant. Some reviewers (Brainerd and Allen, 1971) have faulted Mermelstein and Meyer for imprecise replication and 'loaded' procedures. Three of the replicated procedures were not developed originally to induce n\amber conservation, but rather substance conservation. The results of the experiments designed to induce number conservation did not provide a clear answer to the question the present study posed. Some of the methods revolved around Piagetian notions. Reversibility and cognitive conflict, for example, were successful, but multiple classification and equilibration were not. Additionsubtraction results were ambiguous. Other procedures used reinforcement. Non-verbal reinforcement failed and the results for direct reinforcement were equivocal. Three methodologies focused on verbal help or language activation, They were mostly unsuccessful.

PAGE 27

19 What is it that helps a child acquire niimber conservation ability? The results of literature reviewed here, although not exhaustive of all the pertinent studies, indicated no final answer. Not all the children in any one study cited in the review were helped. The nature of the transition from nonconservation of number to conservation of number and the specific antecedents to this ability remained elusive. Studies dealing with conservation of length A number of training methods used in an attempt to foster the acquisition of conservation of length are summarized in Table 2. These methods were tabulated according to success or failure. No methodologies were attempted in this review of conservation of length studies that were not explained in the review of studies dealing with conservation of nxunber. One of the observations Smedslund (1963) made is interesting.. After viewing the results of an experiment, he concluded that different children seemed helped by one or another of the several variations of the cognitive conflict procedures he used. Perhaps behind the inconsistencies and ambiguities of the research literature is that basic principle: different experiences help different children. Murray jl968) obtained statistically significant results with his reversibility training method. But, he used highly specific

PAGE 28

in in in 1 rH 0) d >1 rH iH c W -H C U] a) cn rH 0) T3 •H d -i r-l rH rl 4J •H (1) •H -H -H -P (0 (fl ro o XI -P 4J C « > O 0 VH •H -H (fl (U •H u l+H Eh 0 CQ d d c rH -P H c •H m >-i Cn -P 0 (fl H (fl -H rH C dJ 0 -H Xi C 1 ja •H •H > U CO g u Cn c ^H d a; 0) 0 0 0 u > U > w E 0) r-l in 00 It

PAGE 29

21 task-related training procedures, and one might have doubts about transfer to length tasks with less similar materials. As with the conservation of number studies cited in the previous section, those concerned with length were inconclusive. Success was more prevalent, but all children still were not helped by any one method. The abilities or knowledge necessary for conservation ability defied reduction to a simple item or combination of items. Studies dealing with conservation of substance A number of training methods used in an attempt to foster the acquisition of conservation of substance are summarized in Table 3. Two new methodologies that were not explained so far were introduced in this review of conservation of substance studies. The first was Waghorn and Sullivan's (1970) film-mediated model. Nonconservers , who watched a model successfully conserve in a filmed sequence, began conserving. This result was cited as evidence for the role of social learning in conservation acquisition. Fleischmann et al . (1966) compared two variations of a traditional conservation task and a third group which received verbal feedback concerning the correctness of their conservation judgment. The feedback group improved significantly better than the traditional groups. The manner in which the "cue constraint" method was applied to substance conservation demands explanation.

PAGE 30

22 0) u H •H (i4 O t3 o C tP i« nS M S Q) mom 0 Vi C k Q) a -P rH m m 0) u o in u 0) o o a V^ (U ft QJ O •H W -IJ m •H -P cu 03 pa o > •H iH iH W c o x: (0 12 0) X! W C •H o (0 o O X! o (0 in en QJ u o * o C rH m QJ CO * 13 C d m OJ g O x: -p QJ s on C •1-1 C •H (S M £-> QJ O •H +J O (0 u QJ O U O 4-1 C -H QJ P5 -P g d S QJ -P r-l -H a-H QJ -H •<-{ rH +J XI CUrH -H -H d m u QJ > C QJ O M -H m +j QJ nj -pom iH -H Cn 4H •H -H d m -P Cj' m (d QJ (B rH k rH QJ QJ O k Vi 04 O •rl O >i •H -P -P -H fd rH QJ O -H rH -H XI rj -rH m m QJ d m g rH ^ o m ^ Q/ m -P o tn d rl X! 4-^ (d •rl U d -H tj)H QJ -P 4J QJ QJ (« m Sh QJ 4J 03 •r( TJ QJ I -H O XI -d Q) Q) fa 03 X! U QJ > P C r-i 03 n p m o u QJ d u o •H rH IP c o u QJ > •H -P -H c O U C O •H +J O 03 U P X3 d in o •H +> I a, 0) o 0) cu 4H o O QJ •H d m u m QJ H M 03 ft d ft-p d w g Q) -P in U3 00

PAGE 31

Halford (1969, 1970a, 1970b) believed that acquisition of conservation was not the result of one or another method. He developed the notion that a child must develop a "mental truth table" which guided his judgment according to all the possible combinations of "equal," "more," and "less" cues from quantity, height, and breadth dimensions jointly considered. His training procedures were designed simply to expose the child to many such combinations under the highest possible level of incentive. The three experiments cited here involved numerous opportunities for classifying containers requiring judgments about the combinations of the several dimensions involved. Sometimes significant and always positive results were found. It seemed that merely exposing a subject to experiences which involved compensation of height, breadth, and quantity cues and their joint constraint on each other promoted the acquisition of quantity conservation quite independently of any of the training procedures painstakingly developed to reflect Piagetian,' learning theory, or other theoretical positions. In addition to the three methodologies described above, Brison (1966) used a "no method" method. Instead of designing a training procedure which had its base in some theory, he focused on accelerating conservation itself. Nonconservers were given two days of training in which the subjects were simply presented with conservation of liquid situations in which they chose which of two deform.ed ~

PAGE 32

24 quantities of juice they wanted, A significant difference between experimental and control groups was found. An impression of a high rate of success of the substance conservation training procedures is given in Table 3. However, when it is noted that Smedslund (1961e) reported no statistical analyses and Sigel, Roeper and Hooper (1966) based their conclusions on trends and one brief statistical test, the evidence is not so clear. Success was mixed and the basic question of what it is that helps children conserve still did not have a clear, universally applicable answer. The manner of transition between stages and the antecedents to such intellectual growth were not revealed by these studies. Studies dealing with conservation of weight Several training procedures which have been used in an attempt to foster the acquisition of conservation of weight are summarized in Table 4. One method found in Table 4 , which was not mentioned previously, was labeled "empirical controls," This meant that the subject could observe the objects used in the task on a scale following his conservation or nonconservation prediction. Such a procedure was identical to what Smedslund and others called "direct reinforcement" elsewhere. Tv70 of the procedures reviewed here involved combination methods. One v;as successful (Overbeck and Schwartz, 1970) and one showed only positive trends (Smedslund, 1959) ,

PAGE 33

0) rH Xi EH to a) •H -p tn -p Cn •H 0) & o c o •H +J > U 0 CO c 0 u o H N +) V4 , ^ Id O -« rH r— 1 VO •H u (T( »U (0 rH «« 13 G O 0) rH ^ to 0) > g o CO ^ ttJ rH N a\ 4J cH iH * u * to rH iH (0 IT) in 1^ a) o to a\ as o t/3 rH iH rH u t^j * 73 >i G G G u o 0) 0 XI 3 0) r>rH H rH rH rH CO to VO to to n G rH CD > •H g 6 g o CO CO to to 0 G CO to 0 1 G •H d \ rH 4-> 0 V CJ 4J CO H •H o 0) M CO C >H (tJ 4J +J rH x; O -P (1) (1) 0 to V-l o •H CO •H e M H 4J (0 (0 d Q) -P c 4J Q) -P 0 X} O H r-l o c sh d 4J Cu (tJ rH M 0 -P CO XI (!) 0) &| >-l (U r-l 0 u G > u (2 lii 1— 1 0 1 to •H •H < G iH u 4J fl H (0 c 1 O •H (1) •P OJ U H 0 < <0 O rH c « -H (T5 -H G G to Q) U -P O -P 0 to 0 X! C -P -H •H -H •H U -H 0) 0 u a 4J (1) 4J Sh C d) CU •H ^3 •H •i — I (tJ Qj •H > g t3 XI Qi Dj 0) 0 -H g d u Q < CO CO e 0) CM m in 1 H

PAGE 34

26 Another method not discussed previously in this review was "subject active participation." The experimenters who used this method, Overbeck and Schwartz (1970) , hypothesized that the personal involvement of the subject in the transformation of the material used in the task was important. The results were nonsignificant. There were still no clear answers emerging from the literature. Considering the number of studies that reported only trends, success at training for acquisition of conservation was mixed and evidence for the antecedents to or nature of transition to weight conservation was equivocal. Literature identifying extraneous variables The problem with the conservation training studies reviewed above is that the results did not reveal how one acquired conservation. The mechanism of transition from preoperational to operational functioning was rot exposed. One way to eliminate those elements that hide the essential one(s) is to control as much extraneous variance as possible by experimental design and statistical procedure. Such variables investigated in the research reviewed for the present study are specified in Table 5. The variables that were found to have a significant effect on measured conservation ability were of two sorts. Some were related to the condition of the subject (intelligence, socioeconomic class, age, vocabulary score and grade) , Others were related to variations in training procedure

PAGE 35

27 CO (U •H 'O :3 -P w c o •H -p > m C O U C •H w Q) iH XI (0 •H (0 > W 3 O 0) c (T3 -P •p o 1 > c (0 rH (1) rH >H rH u 0 ^H 0 d c , — 0 o O o •H u JJ cn o^ rH rH rH m > — ' in Jh W Q) C C r03 (d > > cn a\ 0 o •H •H •H rH rH rH rH U rH rH rH 00 " — D rH rH rH -H >H rH 3 3 a\ Tl m 0) CO W rH •H •H -H H •H XI g 6 6 rH t3 l8 x: x: cn rH o 0 0 U •H 0) Vh !h CO w CO CO CO 1 •H 4J ^ ffl •H to H +J a •H (d rH >i X! >i U -P fd 0) p ^H rl u rH •P •H u fd rH •rl •H c 0 O 0 tT> 3 3 rH M u (d rH rH rH 0 fd fd 3 3 3 a; 1— •rl P -P u cn e -p (0 u 0) c CO C -H •rl •rl (d 0 cu o H fd -P >J H Eh CO s S H CO CO e a; rH CN n IT) CO o rH (N rH rH rH

PAGE 36

28 +> o (U m M Q) 4J •H c -H Q) a 4J (« O •H »W •H C -H W O CO vo 00 00 H in VD vo iH rH Tl rH C >i >1 (H nJ M 0) U u TJ U U Q) g s; CO c 0 Ci H 0 4J P •H (0 O u -P > u m > rH >w S-l cn w CD C CO y5 vo 0 c C (Ti a> cr» u H c 0 rH rH rH rH C C x: w j3 Cn 0) >1 u 0 o o O •H (0 m CO m ID d nJ •t3 •d 'd •d CO w U rH rH rH rH •H 0 0 o 0 0) o a o o cn O •H C rH o Xi O CO >^ N -P u o CO o o •H c rH o x: o CO N -P u I o CO 0) rH rcJ H M > 0) -d vh CJ 0) -p c a) u 0) u G c •H * QJ 0 a) C H •H c •p 0 (0 -p 0 G CO > u •H 0 •H -H (d 4J di o •P 5h 3 >1 (fl c G (0 u -P +J +J •H >W 05 G rH -P 0 g g rH X! 0) 3 +J cr> 0 3 3 (0 o 0) >H fd 0 CO X> CO (U •H CO (U 3 >i QJ «J 1 u (0 IW -p -P -P -P O G P IH m Qj U -H (C 0 0 •H D -H 3 g i+H QJ +J g > •H rH D H (0 0 U C-ri +J -H "i CO H CO Eh g QJ -P H (N in 1^ CM CO

PAGE 37

4J D d) M-l M-t vo W vo vo a\ (U iH r-l 4J H f5 V4 vo vo •H Q) (1) VO vo M-l ft ft o^ <3\ (L) 0 rH rH n o c S » ^ ^ CO c vo 0 o CTi *-< ^ rH vo -P (0 OS (U (1) o> 0) o QJ r\ \y ft rH CQ PQ •H — Q) (U M-l 0 0 rH O Ct< o5 OJ c 4J +J IS (Jl U) > CO 0 >1 0 • rH -ri rH rH dJ •H (0 C! 0) -t-) (U 0) &> 4J -d >-* (jl (U ft 0 o 0 (0 -H •H •H n3 0 o ffl W W CQ u CJ ^ ^ ^ o o cs 0 4J r-l rH •H JJ Q) M-l > M-l ^ ^ (ij • — ^ ^ — ^ ^ — V W rr~ > n n r~ > 0 1^ •r| vo VD vo vo -H CO vo vo 4J a^ rH CTi C3^ 0> (Tl rH c c i-H H r->i T-\ r-{ rH rH H 0 rH rH (0 o VO W CO •H g S C •H A o -> — ' Q) 0 QJ £> H q; s rH Q) (0 ft M -P < O 1 c to c; (0 •H 0 •H •rl •5, W rj rH rH rH rH 0 (0 0 05 O Cu 4J CJ 0 0 e G W2 G) CO X x; c; •H 0 0) 1-1 a (0 (U u -P u 2 IS < H Eh CO CO <: CO CO e (1) in 00 o H rH n It rH rH

PAGE 38

30 (high interest materials, task complexity, mental set, item difficulty, stimulus setting and type of judgment required) , The factors that covaried with conservation helped provide insight into the characteristics of a conserving child and the type of procedures that made a difference. Summary of conservation studies All the methods of training for conservation of number, length, substance and weight that have been reviewed shared the basic problem of the present study, "What is it that helps a nonconserving child to grow intellectually so that he can demonstrate an understanding of conservation?" It is apparent that there is no simple answer. Smedslund must have had part of the answer when he observed that different procedures helped different children. The search for extraneous variables turned up a number of factors relating to the condition of the child. Taking a cue from these thoughts which suggested that it was unique characterisitcs of the child that predisposed him to acquisition of conservation ability, the present study focused on one of these characteristics: cognitive style. Theories and Studies of Cognitive Style Neither the theoretical models for conservation nor the results of the experiments that have tried to train children to conserve have clearly answered the question, "What is it that helps a child become a conserver?" The author of the

PAGE 39

31 present study hypothesized that the individual differences between children contribute substantially to the facilitation or inhibition of conservation acquisition. Much of the answer to the basic question of the current study, therefore, lay in identifying further characteristics of children that correlated with conservation ability. The dimension chosen for investigation was cognitive style. Cognitive style has been used to refer to one way in which researchers have measured individual differences. Basically, measuring cognitive style has been an attempt to find characteristic, consistent ways that people have used in dealing with stimuli in their experience. There have been two main theoretical positions regarding cognitive style that have dominated the recent literature. One has been Field-dependence — Field-independence developed by Witkin and his associates and the other has been Analytic — Non-analytic (or Relational), researched by Kagan and his associates, V7itkin and his associates (Witkin, Dyk, Faterson, Goodenough, and Karp, 1962) defined a Field-dependent person as one who finds it difficult to overcome the influence of the field surrounding an item or to separate an item from its context. When viewing stimuli or a problem this person prefers to see it as a related whole. Field-independent subjects, on the other hand, are able to distinguish an item.— -" from its context. These subjects can handle the parts of stimuli or a problem independently from its context,

PAGE 40

32 Cognitive style has been shov,'n to influence perception of people and events in everyday experience, experience of one's self and body concept, ego defense structures, reading ability (Wineman, 1971) and other variables. Kagan and his associates and other researchers developed a second main theoretical position. This position described two dimensions of cognitive style: (a) Analytic — Nonanalytic and (b) Reflective — Impulsive, Since the SCST, which was used in the experimental portion of the present study, measures cognitive style according to the dimension established by this school of thought, the review is more extensive. Kagan and his associates (Kagan, Moss and Sigel, 1963) began by noting that v/hen adults were asked to sort figures on the basis of some common feature, they sorted in consistently different ways. Different subjects individually preferred using one of three bases for sorting the way they did: (a) Analytic-descriptive (similarity of visible, objective elements) , (b) Inferential-categorical (categories made on the basis of inferred characteristics of the stimuli) , and (c) Relational (functional or them.atic interdependence between elements in a grouping) . After working with these categories, the Inferential-categorical was not found to discriminate among subjects reliably and it was de^emphasized. The major dimension researched by Kagan has been an Analytic — Nonanalytic (Relational) one.

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33 Of Kagan's style measures, the Cognitive Style Test (CST) has been the most v/idely used with children. This test involved the presentation of 30 (originally 44) cards with three figures drawn on each card. The subject was requested to pick two of them that were alike or went together in some way. The subject revealed his cognitive style preference by telling the examiner why he thought the two he selected were alike or went together. If, for instance, a child was shown pictures of a chair, lamp and table, he might have said the chair and table went together because they both had four legs. This would have been an analytic response since he was considering visible, objective parts of the stimuli. If he said the lamp and the table went together because a lamp was always set on a table, that would have been a relational sort. He was placing them together because of their relationship to one another. Bases for analytical and relational style were available on all cards. A great many personality variables were found to be associated with the Analytic — ^Non-analytic dimension (Kagan and Moss, 1962; Kagan, Moss and Sigel, 1963; Kagan, Rosman, Day, Albert and Phillips, 1S64; Lee, Kagan and Rabson, 1963; Sigel, Jarman and Hanesian, 1967). Highly analytic children were persistent in problems, confident about challenging intellectual tasks, motivated for achievement-related goals, reflective, able to differentiate details of experience, able to resist the effects of distracting stimuli, less

PAGE 42

34 "malleable" in their behavior and more able to form analytic concepts. They produced more word associations homologous by part of speech in a word association test, they mentioned objective parts of stimuli in the Thematic Apperception Test (TAT) before offering any thematic responses, and their style scores correlated with nonverbal subscores on the California Test of Mental Maturity (CTMM) . Non-analytic (Relational) children were anxious in new social situations, expecting peer and adult rejection, impulsive, more reactive to external stimuli, less likely to differentiate complex stimulus situations, impulsively aggressive, not easily withdrawn from a group to work on a task, and hyperkinetic. Significant sex (Sigel, 1965) and age variations in the data have been demonstrated. Boys generally have been more analytic than girls and have produced higher correlations between analytic style and the characteristics related to cognitive style. In retesting subjects a year after----initial tests on the CST and on other variables, the results were more stable for girls than for boys. This finding plus the evidence that IQ for the sixto ten-year age span has been more stable for girls than for boys has led some investigators to conclude that cognitive organization is fixed earlier in girls. The relationship between "Ana lytic--Nonanalytic style and age has been shown to be linear. The-*-^' older the subject, the more analytically he performed. In the lower elementary grades, boys' increase in analytic responses has been found to be faster than girls ' ,

PAGE 43

35 Kagan and his associates also investigated the Reflectivity — Impulsivity dimension which has been seen as parallel in many ways to their Analytic — Non-analytic style (Kagan, Rosman, Day, Albert and Phillips, 1964; Kagan, Pearson and Welch, 1966; Schwebel and Bernstein, 1970; Messer, 1970; Drake, 1970; and Milgram, 1970), To summarize, Kagan and his associates have demonstrated the existence of cognitive style along the Analytic--Nonanalytic (Relational) dimension. These predispositions were demonstrated to generalize to various personality characteristics and other areas of performance. The Reflectivity — Impulsivity dimension paralleled the Analytic — Non-analytic one. Analytic — Non-analytic cognitive style appeared relatively stable over time but was subject to the influence of age and sex. Before leaving this discussion of Kagan and the Analytic — Non-analytic dimension, one important experiment (Yeatts and Strag, 1971) is here reviewed in detail. The study is important because it challenged the unidimensionality of cognitive style and supplied the basis for the hypothesis regarding flexibility of style which was investigated in the present study. The study investigated the relationship between an individual's ability to behave flexibly, that is, to shift cognitive style, and his academic achievement. One hundred and twenty-one fourthand sixth-grade students were tested

PAGE 44

36 on Kagan's CST and the California Achievement Test (CAT), The only difference from standard procedure was in Kagan's CST. The subject was given 45 seconds on each of nineteen test items and instructed to arrange the materials in as many ways as he was able. In scoring this test, the subject's first answer identified his cognitive style preference. He was also given a flexibility score according to the number of times he changed his cognitive style in the successive classifications. The results indicated that regardless of cognitive style preference or grade level, flexible subjects performed at a higher level of achievement. Furthermore, of the 31 subjects who were scored inflexible, 25 were at least six months below grade level, 6 at grade level and none above. Review of Literature Linking Conservation and Cognitive Style This section of the review of the literature again begins with the question, "What is it that helps a child to acquire conservation ability?" Ten theoretical models for conservation were cited to see what answers they offered and research attempting to train children to conserve was reviewed in hopes that they could identify experiences or individual differences that facilitated transition from, nonconservation to conservation. Experiences or individual •differences that could explain the appearance of conservation ability in all children were not found.

PAGE 45

37 Taking a cue from Smedslund ' s observation that different children were helped by different training procedures and from evidence that early conservers did share some particular characteristics, attention was turned to cogni-; tive style — one way of measuring individual differences. Perhaps cognitive style played a role in what helped a child acquire conservation ability. The two dimensions of cognitive style that Witkin and Kagan and their associates have researched were reviewed. The present study was not the first to look for relationships between cognitive style and conservation ability (or performance on classification tasks — a prerequisite for conservation according to Piaget) , The research of three investigators (Peters, 1970; Garrettson, 1967; and Orpet and Myers, 1970) who have explored these relationships is reviewed here. Since these investigations were central to the rationale behind the hypotheses of the present study, they are reviewed in detail. Peters (1970) investigated the effectiveness of three methods of reversibility training on number conservation: (a) non-cued discovery, (b) perceptual cue-guided, and (c) verbal rule instruction under several conditions. The subjects, 131 predominantly lower socioeconomic class kindergarten children, were pretested on cognitive style. This measure was derived from a 25-object sorting task published by Educational Testing Service. The subjects were randomly J

PAGE 46

38 assigned to the three experimental groups and a control group. The non-cued group established equivalence between two sets of items 12 times in two training sessions utilizing wooden blocks . These blocks offered no cues that the child could use to infer one-to-one correspondence. The perceptual cue-guided group experienced a training procedure identical to the first, but the blocks had color and dominodot cues. The verbal rule instruction group had materials and procedures like the first again. But, this time a statement of the rule, that is, the logical reason for conservation, was given following the completion of each transformation. At posttest, the means of all three training procedures were significantly higher than the control group. The verbal rule group was significantly higher than either the perceptual cue-guided or non-cue discovery groups. These two did not differ significantly. In a delayed posttest, however, both the perceptual cue-guided and verbal rule instruction groups were superior to the control and did not differ significantly from each other. The best predictor for number conservation performance on pre-and posttests was the subject's age. This was followed by language comprehension and analytic cognitive style. The last finding was evidence that there was a relationship between cognitive style and conservation ability. Some of the reasoning the author included in his conclusion is pertinent to the present study. Since the cognitive style pretest v;as a measure only of the preferred way a

PAGE 47

39 child perceived and organized his environment, it did not reflect an inability to organize things other ways. Peters reasoned that the training may have forced the non-analytic subjects to relinquish their preferred style and to adopt the analytic stance in the experimental situation. This meant that the ability of the siibjects to be flexible in cognitive style may have enabled them to take advantage of the analytic cues offered in the training procedure, regardless of the style preference they showed on the pretest, and helped produce the positive experimental results , This was evidence that flexibility of cognitive style was related to conservation ability, Garrettson (1969) tested 60 seven-year-old, secondgrade, suburban, public school boys on three Piagetian classification tasks. Kagan's CST was administered to assess the subjects' cognitive style. Almost all of the subjects proved to be transitional between preoperations and concrete ^ operations. No significant correlations were observed be-, tween the use of analytic style on Kagan's test and the subjects' performance on the Piagetian tasks. This evidence did not agree with that of Peters (1970) , but the instrument used to measure cognitive style was different and one also had to assiime that a relationship with classification ability would be like a relationship with conservation ability. Despite the fact that classification abilities have been considered by Piaget to be prerequisite to conservation ability, such an assumption was a risky one.

PAGE 48

40 Part of the author's discussion of this study included the hypothesis that paying attention to fine perceptual details (Kagan's analytic style) is associated with superior classification behavior only when it is used in conjunction with attention to the part-whole or hierarchical aspects of the classes. This was evidence that flexibility of cognitive style related to classification ability — and possibly to conservation ability, A study by Orpet and Myers (1970) of 133 firstand second-grade, middle-class subjects produced a discriminant function analysis of conservation stages by structure of intellect and cognitive style variables. The test battery, totaling 22 variables, included conservation of liquids tasks, structure of intellect tests and a cognitive style test. Chronological age was also a variable. Cognitive style was determined by the Descriptive part-whole, Descriptive-global, Relational-contextual and Categoricalinferential scores on the SCST (Sigel, 1967) . The subjects were scored in one of three stages of conservation according to their persistence of judgment. The subjects were rated as nonconservers , transitional conservers or consistent conservers. The results did not discriminate transitional conservers from consistent conservers. The variables best discriminating nonconservers from transitional conservers , in order of strength, were (a) Wechsler Intelligence Scale for

PAGE 49

Children (WISC) — picture arrangement, (b) Nebraska Picture Associations, (c) Knox cube tapping, (d) Descriptiveglobal style, and (e) chronological age. Of importance for the present study was the finding that Descriptive-global scores discriminated the more successful conserver. This was evidence for a relationship between cognitive style and conservation ability. Since Orpet and Myers' research used the same instrument to measure cognitive style as the present study used, the results were the most supportive of the three studies cited here for this paper's hypotheses. The present study, therefore, did not explore the unknown. Peters (1970) found analytic style related to number conservation. Descriptive-global style predicted conservation of liquids ability in a study by Orpet and Myers (1970) , Garrettson (1969) looked for relationships between cognitive style and Piagetian classification tasks. No relationships were found. This could have been seen as contr-adic-:. tory evidence only if one assumed that the ability to -.-tclassify was intimately connected to the ability to conserve. Some of the reasoning in the discussion sections of the ; _ studies by Peters and Garrettson suggested relationships be-, tween flexibility of cognitive style and conservation and classification. These studies provided empirical support for research into the role of cognitive style in the acquisition of conservation ability.

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42 Rationale This investigation sought to answer the question, "TVhat is it that helps a child acquire conservation ability?" The review of the literature presented answers that others offered through their theoretical models and training methods. The present study hypothesized another answer^ — that preference and flexibility of cognitive style play a role in the ease with which a child becomes able to conserve. There were reasons why this answer was a likely one. The rationale behind the hypotheses used supporting evidence from three areas: (a) evidence which indicated a relationship between preference in cognitive style, that is, v/hich style categories were used most frequently throughout all test items, and conservation ability, (b) evidence which indicated a relationship between flexibility in cognitive style, as measured by the frequency of successive style alternations in multiple responses on each test item in a cognitive style test, and achievement, and (c) observations of experimenters which suggested a relationship between flexibility of cognitive style and conservation ability. The specific experimental results and research that pertained to each of these three areas are cited below: 1. Using the SCST (Sigel, 1967), Orpet and Myers (1970) found Descriptive-global style preference to be a reliable basis for predicting a child's ability in conservation of liquids. Peters (1970) obtained a measure of cognitive

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43 style from an Educational Testing Service (1968) sorting task. He found analytic style to be a significant predictor of number conservation ability. Using Kagan's CST, Garrettson (1969) found no relationship between analytic style and success on Piagetian classification tasks. Success on such tasks has been described as a prerequisite to conservation according to Piaget. Two of these three experiments (Orpet and Myers, 1970 and Peters, 1970) succeeded in finding a relationship between cognitive style preference and conservation ability. The third (Garrettson, 1969) did not find cognitive style relating to her criterion variable. But, since classification ability was tested rather than conservation ability, her results were not as directly applicable. There was an ambiguity between the two experiments that obtained positive results. Orpet and Myers (1970) found Descriptive-global style to relate to conservation and Peters (1970) found analytic style to relate. This may have been a plain inconsistency, or it may have been that each of these two different cognitive styles related specifically to the particular conservation ability tested in each experiment. Despite the ambiguity, these experiments suggested a relationship between cognitive style and conservation ability. Discriminant function analyses and correlational studies such as the ones cited above did not show that cognitive style caused conservation ability. Nevertheless, a

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44 more adequate answer to the question of what it is that helps a child conserve appeared likely through further research into the demonstrated relationship, 2. There was evidence that flexibility of style was as important a characteristic as style preference. Flexibility of style referred to a subject's tendency to alternate style on successive choices within each item on a cognitive style test. Using chi-square and multiple correlation analyses, Yeatts and Strag (1971) were able to demonstrate that shift, or flexibility, in cognitive style was significantly related to academic achievement. Flexibility of style was obviously an important individual characteristic of children with consequence for their intellectual functioning. Since this was true for academic achievement, it was reasonable to hypothesize a relationship between flexibility of cognitive style and conservation. 3. The proposed relationship between flexibility of cognitive style and conservation ability was supported by research evidence. The link between flexibility of cognitive style and conservation came from three sources (Halford, 1970b; Peters, 1970; Garrettson, 1969). Halford (1970b) proposed that it was the "constraint" between more global quantitative cues and more discrete height and breadth cues that had to exist before conservation judgments were possible. It was reasoned here that the ability to perceive flexibly, to see things one way and then another, favored

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45 the attention to such "constraint" between cues. Peters' (1970) experiment included a training procedure for number conservation. In discussing the results, he suggested that the kind of experience provided in his training procedure forced all subjects to focus on analytic cues and drop whatever preferences were shown on a style pretest. Ability to be flexible in style, and thus to use the analytic style cues offered in his training procedure, may have contributed to his positive results according to Peters, Garrettson (1969) , who found no significant correlation between the subjects' use of analytic style and their performance on Piagetian classification tasks, proposed that paying attention to fine perceptual details, characteristic of analytic style, was associated with superior classification behavior only when it was used in conjunction with attention to the part-whole or hierarchical aspects of the classes. Flexibility of style would have lent itself to the recognition and use of such a broader spectrum of cues. Halford's (1970b) "cue constraint" model and Peters' (1970) and Garrettson' s (1969) investigations offered strong evidence for a relationship between flexibility of cognitive style and conservation ability. Hypotheses Strong evidence for a relationship between cognitive style preference and conservation ability was produced by Orpet and Myers (1970), Peters (1970) and Garrettson (1969), ; i I

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46 The results of Yeatts and Strag's (1971) investigation, the discussion offered by Peters (1970) and Garrettson (1969) and implications from Halford's (1970b) model clearly indicated a relationship between style flexibility and conservation ability. It was, therefore, proposed to analyze the relationships between cognitive style preference and flexibility and conservation. On the basis of the supporting evidence, the hypotheses were: 1. There will be a significant relationship between preference of cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. 2. There will be a significant relationship between flexibility of congitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. Summary The purpose of this study was to investigate the relationship, if any, between preference and flexibility of cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance, and weight conservation tasks. Considerable literature was reviewed in an attempt to explain the transition from nonconservation to conservation. Studies that offered evidence for relationships between preference of cognitive style ana conservation ability, flexibility of

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47 cognitive style and achievement, and flexibility of cognitive style and conservation ability provided a rationale for hypothesized relationships.

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CHAPTER II METHOD AND PROCEDURES Sample A sample of 37 first-grade, middle-class, suburban boys (almost the entire male population from that group at Lime Street Elementary School, Lakeland, Florida) was used. Such a sample v/as chosen because a review of the literature revealed that conservation ability had been affected by urbanrural residence, socioeconomic class and sex. Socioeconomic class and sex have been shown to affect cognitive style. Limiting the sample in the above manner limited the generalizability of the results, but helped control variance Judgments about the subjects' urban-rural location and socioeconomic class were made on the basis of residence and vocation of the head of the house. These judgments were made in consultation with the principal. Instrumentation The Peabody Picture Vocabulary Test (PPVT) was administered to all subjects. This test was chosen to obtain an IQ measure because it could be quickly and easily administered and because verbal subscores have been generally the most highly correlated v.'ith overall IQ scores (Terman and 48

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49 Merrill, 1937; Wechsler, 1949). Euros (1965) reported alternate form reliability at .77 at the six-year level for the PPVT. Intertest correlations were also reported between the FPVT (Form B) and the CTMM, Henmon-Nelson Tests of Mental Ability, the Stanford-Binet (S-B) and the WISC. These ranged from .58 to .80. The SCST, Form M (1967) was administered to all subjects. The SCST consists of a set of 21 cards, each with three black and white drawings/photographs of familiar objects. Each child was asked to pick out two pictures that "go together, belong together, or are related in any way" and to state the basis for his sort. These stimuli were constructed to elicit Descriptive part-whole. Descriptiveglobal, Relational-contextual and Categorical-inferential concepts. Descriptions of these categories (as Sigel defines them in the SCST Manual) appear in Appendix A, Testretest and split half reliability has varied from .60 to .80 according to Dr. Irving Sigel (personal communication, February, 1972). Davis (1971)' reported a mean test-retest reliability coefficient of ,66 for Form A of the SCST when it was administered to fifth, eighth, and eleventh graders and college students. At the fifth-grade level (closest to the age of the sample in this study) the coefficients were between ,67 and .87 on the four major style categories.

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50 Standard tasks of number, length, substance and weight conservation were also administered to all subjects. The precise procedure and materials for each are described in the Procedure section. Assistants Nine volunteer, undergraduate students from an educational psychology class at Florida Southern College, Lakeland, Florida, were used as assistants. Two females administered the Peabody tests. They were trained by the school principal for several days before the testing was begun. Six males administered the SCST and conservation tasks. They were trained by the author of the present study for several sessions and practiced on non-sample children before testing was begun. Not all the male students tested the same niimber of children. But, effects due to the tester should have been negligible since all the subjects were randomly assigned to the assistants for testing. Male assistants were used to control for sex differences among the examiners affecting the subjects differently. The two females and the seventh male assisted in collecting the data. Two students from a child psychology class at Valencia Community College, Orlando, Florida, also assisted with this study. One, a female, was trained in Smedslund's categories of justification for conservation by the author of the present study. When an interrater reliability between her and

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51 this author reached 92 percent agreement on practice responses, she scored the justification portion of the conservation tests. The student and this author obtained 96 percent agreement in scoring the subjects' justifications. The second student, a male, was trained by the author in scoring the SCST. When an interrater reliability between him and the author of this study reached 80 percent agreement on practice responses, he scored four randomly chosen responses on the SCST for each subject. The student and this author obtained 84 percent agreement in scoring. One difficulty was encountered. Neither the student nor the author was able to satisfactorily distinguish between Relational-contextual 1 and Relational-contextual 5 style categories. As a result, they were combined in the data collection. This was not considered much of a loss in precision of measurement since the SCST Manual published with the test states, "Because of the low frequency of some of these, all Relationalcontextual subcategories can be combined for analysis." Procedure During the first two weeks of the testing, all subjects received the PPVT. The procedures outlined in the test Manual were followed carefully. During the third week, the SCST, Form M (1967) was administered to all subjects. The experimenter (student assistant) sat across from the subject at a table and showed

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52 the cards to the subject one at a time. In addition to the standard experimenter's instructions for the SCST, the subject was invited to find as many ways as possible in which any two figures go together. The experimenter said, "Can you do that in another way?" after each subject's response. The subject was given forty seconds for responses, Style preference was recorded in two ways: (a) the subject's first response to each new stimulus and (b) total frequency of responses in each style category. Successive responses to the same item were analyzed as to sameness or difference of cognitive style and a flexibility score given. The flexibility score was the percentage of total categorizable responses in which there were successive alternations in styles. Only shifts in style within the responses to each test item (not including shifts between the last response of one item and the first response to the next item) were counted r — , r ---------During the fourth and fifth weeks, the conservation tasks were administered. In the conservation of number tasks, the subject was presented with two parallel rows of pennies of equal length, six pennies in each row, arranged in one-to-one correspondence. The experimenter and subject counted the pennies in the experimenter's row and the subject's row to establish equivalence. The experimenter's or subject's row was lengthened or shortened (alternating these features from subject to subject) and the subject was

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53 then asked v/hether he had more, less, or the same number of pennies as the experimenter. An explanation of the judgment was asked. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you sure that you really have the same number as I do?" The subject's responses were recorded according to correctness, symbolic-logical explanation or not and persistence to countersuggestion. The conservation of length task consisted of two sixinch sticks placed parallel to each other and side by side in such a way that their ends coincided. The subject was asked whether the experimenter's stick and the subject's stick were the same length. After equivalence had been established, the subject's stick or the experimenter's stick (alternating by subject) was then moved so that its end extended one inch beyond the other and the subject was asked whether his stick was longer, shorter or the same length as the experimenter's. An explanation of the judgment was asked. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you sure that your stick is the same length as mine?" The subjects' responses were recorded according to correctness, symbolic-logical explanation or not and persistence to countersuggestion. Two small Play-Doh balls of rhe same color and equivalent to all other properties were presented to the

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54 subject in the test for conservation of substance. The subject was asked v;hether they both had the same amount of clay. Small portions were added or subtracted if necessary until the child agreed on their equivalence. One was considered the experimenter's and one the subject's. One of the balls (alternating by subject) was then flattened into a pancake shape by the experimenter. The subject was asked whether his had more, less, or the same amount of clay as the experimenter's. An explanation was requested. If the response was a conserving one, the experimenter asked, "Another child told me that they were not the same; are you sure yours has the same amount of clay as mine?" The subject's responses were recorded in terms of their correctness, symbolic-logical explanation or not and persistence to countersuggestion. The conservation of weight task was similar to the substance task. Initial equivalence was asserted with the help of a balance scale. Clay was added or subtracted, if necessary, to establish equivalence. All the questions related to weight instead of amount, but scoring was the same. In scoring the conservation tasks, the subject was awarded one point for each correct judgment, one point for each symbolic-logical explanation and one point for each survival to countersuggestion. This produced possible scores for each subject from 0 to 12. Sequence of conservation tasks was varied randomly to control for order effects.

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55 All testing was done in four rooms made available by the school for the purposes of this study. Conditions were not identical for each of the subjects, but as close as possible. All sessions of cognitive style and conservation testing were tape recorded. The children's responses were transcribed off of the tapes and ultimately onto forms printed for the purpose of recording the data. This procedure was chosen because it eliminated the distraction and difficulty of a recording person in the test situation and also provided a more accurate transcription of the child's responses. The experimenters (student assistants) called for each subject from his classroom, walked with him to the testing room, being casual and friendly but not overly solicitous, tested him, walked him back to the classroom, called for the next subject, etc. The boys came from four first-grade rooms and were called for and tested in random order. The literature indicated that error had come from variables such as varying desirability of materials (Roll, 1970), varying task complexity (Fiegenbaum, 1963), anxiety due to the strangeness or threatening nature of the test situation, unintentional reinforcement of the experimenter to the responses of the subject — perhaps somehow turning the conservation testing procedure into a training procedure, among other dangers. The test materials were designed with a sensitivity to the problems of stimulus desirability and

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56 task complexity, and it was believed that those factors were not sufficient to affect the results. The experimenter and assistants attempted to create a test situation which was warm and allayed fears v/ithout becoming too personal or producing unintended reinforcement. Da ta Co Uection and Analysis THE PPVT IQ's were recorded directly on the scoring sheets provided with the test Manual and booklets. The age of each subject was recorded here in years and months and later converted into months for the analyses. Cognitive style tests were tape recorded. All responses were then transcribed verbatim onto sheets printed for that purpose by the author. The responses were then scored independently by this author and the student with whom interrater reliability had been established. The results for each subject were tabulated. Preference according to initial preference (first response for each item) was tabulated in two ways: (a) by major categories and (b) by the 20 substyle categories. Flexibility (successive alternation or shift in style within each test item) was tallied in two ways: (a) shift between the four major categories and (b) shift between the 20 substyle categories. The four major categories in the SCST ares Descriptive part-whole (DPW) , Descriptive-global (DG) , Relationalcontextual (RC) , and Categorical-inferential (CI) . It

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should be reiuenibered that only 20 substyle categories appear in the data because two substyles, Relational-contextual 1 and Relational-contextual 5, were combined in the statistical analysis. The conservation task sessions were also tape recorded and all the children's responses were then transcribed onto forms printed for the recording of these data. The justification responses were then scored independently by this author and the student with whom interrater reliability had been established. The results for each student were tabulated. The number of points awarded for conservation on all four conservation tasks, the number of points for symboliclogical justification on conserving judgments and the number of points given successful resistance to countersuggestion and extinction were noted. A total, composite score was then figured. At the conclusion of the data collection, there were scores on each subject for: I. Cognitive Style A. initial preference on four major styles B. total preference on four major styles C. initial preference on 20 substyles D. total preference on 20 substyles E. flexibility of style between major categories F. flexibility of style between all categories G. fluency II. Conservation--composite scores for all points on all tasks III. PPVT IQ IV. Age in months

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58 This information was then punched onto data cards . The data were analyzed using regression techniques. To screen the data and reduce the number of independent variables, discriminant function analyses were completed. Then, a multiple regression analysis was completed on the variables which proved of value in the discriminant function analyses. The multiple regression analysis identified the combination of independent variables with the most power for predicting a subject's conservation score. Stepwise discriminant function analyses were run using the BIOMED 07M program. The results of a discriminant function analysis indicate to a researcher whether any of the data he has for his subjects are useful in predicting to which of two or more groups the subjects belong. In the present study, they indicated the usefulness of cognitive style preference and/or flexibility, fluency of response, PPVT IQ, and age for predicting whether each subject v/as a conserver or a nonconserver . The stepv/ise portion of the analysis indicates which variable is the most powerful in predicting group membership; and then, in order of predictive power, which further variables, in combination with those already entered, are most helpful. Membership in the conserving or nonconserving group was the dependent variable (the one to be predicted) in all five analyses. The independent variable was the score on some characteristic of the subject (e.g., cognitive style preference) that was hypothesized to relate to or predict the dependent variable.

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59 The subjects were divided into two groups for purposes of the discriminant function analyses — conservers and nonconservers. A total of five analyses were completed. The first analysis used initial preference scores on each of the four major style categories as the independent variable; the second, initial preference scores on the substyle categories; the third, total preference scores on each of the four major style categories; the fourth, total preference scores on the substyle categories; and fifth, an analysis was done using the two flexibility scores, PPVT IQ, age in months and fluency (total number of categorizable responses) as the independent variables. The independent variables that demonstrated power in the discriminant function analyses were used in a multiple regression analysis. This analysis was run using the BIOMED 02R program. The results of a multiple regression analysis indicate to a researcher whether there is a combination of independent variables that will predict (when entered into an equation) the score of each subject on the dependent variable. In the present study, they indicated a combination of measures of cognitive style that, when entered in a regression equation, predicted at a statistically significant level the conservation scores of the subjects .

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CHAPTER III RESULTS The conservation scores were bimodally distributed. Most of the subjects clustered around either low scores or high scores and few were in the middle. Twenty-three subjects scored between 0 and 5 points on the composite conservation score. They were classed as nonconservers . Thirteen subjects scored between 7 and 10 points. They were classed as conservers. One subject who scored 6 points was dropped. No subjects scored 11 or 12 points. The distribution of conservation scores is shown in Figure 1, A total of five stepwise discriminant function analyses were completed using the BIOMED 0-7M program, r :The -first analysis used initial preference scores on each of the four major style categories as the independent variable;: the second, initial preference scores on the substyle categories; the third, total preference scores on each of the four major style categories; the. fourth, total preference scores: on. the substyle categories; and fifth, an analysis was done using the two flexibility scores, PPVT IQ, age in months and fluency as the independent variables. 50

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61 Figure 1. Distribution of Conservation Scores

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62 In those cases in which a substyle category was never used by any conserving or nonconserving subject, that variable was omitted from the analysis in which it occurred. This prevented artificial relationships from appearing. Using such variables would have meant that points (0.0) would have been entered into the equation rather than measures of variance. As a result, six variables were dropped from the discriminant function analysis using initial preference for the independent variable. Two variables were dropped from the analysis that used total perference. The approximate multivariate F values of all independent variables in predicting the conservation classification of the subjects are presented in Table 6. In each instance, the variables are listed in the order in which they were stepped into the equation. The numbers of conserving and nonconserving subjects who were classified as conservers and nonconservers on the basis of the variables entered into the equation at each step are also reported in Table 6, The only independent variable that demonstrated statistically significant power was initial preference on the substyle categories. With four variables entered, the ,05 level of significance was reached. Optimum power for classifying (p <.01) was obtained from an equation in which seven variables had been stepped. Therefore, a multiple regression analysis was performed on these data. The BIOMED 02R program was used. The fourteen variables that were analyzed in

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63 Table 6 Stepwise Discriminant Function Analyses '0 (U (1) •H H m IH -0 •d -H •H (U w (0 -H •H tH CO ni tu > iH 0) iH to in to U U to CO u 0) rd Id 0) m > CO tn iH CO H > 0) (U u u u u 0) -P u c Q) (U (1) 0) -P nJ C 0 > CO > > to > to in (d -H (d -H H fi u u u u 0 U U -P Q) 0 Q) m > CJ Xi (U X > C C C C M c (0 U 0 -H H cr0 0 0 o (1) 0 w in 0 (d 2 (d u
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64 Table 6 (continued) T3 'O Q) Q) H I4_l 4-1 Ti H H d) W CO •H CO 0) M-l (U (d (d -H H r-H U) CO CO CQ 0) U (0 CO U ns (d Cfl CO .H CO rH > 0) tfl > > to > CO CO (d -H ^H c u U U U G <1) e M U -P 0) 0 Q) (U CO > O XJ QJ X > m d c: c U G U fi (T3 U 0 -H •H 0 0 0 0 0) 0 CD 0 0. -H W < s •d W 0 2 rd 2 (d U
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65 Table 6 (continued) ^3 T3 (U 0) •H r-i it-l T! •H •H (U Q) m in •H •H H W iH 0) nj nJ •H -H > rH w 0] W W 0) u u U CO W b hI -( W > > y) > 0) 0) fd -H M C u u ^1 5-1 on 0) e M 0 +J Q) 0 <]) OJ 0) rH 'd H nJ •H (d W O to cn > m > o ^ OJ X > C C c G u G G (T3 U 0 -H •H tr O 0 0 0 QJ O Q) 0 •H QJ U +J d w O s o U W U W 0) ^ -P tn C C G t3 C 0 Ui 0 m 0 w 0 U) w > W <: s W 0 S n3 (d U (d U (d L3 DPW3 1. 3581 13,22 NS 18 5 11 2 L4 CI2 1.2930 14,21 NS 18 5 10 3 L5 RC3 1.2595 15,20 NS 18 5 11 2 L6 CIl 1.1265 16,19 NS 18 5 11 2 L7 DPW2 1.0072 17,18 NS 18 5 11 2 1.8 DG6 .9001 18,17 Other NS Variables 18 5 11 2 J. Fluency . 8798 1,34 NS 14 9 4 9 2 Flexibility between ail styles .6717 2,33 NS 10 13 10 3 3 Peabody IQ .4787 3,32 NS 12 11 8 5 4 Age in months .3636 4,31 NS 12 11 9 4 5 Flexibility between .2815 5,30 NS 12 11 9 4 major styles

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66 the discriminant function analysis using initial preference on substyle were entered into the multiple regression analysis. The dependent variable was conservation score. The results of this analysis are presented in Table 7, Conservation scores were predicted at the .05 level with two variables entered. With seven variables entered, maximum power (p <.01) was obtained. The means and standard deviations of all variables are presented in Table 8. In summary, the subjects' conservation scores were bimodally distributed. This distribution allowed reasonable division of the subjects into conservers and nonconservers . Five stepwise discriminant function analyses were completed. These tested the power of initial cognitive style preference, total style preference, style flexibility {measured in two different ways), PPVT IQ, age, and fluency in predicting the classification of the subjects as conservers or nonconservers. The results of these are presented in Table 6. Significant results were produced when initial preference was used as the independent variable. A multiple regression analysis was performed on the fourteen measures on this variable and the dependent variable, conservation score. The results of the multiple regression analysis are reported in Table 7, With seven variables entered into the equation, optimum power was obtained. The variables that were able to predict the subjects' conservation scores were measures of the subjects' tendency to pair the pictures in the item on the SCST

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67 H XI (3 Eh m •H tn >i H o •H VJ tn o u a> (U rH -p rH 2 0) tn •H 15 &. Q) 4-> W C O •H P (0 > QJ -H ro in 00 00 CN CN CM r~ in in cn n a> rH 00 in o CO in CN in in r~t^ ininininrHrHrHrHininin ooooooooooo Ui ^vvvvvvvvvvv n CN rH o 00 in ro n n CN (N CN CN CN CN H CN CO in vo 00 o rH (N rH rH rH UH r-» rin CO o 00 CM in IW UH o VD n 00 00 H in 00 CN CTi H CN in rH (N o in O r~ rH in tn ns n m n ro ro ro CN CN •H CN in in CN r~ rH VD U3 CN u O H O U U a H H cn Q U Q « Q Q Q u U CN Q ro in VD 00 o rH CN

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68 Table 8 Means and Standard Deviations Variable Nonconservers Conservers Mean Std.Dev. Mean Std.Dev. Initial Preference DPW 3.609 3.340 5.538 3.382 DPWl 1.522 2.274 2.385 2.631 DPW2 2.087 2.130 3.000 1.871 DPW3 0.000 0.000 0,154 0.376 DG 2.304 2.285 1.769 1.013 DG4 0.391 0,583 0.308 0.480 DG5 0.696 1.550 0.538 0.519 DG6 0.565 0.728 0,462 0.776 DG7 0 .652 0.935 0.462 0.877 RC 4.130 3.321 4.615 3.404 RC1&5 2.304 2.363 3.462 2.634 RC2 0.217 ' 0.518 0',538 0,660 RC3 0.043 0.209 0.000 0 ,000 RC4 1.087 1.345 0.462 0.877 RC6 0.391 0.656 0.154 0.376 RC7 0.087 0.288 0.000 0.000 CI 3.478 2.810 5.000 2.345 CIl 1.957 2.078 2.231 2.127 CI2 1.000 1.314 1.615 1.387 CIS 0.000 0.000 0.077 0.277 CI4 0.304 0.635 0,615 0.870

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69 Table 8 (continued) Variable Nonconservers Conservers Mean Std.Dev. Mean Std.Dev. CIS 0.000 0.000 0,154 0 . 376 CI6 0.217 0 ,671 0 . 308 0 .480 CI7 0.000 0 .000 0 ,000 0 ,000 Total Preference DPW 6.304 7.600 9.308 7.782 DPWl 2.348 3,511 3.308 4.231 DPW2 3. 870 4.605 5.846 4.723 DPW3 0.087 0.417 0.154 0.376 DG 3.043 3.843 2.462 2.066 DG4 0.435 0.590 0.462 0.660 DG5 1.174 3.525 0,692 0.630 DG6 0.070 0.876 0,692 0.630 DG7 0.739 1.096 0.615 1.121 RC 9.087 1.774 8.846 8.122 RC1&5 5.348 6.135 6.385 5,576 RC2 0.217 0.518 0.615 0.768 RC3 0.043 0 .209 0.077 0.277 RC4 2. 304 4.061 1.308 2.287 RC6 1.087 1. 782 0.538 0.967 RC7 0.087 0.288 0,000 0.000 CI 5.217 4.199 7.461 3.573 CIl 2.870 3.065 3.308 2.983 CI2 1.478 1.780 2,231 2.421

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70 Table 8 (continued) Variable Nonconservers Conservers Mean Mean Std.Dev. CI3 0.000 0 .000 0.077 0.277 CI4 0.435 0.662 0.692 0.947 CIS 0.140 0.458 0.154 0.376 CI6 0,435 0.896 0.769 0.927 CI7 0.043 0.209 0.231 0,439 Flexibility Between Categories 12.261 11.001 12.462 8.705 FlexiDilis-y lietween and Within Categories 19 348 18.059 19.077 13.219 Conservation Score 2.261 1.814 8.538 1,050 PPVT IQ 106.348 19.242 111.000 18.102 Age in months 80 .783 4.502 80,538 3.526 Fluency 23.217 16.251 28.000 11.299 Number of Different 6.83 3.01 8.85 2.23 Styles Used

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71 on the basis of comparison between figures (RC4) , age categories (DG5) , common role or attribute (12), age and sex (DG?) , thematic interaction or interdependent function (RCl & 5), family and other relationship (RC6) , and physical attributes (DPWl) . The means and standard deviations of all variables are reported in Table 8.

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CHAPTER IV DISCUSSION AND CONCLUSION To aid the reader in following this discussion, a brief, descriptive caption for each subcategory, followed by the symbol, has been used as the subcategories occur in the text. The caption refers to the category of reason a subject gave for pairing two of three pictures presented in each item on the SCST. For a fuller description of each category, the reader is referred to Appendix A. First Hypothesis The first hypothesis was: There will be a significant relationship between preference of cognitive style as measured by the Sigel Cognitive Style Test and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. Four stepwise discriminant function analyses were completed in testing this hypothesis. The independent variables were: 1) initial preference on the four major style categories, 2) initial preference on the substyle categories, 3) total preference on the four major style categories, and 4) total preference on the substyle categories. Neither analysis 72

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73 using total preference produced statistically significant results. Likewise, the results of the analysis utilizing initial preference on the four major styles were statistically nonsignificant. There were statistically significant results, however, when initial preferences on the substyle categories were the independent variables. The results are reported in Table 6. Statistically significant (p <.05) results were obtained in the fourth step of the analysis which employed initial preference on the subcategories as the independent variable. The four variables that were entered into the equation at that point were those which indicated the subjects' tendency to pair pictures on the basis of common locale (RC2) , physical attributes (DPWl) , thematic interaction or interdependent function (RCl & 5) , and family or other relationship (RC6) , The approximate multivariate F increased through the seventh step. At this step significance reached the ,01 level and only six subjects were misclassif ied . The fifth through the seventh step added these three style categories: age and sex (DG7) , common role or attribute (CI2) , and age (DG5) . Stepping in further variables progressively lowered the approximate F value and correctly classified only tx-io more subjects — even through the fourteenth step. Adding the next three variables — comparison between figures (RC4), common affect (CI4) and inferred attribute or unseen part (CI6) — did not change the level of significance. However,

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74 significance dropped to the .05 level when the next three variables were entered: status or occupation (DG4) , description of objects {DPW2) , and sex (DG6) , When the final variable, common behavior of function (CIl), was entered, the predictive power of the equation became nonsignificant. These results indicated that the subjects* membership in either the conserving or nonconserving groups could be predicted on the basis of the subjects' scores on seven substyle categories. The variables useful in classifying subjects into two categories, as the discriminant function analysis did, might not be the same as those that predict the subjects' conservation score, as a multiple regression analysis does. Said another way, comparing continuous data (style scores) with discontinuous data (conserving or nonconserving groups) might not produce the same results as comparing continuous data (style scores) with continuous data (conservation scores) . The latter is to be preferred in answering the hypothesis of the present study. In order to obtain the most powerful combination of variables from the 14 substyle categories, these 14 measures and conservation score, the dependent variable, were placed in a stepwise multiple regression analysis. The results are reported in Table 7. Seven of the first eight variables in the discriminant function analysis were the first seven in the multiple regression analysis; only the order in which they were stepped

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75 into the equation differed. The variable that was entered first in the discriminant function analysis , common locale (RC2) , was not entered until the ninth step in the multiple regression analysis. The results cf the multiple regression analysis indicated that an equation with only two independent variables, comparison between figures (RC4) and age categories (DG5), will predict the subjects' conservation scores at a statistically significant level (p <.05). The addition of four more variables raised the level of statistical significance to .01. These four were common role or attribute (CI2), age and sex (DG7) , thematic interaction or functional interdependence (RCl & 5) and family or other relationship (RC6) . Entering one further variable, physical attributes (DPWl) , to the equation, raised the F ratio considerably and accounted for a fair amount of variance. Adding more variables helped to account for very little additional variance and, after the tenth step, lowered the statistical significance to the .05 level. Two of the 14 variables, description of objects (DPW2) and common behavior or function (CIl), obtained an insufficient F for entry into the equation. Therefore, as predicted in the first hypothesis, there was a statistically significant relationship betv/een cognitive style preference and composite scores on several Piagetian conservation tasks. This relationship was

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76 demonstrated between initial preference cognitive style scores and conservation scores. Of the variables entered in the first seven steps of the multiple regression analysis, all four major style categories were represented. Four of these variables were preferred by subjects with low conservation scores. These were comparison between figures {RC4) , age categories (DG5) , age and sex (DG7) and family or other relationship (RC6). Three of the seven variables were preferred by subjects with high conservation scores. These were common role or attribute (CI2) , thematic interaction or interdependent function (RCl & 5) , and physical attributes (DPWl). Patterns were identified among the major styles as they were represented by the subcategories used in the multiple regression analysis. One Descriptive part-whole variable, physical attributes (DPWl), appeared in the seventh step and was positively correlated with the dependent variable. Two Descriptive-global variables, age categories (DG5) and age and sex (DG7) , occurred in the second and fourth steps. Both correlated negatively with conservation score. The Relational-contextual major category appeared three times. Comparison between figures (RC4) , thematic interaction or interdependent function (RCl & 5) and family or other re. lationship (RC6) were entered in the first, fifth and sixth step. Two of these, comparison between figures (RC4) and family or other relationship (RC6),were correlated negatively

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77 with conservation score. Conservation correlated positively with thematic interaction or interdependent function (RCl & 5). One Categorical-inferential variable, common role or attribute (Cl2),was entered in the third step and was positively correlated with conservation score. Summarized another way, positive relationships existed between subcategories from two major styles, Categoricalinferential and Descriptive part-whole and conservation scores. There were negative relationships between two subcategories of the Descriptive-global style and the dependent variable. The relationship of the subcategories within the Relational-contextual major category was ambiguous. These results implied that one can predict a given subject's conservation score by his preferred use of the common role or attribute (CI2) , physical attributes (DPWl) and thematic interaction or interdependent function (RCl & 5) cognitive styles and by his infrequent use of age categories (DG5) , age and sex (DG7) , comparison between figures (RC4) , and family or other relationship (RC6) styles. Furthermore, one can predict a subject's conservation score at a lower level of statistical significance (p <.05) on the basis of a subject's score on just two variables — his infrequent use of comparison between figures (RC4) and age categories (DG5). Why was a coiribination of these particular styles capabl of predicting what a subject's conservation score would be?

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78 Was there something shared by CI2, DPWl and RCl & 5 that a subject needed to use to be able to score high on conservation? Or, was there something shared by DG5 , DG7 , RC4 and RC6 that a subject needed to ignore to be able to score high on conservation? CI2, DPWl and RCl & 5 appeared an unlikely combination. One might have expected a clear preference of one style or another, but a combination of three of the four major styles was confusing. For a subject to choose the CI2 category, he was grouping objects in the SCST on the basis of an inherent common role, class or attribute (e.g., both figures were animals, ways of transportation, tools, professional people, violent, juicy, etc.). When a subject chose the DPWl category, the basis for the grouping was the physical attribute or property of the materials in the pictures (e.g., color, texture, shading, shape). Sorts based on themes, plots or stories (e.g., he killed this man, she is giving him food, etc.) and sorts in which objects were grouped together on the basis of their interdependent use or function (e.g., the hammer is being used to bang the nail, ham and bread make a sandwich, etc.) were scored as RCl & 5 cognitive style. The tendency for a subject to prefer sorting on the basis of inherent, common characteristics (CI) or on the basis of observable parts of the stimulus (DPW) or on the basis of relationships (RC) was found to be statistically independent by Sigel, There was no reason for the

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79 combination of these styles in a regression equation predicting conservation scores. The literature cited in this study did not provide an explanation for such results. V?as there something shared by DG5, DG7, RC4 and RC6 that a subject needed to ignore to be able to score high on conservation? In order to score on DG5, a subject sorted on the basis of discrete age categories (e.g., children, old people, adults, etc.). Sorting on the basis of age and sex {old men, young women, boys, girls) indicated a DG7 cognitive style. RC4 sorts were those based on a comparison between two figures (e.g., this one is better than that one) and RC6 sorts indicated grouping on the basis of an understood relationship between the figures (e.g. , mother-son, doctor-nurse, teacher-student, etc.). There was no common quality between sorts based on the total objective manifestations of the stimuli (DG) and those based on relationships (RC) . The literature cited in this study did not"'^ provide an explanation for such results. ------In order to explain the results, the author attempted to discover the reason why the variables entered in the multiple regression analysis were able to predict the conservation score of the subjects. There was no explanation provided by the literature cited in the present study to support the results. The more frequent use of common role or attribute (CI2) , physical attributes (DPWl) , thematic interaction or interdependent function (RCl & 5) and the

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80 less frequent use of age categories (DG5) , age and sex {DG7) , comparison between figures (RC4) and family or other relationship (RC6) predicted a higher score on conservation. Another observation about the results explained part of what happened. The correlations between the fourteen independent variables used in the multiple regression analysis and the dependent variable, conservation score, indicated a clear pattern. Descriptive part-whole styles and Categorical-inferential styles were consistently positively related to conservation score. Descriptiveglobal styles were consistently negatively related. The Relational-contextual style was ambiguous. A nonconserver preferred Descriptive-global styles and, to some extent. Relational-contextual styles. A conserver rejected the Descriptive-global style for Descriptive part-whole and Categorical-inferential styles, and to some extent. Relational-contextual styles. This suggested that the combination of variables entered in the multiple regression analysis may have been the result of the tendency for a ' " subject who obtained a higher conservation score to choose a broader range of styles while rejecting the Descriptiveglobal style. Conversely, the subject who obtained a lower conservation score preferred the Descriptive-global style and used a more limited range of styles. ' " — ' ' ' Additional evidence for this explanation was provided by a simple tabulation of the styles used by the conservers

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81 and nonconservers (as conservers and nonconservers were defined in the discriminant function analyses) . This showed that the conservers used a mean of 8.85 different styles. This compared with a mean of 6.83 different styles used by nonconservers. No subject in either classification used more than 11 different styles (of the possible 20) in all hi responses on the SCST. The tabulation indicated that 10 of the 13 conservers (77%) used between 8 and 11 different styles. Only 10 of the 23 nonconservers (43%) used that many different styles. Another indication of the suggested distinction between conservers and nonconservers was found in the means of response frequencies tabulated according to initial preference. Of the 20 substyles which could be used by the subjects, 11 of them were preferred by the conservers, 8 by the nonconservers, and one was not used by either group of subjects. These means of response frequencies implied that nonconservers had fewer favorite styles and a more limited repertoire. Conservers, on the other hand, used more styles The total number of categorizable responses on the SCST was higher for conservers than nonconservers (Table 8) , It was, therefore, possible that the preference for more styles that the conservers displayed was only a result of this higher fluency of response. Or, as suggested here, it may truly have been the result of a larger repertoire.

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82 One explanation of the combination of independent variables (cognitive styles) that were entered into the multiple regression analysis to predict the dependent variable, conservation score, has been offered. Inasmuch as no literature cited in this study offered an explanation for the variables that emerged, another observation was made. This observation noted two things : 1) the pattern of correlations between independent and dependent variables, and 2) the number of styles used by conservers in comparison to nonconservers . Categorical-inferential and Descriptive part-whole styles were consistently positively related to conservation score. Descriptive-global was negatively related. Relationalcontextual was ambiguous . Conservers demonstrated a wider choice of styles. Therefore, it was concluded that the results of the multiple regression analysis were a consequence of the tendency for subjects who scored higher on conservation to differ from subjects who scored lower by the increased scope of cognitive style used rather than by transition to a new but also limited repertoire. This was also the response to the first hypo^thesis. There was a significant relationship betv;een cognitive style as measured by the SCST and intellectual maturity as measured by a composite score on number, length, substance and weight conservation ability. But, this significant

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83 relationship was a result of the difference in number of styles used by lov; and high scorers on conservation rather than by a unique and contrasting set of styles used by the two groups of subjects. Miat were the theoretical implications of the preceding discussion for the hypothesis that there would be a relationship between cognitive style preference and conservation ability? Several studies cited in the review of the literature found a relationship. Peters (1970) found that analytic style was the third most powerful predictor of number conservation abilities among kindergarten children. In an experiment with second-grade suburban public school boys, Garrettson (1969) did not find a relationship between the use of analytic style and Piagetian classification tasks. Orpet and Myers (1970) administered the SCST (1967) to 133 firsthand second-grade middle class subjects and found Descriptiveglobal style the fourth most powerful variable in discriminating ability in conservation of liquids. Both styles mentioned in the literature above as predicting conservation ability, that is, analytic style (Peters, 1970) and Descriptive-global style (Orpet and Myers, 1970) would find support for their results in the present study. The first study would find this support because of a positive relationship between Descriptive partwhole style and conservation ability and the second because of a negative relationship between Descriptive-global style and conservation scores.

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84 The results of the present study did not indicate that one particular cognitive style preference related to conservation ability. It produced evidence establishing the role of cognitive style in conservation ability — if only a general expansion in the use of part-whole (analytical) and inferential styles and a decreased use of global style. Second Hypothesis The second hypothesis was: There will be a significant relationship between flexibility of cognitive style and intellectual maturity as measured by the composite conservation score. Flexibility of style was measured in two different ways: (a) flexibility of style as measured in an overall percentage of total responses that shifted between the four major style categories within each item on the SCST and (b) flexibility of style as measured in an overall percentage of total categorizable responses that shifted betv/een the 20 substyle categories within each item on the SCST. A stepwise discriminant function analysis was done using the two sources of data and the results (Table 6) produced neither statistical significance nor mentionable trends. The number of shifts of style a subject made in responding to individual items on the SCST had no predictive value for classifying him as a conserver or nonconserver. In a tabulation of frequency of shifts (Table 8) , the

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85 mean score on both measures of flexibility did not differ by more tl-'an .3 between conservers and nonconservers . The correlation coefficient between these two measures of flexibility was .88 and appeared to carry the same meaning, A subject who shifted between major styles shifted in a like manner between the substyles. What does this mean theoretically? The rationale behind the hypotheses cited theory and research which indicated the plausibility of a relationship between flexibility of cognitive style and conservation ability, Halford (1970b) argued that there must be "constraint" between available cues before a child can conserve. He must both discriminate the cues and see their compensatory relationship. Yeatts and Strag (1971) claimed that not only initial preference but also flexibility of cognitive style is associated with academic achievement. Peters (1970) found analytic sort related to number conservation. According to the same author, ability to be flexible in style may have contributed to the positive results of his training procedure. Garrettson (1969) did not find any significant relationships between analytic style and Piagetian classification tasks. But, she stated that paying attention to fine perceptual details was associated with superior classification when it was used in conjunction with attention to partwhole or hierarchical aspects of the classes. The present study did not support these research findings or the

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86 rationale built on them. Discriminant function analyses attempting to identify conservers and nonconservers on the basis of flexibility of style did not produce significant results nor mentionable trends. IQ, Age and Fluency There were a number of other independent variables considered in this study. Some of the literature (Dodwell, 1960; Murray, 1968; Fiegenbaum, 1963; Goodnow and Bethon, 1966; Goldschmid, 1967) found that IQ related to conservation ability. Therefore, a PPVT was administered to all the subjects. Intelligence as measured by this instrument did not relate significantly to conservation ability (Table 6) . A glance at the mean scores on IQ (Table 8) indicated conservers averaged less than five IQ points higher than nonconservers. With an N of 37, not much could be said on the basis of that difference. Since the IQ scores obtained by the researchers cited above were measures of more general intelligence, it could be that the PPVT IQ does not correlate very highly with conservation. Nevertheless, as mentioned in the Instrumentation section, the vocabulary subscores of the S-B and WISC correlate highly with the full scale scores of the PPVT. Also, congruent validity of the PPVT as reported in the Instrumentation section of this study is high. Nevertheless, for this study, IQ did not emerge as a significant predictor of conservation ability.

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87 Another variable mentioned in the literature as predictive of conservation ability was age (Baptiste, 1969; Fiegenbaum, 1963; Goldschmid, 1967). This was controlled in the present study by selecting subjects in the same grade. Although it was expected that older children would be more likely to conserve than younger children, this didn't happen. The difference in the average age of the conservers and nonconservers was less than . 3 of a month — and that was in the opposite direction than expected (Table 8) , The F value obtained in the discriminant function analysis based on age in months was extremely low (Table 6) . The last variable to be discussed is a measure of the total number of categorizable responses, or fluency, Yeatts and Strag (1971) found that fluency related to intellectual performance. In the present study the F obtained in a discriminant function analysis was nonsignificant. Problems . i :" : : . The author of the present study found difficulties with the measures used for scoring. One difficulty was the manner in which conservation ability was assessed. The opportunity for variance provided by a total range ^of 0 12 in 3 ; the scores was less than optimal. Inasmuch as no child actually scored above 10, such opportunity was even less, ... When one looked over the results on the conservation tasks, it became apparent that the extinction procedure was not very powerful. Only in three instances did the conserving subject

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88 fail to resist, the countersuggestion in the extinction procedure. This means that only 8 of the possible 12 points on the conservation score distinguished between subjects. Also, since a composite score was used in the statistical analyses rather than separate scores on each of the conservation tasks, it was possible that relationships between one or another conservation task and cognitive style were masked by the composite score measurement. There were problem.s associated with using the SCST at this age level. The pictures presented in the text booklet were so poor in their detail that some children were not able to recognize them. Particular difficulties were encountered with items 3, 5, 16, 19, 21, and 31, The reader is referred to Appendix 3 for descriptions of each of the test items. The photographs of a snake, monkey, old man and old woman, ham slice, nurse and melon were not recognized on a number of occasions. A second problem with the use of the SCST at this age level was that some children could not articulate their choices and reasons. Nvunerous subjects would remain silent after pointing to their choices or would speak so indistinctly that their reason was incomprehensible. The experimenter often wished he knew what must have been in the child's mind but not on his lips. The letters of the alphabet were used as identifying marks for individual pictures in the test booklet. Some children used the

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89 alphabetical sequence of these letters as the reason for their sorts. For instance, a child would have said, "L and M go together because L comes before M," Others sorted, offering reasons such as "they sound alike," "they look alike," or "don't know" and monotonously stuck with that until their 'ordeal' was over. Since there was no place in the test procedure to prompt or otherwise press the subject to alter his responses , there was no way out of this dilemma. Some children never caught on. These problems with the use of the SCST on first-grade boys suggested that research into its validity and reliability with such subjects was necessary. Davis (1971) investigated the SCST using 23 items of Form A of the test. The Form M used in thi.s study was a selection of those items from Form A that Sigal found best for male subjects. Davis administered the test to 120 students in the fifth, eighth and eleventh grades and in college. Test-retest reliability ranged from .35 to .87 when scoring was done according to response frequencies as it is in the current study. At the fifth-grade level, the reliability on the four major styles ranged from .67 to .85 — all significant at the ,01 level. Problems were present in the item-response elicitation according to Davis. That is, some item.s of the test elicited only one or another style or inhibited the use of one or another style. A tabulation of four of the ten troublesome items Davis (1971) identified v;as done with the data produced in the

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90 present study. The items from the present study which were investigated were nujubers 13, 14, 25, and 27, As Davis suggested, the responses v/ere not elicited evenly. Item 13 did, as Davis found, elicit a larger proportion of Descriptive-global responses. Categorical-inferential responses were not exclusively produced by item 14 , as Davis discovered, but much in that direction. Davis found that Descriptive part-whole responses were produced out of proportion on item 25. While that style occurred with high frequency on item 25, the notable discrepancy in the present study is between the complete lack of any Descriptiveglobal responses and the occurrence of 30 Relationalcontextual responses. Item 27 replicated Davis' finding of no Descriptive-global responses, but did not elicit a high proportion of Categorical-inferential responses as Davis had found. This check of only four items hardly serves to indict the SCST. Nevertheless, the support that Davis' findings for fifth graders has in the above data for first graders served to suggest the need for investigating the use of the SCST with first-grade children. Conclusion The purpose of this study was to investigate the relationship, if any, between cognitive style as measured by the Sigel Cognitive Style Test (SCST) and intellectual maturity as measured by success on Piagetian ninnber, length, substance, and weight conservation tasks. Building a

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91 rationale on Halford's (1970b) model for conservation training and on experiments by Yeatts and Strag (1971) , Peters (1970), Garrettson (1969), and Orpet and Myers (1970), this author hypothesized that there would be a relationship among cognitive style preference and/or flexibility and conservation ability. Scores vjere obtained from 37 first-grade boys for cognitive style preference, flexibility and fluency; conservation ability; Peabody Picture Vocabulary Test (PPVT) IQ; and age in months. Four major categories of style in which the subjects could score were on the SCST: Descriptive partwhole (DPW) , Descriptive-global (DG) , Relational-contextual (RC) and Categorical-inferential (CI) . The four major categories contained 20 subcategories. These subcategories were indicated by an abbreviation for the major style plus a number (e.g., DPWl, RC4, etc.). To screen the independent variables, stepwise discriminant function analyses were completed. The variables which demonstrated predictive ability were then used in a stepwise multiple regression analysis. Cognitive style was scored according to initial preference (first response for each item on the SCST) and total preference (total frequency of responses in each style category) . Statistically significant results (a=.01) were obtained. Subjects' scores for their initial preference on two independent variables

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92 accurately predicted their conservation score (p <.05). Those two variables were cognitive style categories that used comparison between figures (RC4) and age categories (DG5) as the basis for pairing items on the SCST. The best equation (p <.01) used a combination of seven variables. Those variables were cognitive style categories that used comparison between figures (RC4) , age categories (DG5) , common role or attribute {CI2) , age and sex (DG7) , thematic interaction or interdependent function (RCl & 5) , family or other relationship (RC6) and physical attributes (DPWl) as the basis for sorting. The Descriptive part-whole and Categorical-inferential style categories were positively related to conservation scores. Descriptive-global style was negatively related to the dependent variable. Interpreting these results as they apply to the hypothesized relationship between cognitive style preference and conservation ability was difficult. The research cited in the literature review did not provide an explanation for these results. An explanation of the findings was offered on the basis of the nature of the correlations between the independent and dependent variables and the fact that subjects who scored high on conservation ability tended to use more style categories than the subjects who scored low. This suggested that subjects who obtained higher conservation scores used the Descriptiveglobal style infrequently and simultaneously enlarged their

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93 use of the other style categories. Subjects who scored lower on conservation preferred the Descriptive-global style and exhibited a more limited repertoire of cognitive style. The results gave a clear answer to the hypothesized relationship between cognitive style flexibility and conservation. Flexibility of style, fluency of response, PPVT IQ and age in months did not relate. In summary, this study produced evidence establishing the role of cognitive style in conservation ability — a general expansion in the use of part-whole (analytical) and inferential styles and a decreased use of global style. It did not, though, indicate that one particular style preference related to conservation ability. Nor did it find flexibility of style to relate to conservation. Some inadequacy in the use of a composite conservation score and some difficulties with the validity of the SCST were encountered. . .. -. . ,^ This study suggested the need for investigating the use of the SCST with first-grade subjects. It also pointed to the necessity of further research into the relationship between cognitive style and conservation abili.ty.

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APPENDICES j

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APPENDIX A SCORING CATEGORIES FOR SCST DESCRIPTIVE (Stimulus Center) : Concepts which are derived directly from the physical attributes of the stimulus and ones in which the conceptual label contains a direct reference to a physical attribute present in the stimulus. SUB-CLASSES OF DESCRIPTIVE CATEGORIZATION: These sub-types vary in terms of type of Descriptiveness employed. Their commonality rests on one direct reference to a denotable physical attribute. However, because of difference in cues employed, all Descriptive sub-categories should not be combined. A. The following could be combined, if desired, as indication of DESCRIPTIVE PART-WHOLE. D-1 Sorts in which the physical attributes or properties of the materials presented are the basis of similarity: e.g., color, texture, shading, or shape. D-2 Sorts in which the description of the objects depicted are employed: e.g., heads, legs, guns, belts, clothing, etc., including posture, hair color, or any part of the object. D-3 (Formerly D-7) Sorts based on (or dealing Note: From Sigel Cognitive Style Test by Dr. Irving E. Sigel. This publication used by permission from Dr. Sigel. 95

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96 specifically with) physical attributes (structural material): e.g., made out of wood, plastic, steel, etc. The following could be combined as DESCRIPTIVEGLOBAL. These categories appear similar to Categorical-Inferential labeling {C-2) . At this time, separation is recommended since mere responses are based on the direct cue in the stimulus. Further research is necessary to ascertain the independence of this category. At this time, based on some analyses of data from children and adults, DESCRIPTIVE-GLOBAL categories appear independent of Categorical-Inferential. Thus, these responses, for the time being, should be kept separate. D-4 Sorts in which the label designates the status, occupation, etc., where the cues are manifest in the stimulus: e.g., policeman, cowboy, WAC , nurse, etc. D-5 Sorts in which discrete age categories are employed; e.g., children, old people, adults, babies, young people. ' ' D-6 Sorts in which one of the sexes is grouped: e.g., males, females, men vs. women. D-7 Sorts based on age and sex: e.g., old men, young v/omen, boys, girls.

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97 RELATIONAL-CONTEXTUAL: Concepts which are used to tie together (or relate) two or more people, objects, events, ideas. In this category no stimulus is an independent instance of the concept , each stimulus selected gets its meaning and its definition in the sort from a relationship with other stimuli: e.g., a scene in a mental hospital, a family scene, you can make a triangle out of this square, these two things could make a carburetor, alcohol comes from wood . R-1 Thematic: Sorts which are based on themes, plots, or stories where no category is used: e.g., he killed this man, she is giving him food, etc. Sort implies interaction. R-2 Geographical ; Sorts in which the instances are related in space — locale, geographic, domiciliary, etc.: e.g., this man and this woman work in an office, this table with the chair belongs in the kitchen, they live in a jungle, they swim in water. R-3 Temporal : Sorts in which the figures are grouped on the basis of the temporal development of the individual: e.g., this is a person growing up, these are the stages of life in a person, etc., or temporal sequence: e.g., before and after of a crime. R-4 Comparativ e ; Sorts based on comparison

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98 between two figures: e.g., better than this one. R-5 Functional : Sorts in which objects are grouped together on the basis of their interdependent use or function: e.g., the steam shovel digs sand to put on the truck, hammer is used to bang nail, ham and bread make a sandwich, this woman helps this man, they help us. R-6 Sorts in which objects are grouped on the basis of an understood relationship state between the figures: A. Kinship only : e.g., family, mother-son, etc. B. Other relationship states : e.g., doctor-nurse, teacher-student, etc. R-7 Sorts in which the objects are grouped together on the basis of a relationship to som.e social event, institution, or organization: e.g., these people have something to do with crime or with law, they are in the armed forces. N.B. Because of the low frequency of some of these, all RELATIONAL-CONTEXTUAL subcategories can be combined for analysis.

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99 CATEGORICALINFERENTIAL: A group of objects are put together where each instance in the sort is representative of the total class. Each instance is not interdependent, characteristics are not necessarily observable, and a class label is used; it is an inference. C-1 Sorts in which the objects are grouped on the basis of a common behavior or function: e.g., these people all work for a living, these people all do services, means or ways of transportation, foods we eat, machines we ride in, tools for building, beds to sleep in; and participles of action: e.g., people dressing, modeling. C-2 Sorts in which the figures are grouped on the basis of an inherent common role, class, or attributes e.g., animals, way oftransr. portation, tools, professional people, violence, juicy, squarely, etc. C-3 Sorts in which the basis of similarity is a moral or aesthetic value or judgment placed on the part of the object or figures. .r.z M: Moral--good, bad, wicked, evil (realm of right or wrong) . A: Aesthetic — pretty, ugly, beautiful, attractive, etc. C-4 Sorts in which the figures are grouped on the basis of a common affect state: e.g..

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100 sad, unhappy, happy, etc. C-5 Sorts grouped on the basis of common locale, geographic, domiciliary, etc.: e.g., jungle animals, household furniture, underwater animals. C-6* Selection of an unseen or presumed constituent part or inferred attribute of object or instance: e.g., seeds, motors, color other than black and white. C-7 Value judgment which deals with evaluating something as to its intrinsic worth: e.g., something is useful, these are important for men, these are necessary, it is good for you to eat these. N.3. The only sub-categories in this area that might be combined are those dealing with single attributes: e.g., inferred parts, like motors; inferred characteristics: e.g., they grow; such as C-3, C-6, C-7.' Formerly a class labeling category, not combined with C-2.

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APPENDIX B SIGEL COGNITIVE STYLE TEST ITEM DESCRIPTIONS Item# Left Picture Middle Picture Right Picture 1 A tomato B pear C apple 3 G children H — fish J snake 4 K man 1 L — man 2 M man 3 5 N chair 0 _ floor lamp P — table 6 R banana S — monkey T — lollipop 7 V uniformed man W man in suit X uniformed man 8 Y axe z man A saw 12 L cow M horse N elephant 13 0 boy P man R girl 14 S peanuts T string beans V grapes 18 F sailboat G wrench H jeep 19 J — old woman K young woman li old man . . . _ 20 M horse N — stage coach 0 — dog 21 P sliced loaf of bread R tomato S ham slice 22 T girl V woman W baby 23 X boy Y woman z boy 25 D horse E pickup truck F baby carriage 26 G woman H man J nurse 27 K tractor L speed boat M stage coach 29 R uniformed man S nurse T man in suit 31 Y orange Z melon A apple 101

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REFERENCES Baker, N. E. , and Sullivan, E. V. The influence of some task variables and of socioeconomic class on the manifestation of conservation of number. Journal of Genetic Psychology , 1970, 116 , 21-30. Baptiste, H. The effect of an equilibrated methodology on the acquisition of the concept — conservation of quantity . Doctoral dissertation, Indiana University, Bloomington, Indiana, 1969. Beilin, H. Learning and operational convergence in logical thought development. Journal of Experimental Child Psychology , 1965, 2, 317-339. Braine, M. D. , and Shanks, B. L. The development of conservation of size. J ournal of Verbal Learning and Verbal Behavior , 1965, 4, 227-242. Brainerd, C. J. , and Allen, T. W. Experimental induction of the conservation of "first order" quantitative invariants. Psychological Bulletin , 1971, 75(2), 128-144. Brison, D. W. Acceleration of conservation of substance. Journal of Genetic Psychology , 1966, 109 , 311-322, Bruner, J. S. The course of cognitive growth, American Psychologist , 1964, 19_, 1-15. Buros, 0. The sixth mental measurements yearbook . Highland Park, New Jersey: Gryphon Press, 1965. Davis, A. J. Cognitive style: Methodological and developmental considerations. Child Development , 1971, 42, 1447-1459. Dodwell, P. C. Children's understanding of number and related concepts. Canadian Journal of Psych ology, 1960, 14, 191-205. Drake, D. Perceptual correlates of impulsive and reflective behavior. Developmental Psych ology, 1970, 2(2), 202-214. ' 102

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103 Fiegenbaum, K. D. Task complexity and IQ as variables in Piaget's problem of conservation. Child Development ^ 1963, 3A, 423-432. Fleischmann, B. , Gilmore, S., and Ginsberg, H. The strength of nonconservation. Journal of Experiemental Child Psychology , 1966, 4_, 353-368. Garrettson, J. E. Cognitive style and logical thinking . Doctoral dissertation, Columbia University, New York, N. Y., 1969. Ginsberg, H. , and Opper, S. P iaget's theory of intellectual development . Englewood Cliffs, N. J,: PrenticeHall, 1969.' Goldschmid, M. L. Different types of conservation and nonconservation and their relation to age, sex, IQ, MA, and vocabulary. Child Development , 1967, 38 , 1229-1246. Goodnow, J., and Bethon, G. Piaget's tasks: the effects of schooling and intelligence. Child Development , 1966, 32' 573-581. Gruen, G. F. Experiences affecting the development of number conservation in children. Child Development , 1965, 36(4), 963-979, Halford, G. S. An experimental analysis of the criteria used by children to judge quantities. Journal of Experimental Child Psychology , 1969, 8^, 314-327. Halford, G. S. A classification learning set which is a possible model for conservation of quantity, Australian Journal of Psychology , 1970, 22_, 11-19 (a), Halford, G. S. A theory of the acquisition of conservation. Psychological Review , 1970, 21^'*)' 302-316 (b) . Halford, G. S. Acquisition of conservation of quantity by learning a consistent classification system for quantities. Unpublished paper, 1970. Cited by G, S. Halford, A classification learning set which is a possible model for conservation of quantity, Australian Journal of Psychology , 1970, 22./ 11-19 (c) . Halford, G. S., and Fullerton, T. J. A discrimination task which induces conservation of nuitiber. Child Develop ment, 1970, 41, 205-213.

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104 Hatano, G., and Suga, Y. Equilibration and external reinforcement in the acquisition of number conservation. Japanese Psychological Research , 1969, 11(1), 17-31. Kagan, J., and Moss, H. A. Birth to maturity . New York: Wiley and Sons, 1962. Kagan, J., Moss, H. A., and Sigel, J. E. The psychological significance of styles of conceptualization. In J. F. Wright and J. Kagan (Eds) , Basic cognitive processes in children . Monograph of the Society for Research in Child Development, 1963, 28^(2), 73-112. Kagan, J., Rosman, B. L. , Day, D. , Albert, J., and Phillips, W. Information processing in the child: Significance of analytic and reflective attitudes. Psychological Monograph, 1964, 8_(1) (Whole No. 578). Kagan, J., Pearson, L. , and Welch, L. Conceptual impulsivity and inductive reasoning. Child Development , 1966, 37, 583-594. Kingsley, R. C. , and Hall, V. C. Training conservation through the use of learning sets. Child Development , 1967, 38, 1111-1126. Klahr, D., and Wallace, J. G. An information processing analysis of some Piagetian experimental tasks. Cognitive Psychology , 1970, 1, 358-387. Lee, L. C, Kagan, J.^ and Rabson, A. Influence of a preference for analytic categorization upon concept acquisition. Child Development , 1963, 34, 433-442*,Mermelstein, E., and Meyer, E. Conservation training techniques and their effects on different populations. Child Development , 1969, 40, 471-490. Messer, S. The effect of anxiety over intellectual performance on ref lection-impulsivity in children. Child Development , 1970, £1, 723-735. ^ .f-=--v Milgram, J. J. The relationship between the m.easures of the ref lectioh-impulsivity dimension of cognitive ' " style and visual perception . Doctoral dissertation," University of Maryland, College Park, Maryland, 1969, Murray, F. B. Cognitive conflict and reversibility training in the acquisition of length conservation. Journal of Educational Psychology , 1968, 59 (2), 82-87"!

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105 Murray, F. B. Stimulus mode and the conservation of weight and number. Journal of Educational Psychology , 1970, 6^(4) , 287-291. Orpet, R. E., and Myers, C. E. Discriminant function analysis of conservation stages by structure of intellect and conceptual style variables. Proceedings of the Annual Convention of the American Psychological Association , 1970, 5(1), 279-280. Overbeck, C. , and Schwartz, M. Training in conservation of weight. Journal of Experimental Child Psychology , 1970, 9, 253-264. Peisach, E. , and Wein, N. Relationship of conservation explanations to item difficulty. Journal of Genetic Psychology , 1970, 217, 167-180. Peters, D. L. Verbal mediators and cue discrimination in the transition from nonconservation to conservation of number. Child Development , 1970, £1, 707-721. Piaget, J. The psychology of intelligence , Totowa, N.J. ; Littlefield, Adams and Co., 1966. Roll, S. Reversibility training and stimulus desirability as factors in conservation of number. Child Development , 1970, 41(2) , 501-507. Rothenberg, B. B. , and Orost, J. H. The training of conservation of number in young children. Child Develop ment, 1969, 40, 707-726. Schwartz, M. M. , and Scholnick, E. K. Scalogram analysis of logical and perceptual components of conservation of discontinuous quantity. Child Development , 1970, 41, 695-705. Schwebel, A., and Bernstein, A. The effects of impulsivity on the performance of lower-class children on four WISC subtests. American Journal of Orthopsychiatry , 1970, 40(4), 629-636. Sigel, I. E. Rationale for separate analyses of male and female samples on the cognitive tasks. The Psychologi cal Record , 1965, 15, 369-376. Sigel, I. E., and Hooper, F. H. (Ed.). Logical thinking in children . New York: Holt, Rinehart and Winston, 196 8, Sigel, I. E. , Jarman, P., and Hanesian, H. Styles of categorization and their intellectual and personality correlates in young children. Human De velopment, 1967, 10, 1-17. —

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106 Sigel, I. E., Roeper, A., and Hooper, F. H. A training procedure for acquition of Piaget's conservation of quantity: A pilot study and its replication. The British Journal of Educational Psychology , 1966, 36, 301-311. Smedslund, J. The acquisition of conservation of substance and weight in children: II. External reinforcement of conservation of weight and of the operations of addition and subtraction. Scandinavian Journal of Psvcholoav. 1961, 2, 71-84 (a): ^ Smedslund, J. The acquisition of conservation of substance and weight in children: III. Extinction of conservation of weight acquired "normally" and by means of empirical controls on a balance scale. Scandinav ian Journal of Psychology , 1961, 2, 85-87 (bT Smedslund, J. The acquisition of conservation of substance and weight in children: IV. Attempt at extinction in the visual components of the weight concept. Scandi navian Journal of Psychology , 1961, 2, 153-155 (cT. Smedslund, J. The acquisition of conservation of substance and weight in children: V. Practice in conflict situations without reinforcement. Scandinavian Journal of Psychology , 1961, 2, 1956-160 {dT. ~ ~~ Smedslund, j. The acquisition of conservation of substance and weight m children. VI. Practice on continuous versus discontinuous material in conflict situations without external reinforcement. Scandinavia n Journal of Psychology , 1961, 2, 203-210 {eT. Smedslund, J. Apprentissage des notions de la'conservatibn ' " et de la transitivite du poids . In J. Piaget (Ed.), Etudes d'empistemologie genetique, 1959, Cited by Smedslund, J. Acquisition of conservation of substance 2 " 11^20^* U) ^^^^'^^"^^^^^^ Journal of Psychology . .1961, Smedslund, J. Patterns of experience and the acquisition of conservation of length. Scandinavian Jo urnal of Psychology . 1963, 4_, 257-264 .. .. . . . . . . Sollee, N. D. Verbal competence and tho ;.r^rrii-i =-; ^-^ of conservatio n. Doctoral dissertation, Boston University Graduate School, Boiiton, Massachusetts, 1969. Strauss, S. and Langer, J. Operational thought inducement. Child Development , 19 70, 41, 163-175. ^t^menx:.^

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' 107 Terman, L. M. , and Merrill, M. A. Measuring intelligence . Boston: Houghton-Mifflin, 1937. Waghorn, L. , and Sullivan, E. V. The exploration of transition rules in conservation of quantity (substance) using film mediated modeling. Acta P s ychologica , 1970, 22, 65-80. Wallach, L. , and Sprott, R. L. Inducing number conservation in children. Child Development , 1964, 35, 10571071. ~ Wallach, L. , Wall, A. J., and Anderson, L. Number conservation the role of reversibility, addition, subtraction, and misleading perceptual cues. Child Development , 1967, 38^, 425-442. .... Wechsler, D. Wechsler intelligence scale for children manual . New York: Psychological Corporation, 1949. Wineman, J. H. Cognitive style and reading ability. Cali fornia Journal of Educational Research , 1971, 22(2), 74-79. Winer, G. A. Induced set and acquisition of number conservation. Child Development , 1968, 39.' 195-205. Witkin, H. A., Dyk, R. B. , Faterson, H. F., Goodenough, D. R. , and Karp, S. A. Psychological differentiatio n. New York: Wiley and Sons, 1962. Wohlwill, J. Un essai d ' apprentissage dans le domaine de_la conservat-ion du nombre. In J. Piaget (Ed.), Etudes d' dpistemologie genetique, 1959, Cited by Smedslund, J. Acquisition of conservation of substance and weight. Scandinavian Journal of Psychology , 1961, 2, 11-20. Wohlwill, J. F. , and Lowe, R. C. Experimental analysis of the development of the conservation of numbers. Child Development , 1962, 33_(1) , 153-167. Yeatts, P., and Strag, G. Flexibility of cognitive style and its relationship to academic achievement in fourth and sixth grades. Journal of Educational Research , 1971, 64(8), 345-346. ~

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BIOGRAPHICAL SKETCH Glen Howard Rediehs was born March 19, 1940, in Hinsdale, Illinois. He attended the Hinsdale public schools through high school. In 1959 he received an Associate in Arts from Concordia Junior College, St. Paul, Minnesota. He earned a Bachelor of Arts from Concordia Senior College, Ft. Wayne, Indiana, in 1961 with a major in theology and a concentration in psychology. Concordia Seminary awarded him a Bachelor of Divinity in 1965. In 1971 he was admitted to the degree of Master of Divinity by the same institution. From 1965 to 1968 he served as pastor of Resurrection Lutheran Church, Orlando, Florida. In August, 1968, he began studies in the Department of Psychological Foundations, College of Education, University of Florida, Gainesville, Florida, and received the Master of Education in December, 1969. Since then he has pursued a Doctor of Philosophy from the same department. Between 1968 and 1970, he was employed as a counselor in the Division of Housing of the University of Florida for one year and was a Graduate Fellow for one year. Since 1970 he has been an instructor in psychology at Valencia Community College, Orlando, Florida. 108

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109 Hs is a meniber of Phi Delta Kappa and was elected to Phi Kappa Phi in 1969. In April, 1971, he married Patricia Lee (nee Bussell) . They are the parents of an infant daughter, Kimberley Gayle.

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. William Watson Purkey, Chairman Professor of Education I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. 'Robert Emile Jester, Co-chairman Associate Professor of Education I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. William E. Ware Assistant Professor of Education I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Vernon D. Van De Riet Associate Professor of Psychology

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This dissertation was' submitted to the Dean of the College of Education and to the Graduate Council, and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy, August, 1973 Dean, College/ of Education Dean, Graduate School