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An assessment of the relationship between social integration variables and community college student retention

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An assessment of the relationship between social integration variables and community college student retention
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Rom, Michael G
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English
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xiii, 186 leaves : ; 28 cm.

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College students ( jstor )
Colleges ( jstor )
Employee interaction ( jstor )
Peer relations ( jstor )
School dropouts ( jstor )
Social integration ( jstor )
Social interaction ( jstor )
Social systems ( jstor )
Student interaction ( jstor )
Students ( jstor )
College dropouts ( lcsh )
Community college students ( lcsh )
Dropout behavior, Prediction of ( lcsh )
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non-fiction ( marcgt )

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Thesis (Ph. D.)--University of Florida, 1985.
Bibliography:
Includes bibliographical references (leaves 142-150).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Michael G. Rom.

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University of Florida
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Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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AN ASSESSMENT OF THE RELATIONSHIP BETWEEN SOCIAL INTEGRATION
VARIABLES AND COMMUNITY COLLEGE STUDENT RETENTION















BY

MICHAEL G. ROM


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


1985

















DEDICATION


To my parents Jean and George Rom,
Who taught me to accept challenges and conquer fear;

To my son David who had to play ball by himself,
Because I was not there;

To my daughter Michele who because of my absence,
Fell asleep while shedding a tear;

To my ever loving wife Lucile,
Who was both mother and father when I was not near;

To my God who when things appeared the darkest,
Gave me strength to see things clear;

This dissertation is dedicated in your honor.
















ACKNOWLEDGEMENTS

I would like to acknowledge several individuals for their

continual support. Without these people I might not have

completed this task.

My committee consisted of Dr. Al Smith, Dr. Steve Olenjik,

Dr. Gordon Lawrence, and Dr. Paul Fitzgerald. I would like to

thank Steve for his patience which helped me through the final

stage of my data analysis. I would like to especially thank Al

who at times had to show me the way, at times hold me back, and

several times had to come find me because I was lost. To each of

these men I am deeply grateful.

I would like to thank all the professors, secretaries,

clerks, and students who were a part of my study and experiences

at the University of Florida. I would also like to express my

deepest appreciation to all of my friends who have given me

support and love on a daily basis. It's the contribution of the

many parts, however small, that make up the total affect of any

experience. For the part each of you played in mine I thank you.

The individuals who contributed to this study by editing,

typing, reading, or adding words of encouragement are too

numerous to list. I would like to acknowledge some special

individuals who made my task easier: David Rom, Jean Rom,

Charles and Catherine Hudson, Bill Reynolds, Larry Eason, Jane

iii










Schmit, Dora Mae O'brien, Rindy Penegor, Debbi Amburgey, Juan

Burbano, Bob Judson, Debbie Depoy, Don Lester, Hugh Turner, Dave

Helfirch, and Susan Anderson. In addition much appreciation goes

to the staff, faculty, and administration at Pasco Hernando

Community College for their support of this project.

To my family, Lucile my wife, David my son, and Michele my

daughter, I pledge my deepest love and appreciation. Seven

years ago if I had known what I was going to ask of you, I would

not have. My ignorance of the sacrifices you would have to make

the next seven years allowed me to forge on step by step. I not

only thank you for standing by me when I needed you but I truly

thank you for doing this tremendous task with me. We finally

made it and received our Ph.D.'s. Thank you Drs. Lucile, David

and Michele Rom, Ph.D.'s for all your love and congratulations

for a well deserved honor.
















TABLE OF CONTENTS



PAGE


ACKNOWLEDGEMENTS.............................................iii
LIST OF TABLES....................... ........................vii
LIST OF FIGURES................................................ x
ABSTRACT................... ...................................xi

CHAPTER

ONE INTRODUCTION ..................... .....................1

Tinto's Model.........................................5
Statement of the Problem.............................9
Hypotheses............................................9
Assumptions ................. ......................... 12
Delimitations ..................... ...................12
Limitations..........................................12
Significance of the Study...........................14
Definition of Terms.................................. 16
Organization of the Dissertation........................19

TWO REVIEW OF THE LITERATURE AND RELATED RESEARCH..........20

Review of the Literature..............................22
Validity of Tinto's Model in Residential
Settings...........................................24
Validity of Tinto's Model in Non-residential
Settings.............................. ............25
Reconceptualization of Tinto's Model ..............28
Variables...........................................31
Family Background.................................32
Individual Attributes.............................33
Pre-College Schooling............................ 34
Institutional Commitment..........................34
Goal Commitment..... .........................35
Grade Performance................................35
Intellectual Development.........................36
Peer-Group Interaction.................. ..........36
Faculty-Student Interaction......................37
Summary of the Chapter................................37











THREE METHODOLOGY .... .........................................40

Instrumentation.................................... ..40
Description of Student Survey.....................40
Development of Student Survey......................42
Variables................ ..........................42
Pilot Study.........................................50
Present Study.........................................51
Subjects..... ....................................51
Data Collection....................................52
Data Analysis............. ........................52
Summary of the Chapter..............................56

FOUR FINDINGS........ .....................................57

Descriptive Analysis...... ........................... 60
Demographic Variables...............................60
Correlations........................................66
Regression Analysis..................................78
Hypotheses 1-4................................... 78
Hypotheses 5-13..................................92
Hypotheses 14-19................................107
Anova Between Campuses............................112
Summary of the Chapter.............................113

FIVE SUMMARY, CONCLUSIONS, IMPLICATIONS,
AND RECOMMENDATIONS..................................117

Summary ................... ..........................117
Conclusion..................... .....* ....* ...........122
Implications...... .................. ............... 134
Recommendations.................. ...................138

REFERENCES ...................................................142

APPENDIX

A PROGRAM DECLARATION........................... ....152
B WRITTEN ENGLISH EXPRESSION PLACEMENT
TEST................................................. 154
C READING PLACEMENT TEST................................ 164
D STUDENT SURVEY ....... ...............................175
E MONITOR INSTRUCTIONS.................................. 185

BIOGRAHICAL SKETCH............ ..............................186

















LIST OF TABLES


TABLE PAGE

1 Frequency and Percentage Distribution for
Demographic Variables....................................61

2 Pearson Product Moment Correlation for
Endogenous and Exogenous Variables--
Total Campus...............................................67

3 Pearson Product Moment Correlation for
Endogenous and Exogenous Variables--
East Campus........................................... ..70

4 Pearson Product Moment Correlation for
Endogenous and Exogenous Variables--
North Campus.......................................... ..73

5 Pearson Product Moment Correlation for
Endogenous and Exogenous Variables--
West Campus.............................................76
2 2
6 R R" Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dtopout Decisions
With Social System Integration by Campus................80

2 2
7 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Social System Integration by Campus................80

2 2
8 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With Peer-Group Interaction by Campus....................83

2 2
9 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Peer-Group Interaction by Campus....................83

2 2
10 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With Faculty-Student Interaction by Campus..............87











TABLES-continued


TABLES PAGE

2 2
11 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Faculty-Student Interaction by Campus..............87

2 2
12 R2, R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With the Interaction Effect of Peer-Group and
Faculty-Student Interaction by Campus...................90

2 2
13 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With the Interaction Effect of Peer-Group and
Faculty-Student Interaction by Campus....................90

14 Means, S.D., and Computed t-Statistic
Comparing White and Non-White Students
on the Social System Variable............................ .. 93

15 Means, S.D., and Computed t-Statistic
Comparing White and Non-White Students
on the Peer-Group Interaction Variable..................95

16 Means, S. D., and Computed t-Statistic
Comparing White and Non-White Students
on the Faculty-Student Interaction Variable.............97

17 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Social System Variable............................99

18 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Peer-Group Interaction Variable.................100

19 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Faculty-Student Interaction Variable ............102

20 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who
Have Not on the Social System Variable..................104


viii










TABLES-continued


TABLES PAGE

21 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who
Have Not on the Peer-Group Interaction Variable........ 106

22 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who Have
Not on the Faculty-Student Interaction Variable....... 108

23 Correlation Coefficients for Accumulated
Semester Hours and Social System, Peer-Group
Interaction, and Faculty-Student Interaction
Variables by Campus.................................... 109

24 Correlation Coefficients for Age and Social
System, Peer-Group Interaction, and Faculty-
Student Interaction Variables by Campus................. 11

25 ANOVA Between East, North, and West
Campuses on Variables of Interest...................... 114

26 BONFERRONI Statistics: Faculty-student
Interaction on Student Survey Questionnaire............115

27 Results of the Hypotheses...............................127















LIST OF FIGURES


FIGURE PAGE

1 A Conceptual Schema For Dropout
From College (Tinto, 1975).......................... 3

2 Suggested Reconceptualization of
Tinto's Model (Pascarella, Duby,
and Iverson, 1983)..................................31
















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 ASSESSMENT OF THE RELATIONSHIP
BETWEEN SOCIAL INTEGRATION VARIABLES AND COMMUNITY
COLLEGE STUDENT RETENTION


By


MICHAEL G. ROM


August 1985



Chairman: Albert B. Smith III
Major Department: Instruction and Curriculum



Using Tinto's conceptual framework model, the purpose of

this study was to determine what relationships existed between

social system integration variables (peer-group and

faculty-student interaction) and student dropout decisions in a

two-year community college. Two hundred students, at Pasco

Hernando Community College, were surveyed during the Fall term of

1984, using a Student Survey Questionnaire. One hundred

fifty-two usable responses were received for a 76 percent return

rate. The instrument measured the student's background

characteristics, commitment (goal and institutional), academic

integration, social integration (peer-group and faculty-student

xi










interaction), and perceived dropout decision. In addition, other

demographic variables were requested via this questionnaire.

Four different population groups were considered; the total

student population, students attending the East, the North, and

the West campuses. Each of the 19 hypotheses was tested using

the four different population groups. Hypotheses 2 and 3, which

related peer-group and faculty-student interaction to the actual

dropout decision, showed significance at the .05 level for the

East and North campuses.

For East Campus students a significant proportion of the

variation in dropout decisions (11.2%) was explained by the

peer-group interaction variable (negative influence) and the

faculty-student interaction variable (8.6%), which was a positive

influence. For North Campus students a significant proportion of

the variation in dropout decisions (10.9%) was explained by the

peer-group interaction variable (positive influence) and the

faculty-student interaction variable (16.7%), which was a

negative influence.

Of the remaining 15 hypotheses relating age, sex, race,

accumulated semester hours, and a human relations type course

with the social integration, peer-group interaction, and

faculty-student interaction variables, six were found to have

statistically significant relationships at the .05 level.

The study showed that similarities between campus

populations were greater than the differences. The two main

xii










exceptions were peer-group and faculty-student interaction. The

variable relationships in Tinto's model did not appear to apply

evenly to this commuter school. When commuter populations have

characteristics in common with residential schools, then Tinto's

model of the dropout process may be more applicable than recent

research indicated.


xiii
















CHAPTER ONE

INTRODUCTION

Substantial time and interest have been dedicated to college

student attrition as is represented in the work of by Spady

(1970); Cope and Hannah (1975); Tinto (1975); Pantages and

Creedon (1978); and Lenning, Sauer, and Beal (1980). Despite all

the research, community college attrition rates have remained

high and virtually unchanged.

A national survey conducted in the spring of 1979 by the

American College Testing (ACT) Program and the National Center

for Higher Education Management Systems verified this consistency

in attrition rates (Beal & Noel, 1979). Retention after one year

in two-year public institutions was 55 percent in 1975-76, 55

percent in 1976-77, and 53 percent in 1977-78 as reported by 74,

82, and 92 two-year institutions respectively. More recent

statistics also confirmed a 50 percent dropout rate in

postsecondary schools (Grant & Eiden, 1982).

Prior to the 1970's, much of the research on attrition was

theoretical, identifying a variety of associations among various

student and institutional characteristics and attrition, but

lacked a theoretical base by which attrition could be studied.

Tinto (1975) attempted to bring some coherence to this research

as well as provide a conceptual framework to guide future

research. Tinto expanded Spady's (1970) work on student

I











attrition by developing a predictive, explanatory model of the

dropout process which has at its core the concepts of student

academic and social integration into the institution.

Tinto (1975), in his article "Dropout from Higher Education:

A Theoretical Synthesis of Recent Research," drew upon Durkeim's

(1961) theory on suicide which essentially theorizes that suicide

is more likely to occur when individuals are insufficiently

integrated into the fabric of society. Spady (1970) first

applied Durkeim's theory to college student dropouts by

suggesting that a college is a social system with its own values

and belief system.

Tinto (1975) further suggested that social conditions

affecting dropouts from college would be similar to those social

conditions resulting in suicide in society as a whole.

Specifically, he stated:

Insufficient interaction with others in the college and
insufficient congruency with the prevailing value
patterns of the college collectively will lead
to low commitment to that social system and will
increase the probability that individuals will decide
to leave college and pursue alternative activities.
(p.92)

The model Tinto developed to depict his theory on college

dropout decisions emphasized two main areas of integration: the

academic and social systems (see Figure 1 on p.3). These areas

of integration have been verified as causes of college dropouts

and as explanations for college student persistence (Bayer, 1968;

Denzin, 1966; Medsker & Trent, 1968; Rootman, 1972; Scott, 1976;

Spady, 1971).














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Tinto states that social integration occurs primarily

through informal peer-group associations, semi-formal

extra-curricular activities, and interaction with faculty and

administration within the college. Tinto's theoretical model

implies that successful social integration, via the above means,

results in increased retention of students in an educational

institution. Tinto stated:

Successful encounters in these areas result in varying
degrees of social communication, friendship support,
faculty support, and collection affiliation, each of
which can be viewed as important social rewards that
become part of the person's generalized evaluation of
the cost and benefits of the college attendance and
that modify his educational and institutional
commitments. Other things being equal, social
intergation should increase the likelihood that the
person will remain in college. (p. 107)

Pascarella and Chapman (1983), using 2,326 freshmen from 11

postsecondary institutions, and Pascarella and Terenzini (1983),

using a longitudinal study with three data collections and a

sample of 763 freshmen, verified the direct influence of social

integration on college dropouts as theorized by Tinto. These

studies were conducted in four-year residential schools. However

when Tinto's model was applied to both four and two-year commuter

schools, the results were non-supportive (Pascarella & Chapman,

1983; Pascarella, Duby, & Iverson, 1983). Pascarella and Chapman

(1983) found no direct nor indirect effects of social integration

on persistence in four or two-year commuter institutions. In

addition, Pascarella, Duby, and Iverson (1983), using 269 in-

coming freshmen, reported a negative direct effect of social







5




integration on persistence in a commuter school. This negative

effect was also reported in a residential school by Terenzini,

Pascarella, Theophilides, and Lorang (1983).

Even though social integration variables have been shown to

affect dropout decisions in particular institutions, the

application of Tinto's model across all institutional types is

still problematic. Further research is needed to verify the

influence of social integration variables, specifically

peer-group and faculty-student interaction, on college student

persistence as it relates to different types of postsecondary

institutional settings.

Tinto's Model

In the theoretical model of dropout decisions in college

diagrammed in Figure 1, Tinto suggests

the process of dropout from college can be viewed as a
longitudinal process of interactions between the
individual and the academic and social systems of the
college during which a person's experiences in those
systems (as measured by his normative and structural
integration) continually modify his goal and
institutional commitments in ways which lead to
persistence and/or to varying forms of dropout. (p.
94)

Individuals enter institutions of higher education with

background characteristics, pre-college experiences, a variety of

individual attributes, and family backgrounds, each of which has

a possible direct and/or indirect impact upon their performance

in college. In addition, these background characteristics and

individual attributes also influence the development of the











educational expectations (goal commitments) and commitments the

individual brings into the college environment (institutional

commitments). These goals and institutional commitments serve

both as predictors and reflections of the person's successes and

failures in the collegiate setting.

Tinto's model further suggests that if background

characteristics and commitments are given, then the individual's

integration into the academic and social systems of the college

is the factor that most directly affects the student's

continuance in that college. Tinto (1975) states, "Given prior

levels of goal and institutional commitment, it is the person's

normative and structural integration into the academic and social

systems that lead to new levels of commitment" (p. 96).

According to Tinto's model, other things being equal, the

higher the degree of integration of the individual into the

college system, the greater will be the student's commitment to

the goal of college completion. Through the model Tinto implies

that if preceding variables can be held constant, such as prior

college characteristics and/or experiences and commitment, then

academic and social integration will contribute to the

persistence of a student in college. According to Tinto, if

academic system variables could be controlled for, then social

system variables, specifically peer-group interaction and

faculty-interaction, would contribute to and explain the

persistence of a student in college.












There is adequate research to justify Tinto's inclusion of

social systems into his model of retention. Peer-interaction has

been shown to be an important variable in a student's decision to

stay in college (Denzin, 1966; Pancos & Astin, 1968; Slocum,

1956; Spady, 1970). Spady (1971) used a sample of 683 students

who entered the University of Chicago as freshmen in September

1965 to study interpersonal relations. He concluded that

interpersonal relationships accounted for over 12 percent of the

explained variance in social integration for the men and nearly

20 percent for the women.

The quantity and/or quality of faculty interaction has been

demonstrated as an important variable in the retention of

students in colleges (Centra & Rock, 1971; Cesa, 1980; Noel,

1976; Pascarella & Terenzini, 1976; Spady, 1971). Pascarella and

Terenzini (1977) used a sample of 536 students at Syracuse

University, to test Tinto's theoretical model of attrition.

Under discriminant analysis, Pascarella and Terenzini concluded

that informal student-faculty contact is a significant predictor

of college persistence with significant F-ratios being found on

three of the six faculty interaction categories.

Other things being equal, the greater the college student's

level of social and academic integration, the greater his or her

subsequent commitment to the institution and commitment to the

goal of college graduation, respectively. These subsequent












commitments, in turn, are seen, along with levels of integration,

as having a positive influence on persistence.

As suggested by Tinto's model, the student's social system

is an important part of the process that leads toward an

individual's decision to persist or dropout of college.

According to research, peer-group interaction and faculty-student

interaction have a unique contribution to student social systems

and student retention, but this may not apply across all

institutional types. Additional research needs to concentrate on

the influence of social system variables, such as peer-group and

faculty-student interaction, on college student dropout in both

residential and commuter institutions.

In order to determine the influence of social system

variables on the dropout decision, all other preceding and

related variables such as family background, individual

attributes, pre-college schooling, commitments, and academic

system need to be held constant. If this is not done, then one

cannot assume that social system variables alone contribute to

the student's decision to either leave school or remain.

This dissertation controlled for those variables in Tinto's

model, background characteristics, commitments and academic

system, while investigating the relationship between social

system variables and college student retention in a two-year

commuter community college.












Statement of the Problem

A problem facing community colleges today is high student

attrition or drop out rates. There is a need to investigate what

variables relate to community college student attrition in order

to better understand and prevent the dropout process.

Using Tinto's (1975) conceptual framework, the purpose of

this study was to determine what relationships exist between

social system integration variables (peer-group interaction and

faculty-student interaction) and students dropout decisions in a

two-year community college. The researcher hoped that the

results of this study would then be used by community colleges to

develop new programs designed to reduce student attrition and

subsequently enhance support for these colleges.

Hypotheses

The following null hypotheses were tested (alpha level .05):

Hypothesis 1. A significant proportion of the variation in

student dropout rates is not explained by selected social

system variables after controlling for student background

characteristics, student commitments, and the student

academic system (student grade performance and student

intellectual development).

Hypothesis 2. A significant proportion of the variation in

student dropout rates is not explained by peer-group

interaction after controlling for student background

characteristics, student commitments, the academic system,

and faculty-student interaction.












Hypothesis 3. A significant proportion of the variation in

student dropout rates is not explained by faculty-student

interaction after controlling for student background

characteristics, student commitments, the academic system,

and peer-group interaction.

Hypothesis 4. There is no interaction effect between peer-group

interaction and faculty-student interaction.

Hypothesis 5. There is no significant difference between white

and non-white student population measurements on the social

system variable.

Hypothesis 6. There is no significant difference between white

and non-white student population measurements on the

peer-group interaction variable.

Hypothesis 7. There is no significant difference between white

and non-white student population measurements on the

faculty-student interaction variable.

Hypothesis 8. There is no significant difference between male

and female student measurements on the social system

variable.

Hypothesis 9. There is no significant difference between male

and female student measurements on the peer-group

interaction variable.

Hypothesis 10. There is no significant difference between male

and female student measurements on the faculty-student

interaction variable.












Hypothesis 11. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the social

system variables.

Hypothesis 12. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the

peer-group interaction variable.

Hypothesis 13. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the

faculty-student interaction variable.

Hypothesis 14. There is no correlation between student semester

hours completed and the social system variable.

Hypothesis 15. There is no correlation between student semester

hours completed and the peer-group interaction variable.

Hypothesis 16. There is no correlation between student semester

hours completed and the faculty-student interaction

variable.

Hypothesis 17. There is no correlation between student age and

the social system variable.

Hypothesis 18. There is no correlation between student age and

the peer-group interaction variable.

Hypothesis 19. There is no correlation between student age and

the faculty-student interaction variable.












Assumptions

The assumptions for this study were as follows:

1. The testing of some of the hypotheses relied on

self-reported data. Systematic error caused by method bias,

therefore, may have affected any relationships that have been

confirmed or questioned. However, there was evidence that

suggested that one's perception of social integration most

directly relates to college persistence (Pervin, Reik, &

Dalrymple, 1966; Rootman, 1972; Spady, 1971). This research was

relevant since the responses on the instrument used in this study

were based on the student's perception.

2. It was assumed the dropout rate for Associate of Arts

and Associate of Science degree seeking students would be

approximately 30 percent.

3. Decisions to remain in school or drop out are tentative

decisions and therefore conclusions derived from such data should

be considered in the same reference.

Delimitations

This study was confined to the student population of Pasco

Hernando Community College, a tri-campus college located in Dade

City, Brooksville, and New Port Richey, Florida.

Limitations

1. The ex post facto design of the study and the fact that

questionnaires were administered only once precluded advantages

inherent in experimental designs. The researcher was not able to












control all extraneous variables and to manipulate independent

variables.

2. The results of the study were interpreted within the

limitations imposed by the validity and reliability of the survey

instrument used in the investigation and the decisions made

concerning which items to include in the constructed scale scores

for each variable.

3. The generalizability of the findings was limited because

the subjects were not selected randomly from the total population

of two-year college students. They were randomly selected from

within the population of degree seeking students enrolled at

Pasco-Hernando Community College for the Fall term of 1984. Even

though Pasco-Hernando Community College students were felt to be

representative of other community college students, further

empirical study must determine the extent to which the findings

will be applicable in other two-year colleges or other

educational institutions.

4. Subjects were limited to students who had declared

programs on the Pasco-Hernando Community College Program

Declaration form (see Appendix A), of either an Associate of Arts

or Associate of Science degree. This assured at least a minimum

commitment to a college education by the students. This

eliminated students from the sample who declared undecided,

certificate program, vocational certificate program, or personal












objectives as their anticipated goal. By eliminating these four

groups, potential dropouts would not be eligible for the sample,

and therefore would limit the generalizability of the findings.

5. The dropout rate for degree seeking students in this

study was approximately 15 percent. This low dropout rate plus

the small sample size from each individual campus may limit the

validity of some of the statistical analysis.

6. Because of the large number of tests of hypotheses (92)

it might be expected, due to the error rate, that at least one

hypothesis might be found statistically significant in reference

to any given campus.

Significance of the Study

Academic failures are generally accepted as a category of

dropouts from educational institutions. There is a second

category of students, although academically capable, who lack

forms of personal and/or social qualities that prevent them from

becoming properly integrated into the college social environment.

Noel (1976), reporting on the findings of a national seminar on

retention, stated that the seminar group realized the need to

study the interaction between students and their institutional

environment. The University of California, Los Angeles, Academic

Advancement Program has also identified difficulty in adjusting

to campus life as one of the central areas of students' problems

(Moore, 1976). Edwards and Waters (1983) also suggested that lack

of satisfaction with the non-academic part of college could

contribute to students dropping out.












More could be done in two-year colleges toward both

redirecting non-persisters and increasing important recruitment

markets for student enrollment. There exists a great need in

community colleges to service all students who enter. Student

retention should not be promoted to the extent that students see

leaving community college as a failure. Students should feel

comfortable to come and go as they please (Hahn, 1974). There is

a need, however, to provide structured programs to assure that

potentials are realized by both students and the institution.

Students should be given every opportunity to become socially and

academically integrated into an existing college environment.

Programs presently exist that attempt to improve on those

personal and social qualities that are advantageous for social

integration into the college environment. Meyer (1975) concluded

the following concerning the impact of a human development course

on community college students: (a) a human development course can

have a significantly positive impact on college students'

self-esteem, definiteness about self, and sense of purpose and

meaning in life; (b) participation in a human development course

can significantly strengthen students' interpersonal feelings,

particularly feelings toward others; and (c) the human

development course is strongly endorsed by participants as being

personally relevant and meaningful. Similar findings supporting a

human relations-type course by actual participants were reported












by Wall (1979). Recent evidence of programs designed to improve

retention through improving the degree of social integration has

been cited by Beck (1980).

In light of the expressed need to retain students, and

considering the importance of student retention to the sustenance

of institutional vitality, the investigation of Tinto's

theoretical model of retention, specifically, social system

integration (peer-group and faculty-student interaction) and how

it related to dropout decisions in a two-year commuter

institution seemed appropriate. This study contains a description

of the contributions made by peer-group interaction and/or

faculty-student interaction variables toward the process of

dropout decisions described by Tinto (1975). Information provided

by this research should encourage educational institutions to

investigate whether single retention models are applicable to any

one institutional type or if a combination of theoretical models

might be more advantageous.

Definition of Terms

The following definitions were cited from Tinto (1975). A

complete operational definition of each term is provided in

Chapter 3.

Academic integration. Meeting certain explicit standards of

the academic system (grade performance) and identification with

the norms of the academic system (intellectual development).












Academic system. The combined effects of grade performance

and intellectual development on the student.

Actual dropout. Students who did not return the following

term

Background characteristics. Extraneous variables

characteristic of individual students, i.e., family background,

individual attributes, and pre-college schooling.

Commitment. A degree of obligation to a goal or

institution.

Dropout decision. The perceived intent of individuals'

educational plans or the actual decisions to drop out of an

institution.

Faculty-Student interaction. The degree to which students

evaluate both the quantity and quality of their relationships

with their instructors.

Family background. The highest level of formal education

obtained by a student's parent or parents.

Goal commitment. The degree of commitment to complete a

declared college program.

Grade performance (college). The grade point average (GPA)

of a student's academic performance.

Individual attributes. Academic ability characteristics

possessed by the student prior to entering college.

Institutional commitment. The educational expectations

involving specific institutional components which predispose the

student toward attending one institution rather than another.












Intellectual development. The self-perceived growth of a

student in the areas of: general knowledge, reasoning skills,

critical thinking skills, and appreciation of new ideas.

Peer-Group interaction. The degree to which a student

perceives an institution as being receptive socially and the

degree the student feels accepted by the institution. Also the

degree to which a student feels other individuals demonstrate

accepting behaviors and to what degree a student feels accepted

by others.

Pre-College schooling. Characteristic of the school setting

that students were exposed to prior to entering college.

Social system. The combined effects of peer-group

interaction and faculty-student interaction on the students'

integration into the social setting of an institution.

Social integration. The degree of social communication,

friendship support, faculty support, and collective affiliation

students perceive they possess in a social environment.

Organization of Remainder of the Research Report

The following chapters are utilized in the remainder of the

research report. Chapter Two discusses dropouts in general and

additional research and literature that were pertinent to the

investigation. Chapter Three contains the procedures used to

formulate the survey instrument, the pilot study, along with the

complete methodology used in the study. Three campuses of a







19




multi-campus community college were surveyed. Multiple

regression was used to analyze the main hypotheses of interest.

The findings and analysis of data are presented in Chapter Four.

Chapter Five includes a summary of the findings and the

conclusions drawn as a result of the study, as well as

implications for practices and further research.
















CHAPTER TWO

REVIEW OF THE LITERATURE AND RELATED RESEARCH

Postsecondary institutions are facing a serious situation

that has a number of important implications for institutions as

well as students. Considering the economic times and the

evolving demographics of student populations, there has been an

increased interest in research studies concerning student

retention. Until recently little attention has been directed to

the underlying dynamics of the phenomenon of student withdrawal,

rather the main emphasis has been theoretical and descriptive.

A number of theoretical papers (e.g., Bean, 1981; Spady,

1970; Tinto, 1975) have developed conceptual models. These

studies have made an important contribution to our understanding

of dropout behavior in postsecondary institutions. These models

provide both a comprehensive and an explanatory view of attrition

which provides direction to researchers confronted with the

problem of student dropout.

Tinto's (1975) schema has generated perhaps the most

extensive body of research. Using the work of Spady (1970),

Tinto has developed a longitudinal model which attempts to

explain the persistence/withdrawal process in postsecondary

education. This process is largely based on the degree of

personal fit between the institutional environment and the

20












individual student. The concept of personal-institutional fit as

an explanatory concept for student dropout has created much

interest in postsecondary research (Aitken, 1982; Baumgart &

Johnstone, 1977; Bean, 1981). It would follow then that the

validity of Tinto's (1975) model has been the focus of recent

research (Pascarella & Chapman, 1983; Pascarella, Duby, &

Iverson, 1983; Pascarella & Terenzini, 1983; Terenzini,

Pascarella, Theophilides, & Lorang, 1983).

Pascarella and Terenzini (1980) generally supported the

predictive validity of the major dimensions of the Tinto model

after sampling 763 students at Syracuse University. By adding

five institutional integration scales to a discriminant analysis

based on fourteen pre-college characteristics, freshman year

academic performance, and extracurricular involvement, they were

able to increase the correct identification of persisters and

dropouts from 58.2 percent to 81.4 percent.

Additional support for Tinto's model was reported by

Terenzini, Pascarella, Theophilides, and Lorang (1983) in which

an earlier path analytic study (Pascarella & Terenzini, 1983) of

the predictive validity of Tinto's theory of college student

attrition was replicated. The study by Pascarella and Terenzini

(1983) produced 24 significant paths in Tinto's model and

Terenzini, Pascarella, Theophilides, and Lorang (1983) identified

22. Sixteen or 72.7 percent of these paths were common to the

two studies. Both institutions were large, comprehensive,












research-oriented universities, with undergraduate enrollments of

approximately 11,000. The first institution (Pascarella &

Terenzini, 1983) was an independent residential, private

institution and the other was a public residential institution.

Pascarella, Duby, and Iverson (1983) partially verified

Tinto's model using a sample of 269 students from an urban,

commuter university setting, rather than a residential setting.

They suggested that when applied to a commuter institution sample

not all dimensions of Tinto's model functioned according to

expectations.

The validity of Tinto's model appears to be generally

accepted, particularly in reference to residential settings. In

addition, individual variables in Tinto's model appear to have

predictive and explanatory power concerning dropout decisions.

Despite this growing body of research on persistence/withdrawal

behavior in colleges and universities, there lacks sufficient

interest in two-year, community college commuter institutions.

Thus a major purpose of this study was to assess the relationship

between social integration variables and community college

student retention using Tinto's (1975) conceptual framework.

Review of the Literature

Research in the past has generally come to the same

conclusions concerning the particular characteristics of students

who dropout from college. Dropouts generally (1) lack direction

(Summerskill, 1962) and plans for the future (Pancos & Astin,












1968; Wessell, Engle, & Smidchens, 1978); (2) lack institutional

commitment (Gottfredson, 1982; Hackman & Dysinger, 1970); (3)

lack interpersonal orientation and friendship support to some

degree (Astin, 1964a; Fiedler & Vance, 1981; Medsker & Trent,

1968; Spady, 1971; Yourglich, 1966); (4) have less success in

academic areas (Aitken, 1982; Baumgart & Johnstone, 1977; Slocum,

1956); (5) lack either insight and/or capacities for

self-analytic, critical thinking or reject these processes as

important parts of their personality (Daniel, 1963; Faunce,

1966); (6) lack acceptance of themselves to some degree (Lavin,

1965; Stevens, 1956); (7) are less conforming, flexible, or

adaptable (Gurin, Newcomb, & Cope, 1968; Stern, Stern, & Bloom,

1956; Summerskill, 1962); and (8) possess fewer social skills

that provide for positive social integration (Bourn, 1976; Spady,

1971; Tinto, 1975).

Of the many variables associated with attrition, two

particularly stand out: social integration and academic

integration (Spady, 1971; Tinto, 1975; Wider, 1981). The degree

and the direction to which these variables affect college student

retention varies. This variation is partially dependent on the

type of institution under investigation (residential or commuter)

and the uniqueness of the individual study (Pascarella & Chapman,

1983; Pascarella, Duby, & Iverson, 1983; Terenzini, Pascarella,

Theophilides, & Lorang, 1983).












Validity of Tinto's Model in Residential Settings

Research findings related to Tinto's (1975) model by

Pascarella and Terenzini (1983) concluded that

persistence/withdrawal behavior is essentially the result of a

longitudinal process of person-environment fit as theorized by

Tinto. Specifically, background characteristics and

institutional commitments explained little variance in

persistence with reported R2 increases of only .9 percent and 1.3

percent respectively. With alpha levels set at .01, significant

R2 increases occurred with the addition of the academic and

social integration scales. Therefore, both academic integration

and social integration had a direct influence on persistence.

Terenzini, Pascarella, Theophilides, and Lorang (1983)

support the major constructs and their causal linkages in Tinto's

model of college student attrition, with some noteworthy

exceptions. In comparing their study of a public, residential

school (study 2) with Pascarella and Terenzini's (1983) study of

a private, residential school (study 1), the following

differences were reported. In the second study the investigators

found that a significant and direct path was lacking between

students' level of academic integration, as was reported in the

first study and college persistence. This direct path was

present until subsequent institutional commitment was added to

the model. It is suggested that this non-significant direct path

may be artificial due to the fact that academic integration still

has a strong indirect effect on persistence.












Another discrepancy reported by study 2 was that the direct

path between social integration and persistence was marginally

reliable (p<.15) and the influence was negative. This finding

was in direct conflict with Tinto's theory and previous

research. Possible speculative explanations were provided by the

authors of study 2. They suggested excessive social involvement

may reduce time spent studying, and withdrawal due to the

student's recognition of poor academic performance was preferred

over academic dismissal. The authors emphasized the fact that

these were only speculations.

Study 2 confirmed findings in study 1 that indicated

students' background characteristics had no direct effect on

retention of students. Instead, background characteristics

influence was dependent on the student's interaction with the

institution and the student's experience in college.

Validity of Tinto's Model in Non-residential Setting

There is a growing body of research investigating the

appropriateness of Tinto's model in relationship to

non-residential schools. The research of Pascarella and Chapman

(1983) compared the validity of Tinto's (1975) model of college

withdrawal in three different types of institutions: four-year

residential institutions, four-year commuter institutions, and

two-year commuter institutions. The pooled analysis generally

supported a number of Tinto's theoretical expectations, but there

were variations between institutional setting types which were

relative to this study.












The major difference between residential institution and

commuter institution was the role played by academic and social

integration variables. The residential sample reported academic

integration having neither direct nor indirect effect on

voluntary persistence. Social integration was found to have a

significant direct effect on persistence. Conversely, in both

the four-year and two-year commuter institutions, social

integration had neither a direct nor indirect influence on

student persistence. Academic integration indirectly influenced

persistence through its direct effects on institutional

commitment.

The pooled analysis of this study suggest that Tinto's

model is potentially useful in predicting and explaining

persistence/withdrawal behavior. Under separate analysis,

results for different institutional settings may vary

substantially.

Another study concerning the efficacy of the

person-environment fit theory promoted by Tinto was conducted in

a non-residential school by Pascarella, Duby, and Iverson (1983).

Background characteristics were reported as having greater

influence on persistence than social integration. This apparent

influence was partially explained by the differences between

residential and commuter institutions. Commuter students'

environments were found to be generally less rich in terms of

social integration opportunities than residential students'












settings and in addition the students enrolled in these

institutions usually spent less time on campus (Chickering,

1974). From this research one could assume that the background

characteristics which the commuter student brings to college

might have a stronger direct impact on subsequent persistence

than the background characteristics of residential students.

Additional findings showed that academic integration had a

direct effect on persistence, a finding which was consistent with

several previous studies conducted in residential schools (Bean,

1980; Munro, 1981; Pascarella & Terenzini, 1983; Terenzini &

Pascarella, 1978). Social integration was found to have a

negative influence on persistence. This was inconsistent with

previous research in residential institutions (Pascarella &

Terenzini, 1983; Pascarella & Chapman, 1983) but supported the

findings of Terenzini, Pascarella, Theophilides, and Lorang

(1983).

A possible explanation for this negative influence was

given by the authors based on findings by Pascarella and Chapman

(1983). They concluded that students with high levels of social

integration tend to have high affiliation needs. Because of

these needs, these students may be more sensitive to the limited

opportunities for social integration satisfaction than their less

socially integrated counterparts. This may increase the chance

of the socially integrated student transferring to a residential

school in order to fulfill these affiliation needs.












Another possible explanation for this negative influence of

social integration is evidence suggested by Astin (1973) and

Chickering (1974). They reported that commuter college students

are a different population to begin with than residential college

students. These initial differences may be a significant factor

affecting the patterns of variables involved in the retention

process across commuter and residential institutions.

If these explanations are feasible, then what is the

possible flaw in Tinto's model that accounts for this negative

influence. As Pascarella, Duby, and Iverson (1983) suggested,

the flaw may not be in the model, but rather in the population to

which it is applied. When Tinto's model is applied to

residential schools, then Tinto's assumption that the institution

provides ample opportunities for social integration applies. But

when Tinto's model is applied to commuter school samples, the

social integration component of the model may have an influence

quite different from the initially hypothesized model.

Reconceptualization of Tinto's Model

The reported negative influence of social integration on

persistence of college students ( Pascarella, Duby, & Iverson,

1983; Terenzini, Pascarella, Theophilides, & Lorang, 1983) may

have important implications in reference to the association

between person-environment fit and college persistence.

Possibly, this person-environment fit only influences persistence

when institutions provide means for students to achieve social


integration.


P












Pascarella, Duby, and Iverson (1983) have revised Tinto's

model to better reflect their findings. Based on their research,

a reconceptualization of Tinto's model was offered (Figure 2

p.30). This revised model was intended to provide more

explanatory power in a non-residential institution.

The model assumes that the characteristics which students

bring to college will not only influence their interactions with

the college environment, but will also have important direct

effects on persistence. In Tinto's original model, these

characteristics were seen basically as determinants of students'

integration with the academic and social systems rather than

having any direct influence.

Even though social and academic integration were retained

as major elements of the model, some revisions were made.

Academic integration was hypothesized as having a direct

influence on persistence and an indirect effect through its

influence on goal commitment. This was consistent with Tinto's

model. The direct effect of social integration was hypothesized

to be either non-significant (suggested by Pascarella & Chapman,

1983) or negative. This departure of social intergrations'

influence from Tinto's model was based on two assumptions.

First, commuter schools generally provide fewer social

integration opportunities than residential schools and second

this fact may lead to a more complex relationship between social

integration and persistence than originally hypothesized by

Tinto.















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This reconceptualization of Tinto's model for use in

non-residential institutions needs to be tested across different

samples. Only a partial description of the model was included so

as not to imply a complete testing of its validity by the present

research investigation. Both models were included to provide the

reader with background information concerning existing research.

This present study mainly investigated the influence of social

integration on persistence in reference to Tinto's model.

Results obtained may, in addition, provide further information

that will enhance the promotion of the revised model of

Pascarella, Duby, and Iverson (1983).

Variables

In order to relate Tinto's model of retention and

corresponding literature to this investigation, it was necessary

to isolate and document characteristics and/or measurements that

most substantially represent the variables under consideration.

The following variables in Tinto's model of retention were

investigated for research support: background characteristics

(consisting of family background, individual attributes, and pre-

college schooling), commitments (consisting of goal commitment

and institutional commitment), academic system (consisting of

grade performance and intellectual development), social system

(consisting of peer-group interaction and faculty-student

interaction), and dropout decisions. The following sections

contain a review of the research in these areas.












Family background. The three most accepted characteristics

of family background were (1) socioeconomic status, (2) parental

education, and (3) quality of relationship.

Research has shown that the socioeconomic status of the

family is inversely related to student dropout rates from college

(Astin, 1964b; Brown, 1980; Pancos & Astin, 1968; Pascarella &

Terenzini, 1983). Even when intelligence was held constant,

children from lower status families exhibited higher rates of

dropout than did children of higher status families (Sewell &

Shah, 1967).

The educational status of the student's parents is another

variable related to dropout from college. The higher the level

of formal education by the parents the more likely the student

will persist in college (Chase, 1970; Jaffe & Adams, 1970;

Kowalski, 1982; Pascarella & Chapman, 1983; Pascarella, Duby &

Iverson, 1983; Ramist, 1981; Spady, 1971; Terenzini, Pascarella,

Theophilidles, & Lorang, 1983). Bennet and Bean (1983) found this

particularly true for black students.

Additional research has indicated that the quality of

relationships between parents and students is an important factor

related to dropout rates from college. The quality of

relationships not only includes the quality of communication

within the family but the expectations that parents and/or family

members have concerning the student's education (Bean, 1981).

College persisters' home environments tend to be characterized by











more open democratic, supportive, and less conflicting

relationships (Congdom, 1964; Trent & Ruyle, 1965; Willner,

1980). In addition, these parents expressed more interest and

offered more advice concerning college experience than

non-persisters' parents (Trent & Ruyle, 1965). Hackman and

Dysinger (1970) also confirmed that the greater the parental

expectations the more likely the student would remain in school.

Slocum, in his 1956 study, received a positive response from 81

percent of college persisters and only 35 percent from the

dropouts to the following question, "Do your parents want you to

finish college?"

Individual attributes. There are many individual

characteristics that could be correlated with dropout behavior,

such as personality traits and attitudinal differences. These

variables certainly should not be discredited concerning their

possible influence. Two particular characteristics have received

the most research support concerning their relationship to

student persistence in college: grade point average (GPA) in high

school and scores on a standardized test.

The grade point average in high school indicates the

students' ability and serves as a measurement of their past

success (Bean, 1982; Blanchfield, 1971; Chase, 1970; Coker, 1968;

Hutchenson, 1980; Jaffe & Adams, 1970; Lavin, 1965; Pancos &

Astin, 1968; Prather, 1982; Taylor & Hanson, 1979; Willner,

1980). Tinto (1975), Edwards and Waters (1982), and Pascarella












(1968) confirmed that GPA in high school is one of the best

predictors of college persistence. Tinto (1975) also supported

Astin's (1973) conclusion that measures of ability, as obtained

on a standardized test, are a significant predictor of college

persistence.

Pre-College schooling. Nelson (1972) suggested that the

characteristics of the high school attended by students were

important variables in determining the probability of a student

either persisting in college or dropping out. Two variables

confirmed as predictors of college persistence by Davis (1966),

Nelson (1972), and St. John (1971) were the students' ability

level and their social status composition in the school. These

two variables not only appear to affect the individuals'

perception of their own ability but also their expectations for

future college education. Additional research by Pascarella and

Chapman (1983) found students' percentile rank in high school and

high school GPA to be consistent predictors of college

persistence.

Institutional commitment. In researching the variables that

may influence an individual's decision to remain in school or

dropout, one would have to investigate to what extent an

individual was committed to a particular institution (Pascarella

& Chapman, 1983). A valid procedure would be to determine

whether specific institutional components exist that would

predispose a student toward attending one institution rather than

another (Pascarella & Chapman; Spady, 1970; Tinto, 1975).












Goal commitment. There seems to be little doubt that lack

of goals in life decreases our motivational drive; thus college

persistence depends on degree of career goals (Day, 1982;

Churchill & Iwai, 1981; Jacobs, Bringman & Friedman, 1982).

Previous research supports this statement: Slocum (1956)

emphasized the need for occupational plans; Summerskill (1962)

reported students need direction; Astin (1964b) implied" What to

study?" was the important question for college students; Wessell,

Engle, and Smidchens (1978) cited the need for a clear purpose

concerning educational persistence; Beck (1980) reported that an

important factor related to college dropout is inadequate

clarification; and Simpson, Baker, and Mellinger (1980)

demonstrated that voluntary withdrawals had less commitment than

persisters. Research reports that if students have some degree

of direction they are more likely to persist in college.

Grade performance. Researchers reported that grade

performance is an important variable in students' college success

(Avakian, MacKinney, & Allen, 1982; Bean, 1982; Edwards & Waters,

1983). Spady (1970) reported that grades are the single most

important factor related to persistence in college. Tinto's

(1975) synthesized research also confirmed the importance of

grade performance. There is little doubt that grades indicate to

what degree students are academically integrated into the college

environment (Creamer, 1980).












Intellectual development. Tinto (1975) stated that

intellectual development deals with intrinsic forms of reward;

this development is the individual's evaluation of the academic

system. Medsker and Trent (1968) referred to intellectual

development as the degree to which students value their college

education as a process of gaining knowledge and appreciating

ideas. Spady (1971) suggested that intellectual development is

exposure to stimulating ideas and experiences.

Though not as important as grade performance, intellectual

development was found to be an influencing variable in students'

decision to drop out (Rootman, 1972; Spady, 1970; Summerskill,

1962; Tinto, 1975). Tinto states,

Though grade performance and intellectual development
appear as separate components of a person's integration
into the academic system, it's clear that persons with
high grades are more likely to be high in measures of
intellectual development. (p. 106)

The distinction may be that grade performance is generally

measured objectively, whereas intellectual development is more

likely a subjective measurement.

Peer-Group interaction. Terms used to describe peer-group

interaction included friendship support (Flacks, 1963), social

fit (Rootman, 1972), supportive groups (Hanson & Taylor, 1970),

and normative congruence (Spady, 1970). In general, researchers

concluded if students perceive themselves as being accepted by

some form of peer-group, college persisters will be enhanced












(Baker, 1980; Beck, 1980; Simpson, Baker, & Mellinger, 1980;

Spady, 1970; Spady, 1971; Tinto, 1975). In addition to research

indicating that informal peer-group associations are related to

persistence (Gardiner & Nazari, 1983), semi-formal

extra-curricular activities were also related to students

persisting in college (Chase, 1970; Ramist, 1981; Spady, 1971).

Faculty-Student interaction. Social interaction with

faculty by students, in various forms and degrees, has been shown

to be related to persistence in college (Bean, 1982; Gardiner &

Nazari, 1983; Noel, 1976; Pascarella & Terenzini 1976; Penick &

Morning, 1982; Tinto, 1982). Additional research has concluded

that some types of interaction are more effective than others.

The strongest form of interaction appeared to be informal contact

concerning subject and/or career related material (Pascarella &

Terenzini, 1977). A general conclusion that has been drawn from

the existing research is that increased quantity and/or quality

of faculty-student interaction is advantageous to persistence in

college (Centra, 1971; Hutchenson, 1980; Keim, Van Allen, &

Anderson, 1982; Pancos & Astin, 1968; Reed, 1981; Slocum, 1956;

Spady, 1971; Tinto, 1975; Tinto, 1982).

Summary of the Chapter

Research has shown that social system integration,

peer-group interactions, and faculty-student interaction

variables can potentially affect whether students decide to

remain in school or drop out. According to Tinto's theoretical











model, the influences of these variables are dependent on

preceding and related variables, background characteristic,

commitments, and academic integration. The strength of the

research concerning social integration may lie in variables not

adequately under the researchers control such as type of

institutional setting. Additional variables not under the

researchers control are family background, individual attributes,

pre-college schooling, commitments, and academic system.

If the research on social integration is to be valid and

useful in the educational system, investigators must control

adequately for extraneous variables. Programs developed to

enhance the educational climate of students should be based on

the best available data on college student persistence.

Retention programs emphasizing human relations type courses

have been promoted in educational settings to improve individual

interpersonal skills and a sense of purpose in life (Meyer,

1975). Little (1971) and Wall (1979) found that a human

relations course significantly strengthened students'

interpersonal feelings, particularly feelings towards others. If

these courses and programs are successful, then according to the

research improved retention should be a by-product.

Recent evidence of programs designed to improve

interpersonal skills and therefore improve retention have been

cited by Beck (1980). He reported the following findings from

Lurleen B. Wallace Junior College: (a) the Human Potential












Seminar (HPS), which is part of the freshman orientation, has

proven to be a successful retention strategy; (b) the dropout

rate for HPS students was less than for students without HPS; (c)

follow-up studies, approximately one year later, showed the HPS

dropout rate was 15 percent, compared to 29 percent among those

without HPS; (d) on an evaluation questionnaire, 99 percent of

the students responded that the HPS was helpful. This research

supported the concept promoted by Tinto (1975) that peer-group

interaction and to some extent, faculty-student interaction are

important ingredients for social integration, and this

integration is advantageous to a successful retention program.

The important issue is whether the increased retention of

college students in these institutions is due to a cumulative

affect of many variables as Tinto suggested or whether programs

of this type can stand on their own merit as vital retention

programs. In addition, can the same results be expected

regardless of the type of institutional setting in which the

programs are being conducted, either residential or commuter.
















CHAPTER THREE

METHODOLOGY

Using Tinto's (1975) conceptual framework, the purpose of

this study was to determine what relationships exist between

social system integration variables (peer-group interaction and

faculty-student interaction) and student dropout decisions in a

two-year community college.

Instrumentation

The survey questionnaire developed for this research

investigation was formulated by this researcher using the most

recent and popular measurements of the variables under

consideration. The questionnaire provided measures of each of the

concepts in Tinto's (1975) theoretical model under investigation,

except for those provided by the institution: the students' grade

point average, number of college semester hours completed, the

actual dropout rate and the Guidance Placement Test scores

(Appendix B and C). In addition, the instrument obtained

information regarding demographic characteristics, i.e. social

security number, age, sex, and race. The instrument contains

forty-one items and appears in Appendix D.

Description of Student Survey

The Student Survey Questionnaire (Appendix D) provides

measures of five main areas under consideration: background

characteristics (family background; individual attributes;

40












pre-college initial commitments (goal and institutional);

academic system (academic grade performance and intellectual

development); social system (social peer-group interaction and

faculty-student interaction); and dropout decisions. In

addition, item 8 measures whether an individual has completed a

human relations type course. The specific breakdown by category

and item number follows.




Category Item Number

Social Security Number................................. 1
Age .............. .................................... 2
Human Relations Course............................... 8
Background Characteristics
Family Background
parental education............................ 7
Individual Attributes
sex........... ............................*.. 3
race.......................................... 4
Pre-college Schooling
high school percentile rank.................. 6 6
high school grade point average................ 5
Initial Commitment
Goal Commitment
highest expected degree....................... 9
importance of graduation....................... 11
Institution Commitment
rank of subject institution as choice......... 10
probability of transfer...................... 13
confidence of choice of subject institution... 12
Integration
Academic System
students' perceived intellectual development.. 15-21
perceived faculty concern.................... 22-26
faculty out-of-class contact (academic)........ 14(1,2,3)
Social System
student extracurricular activity............... 40
student-peer interaction.......... .......... 27-33
faculty-student interaction..................... 34-38
faculty out-of-class contact (social)......... 39(1,2,3)
Dropout Decisions
intent of future educational plans............ 41












Development of the Student Survey

The student survey utilized in this study was formulated

from the combined information received from the following

research:

A Multiinstitutional, Path, Analytic Validation of Tinto's
Model of College Withdrawal by E.T. Pascarella and D.W. Chapman
(1983);

A Test and Reconceptualization of a Theoretical Model of
College Withdrawal in a Commuter Institution Setting by E.T.
Pascarella, P.B. Duby, and B.K. Iverson (1983);

Predicting Voluntary Freshman Year Persistenece/Withdrawal
Behavior in a Residential University: A Path Analytic Validation
of Tinto's Model by E.T. Pascarella and P.T. Terenzini (1983);

and Path Analytic Validation of Tinto's Theory of College
Student Atrition by P.T Terenzini, E.T. Pascarella, C.
Theophilides, and W. G. Lorang (1983).

Variables

As presented in Figure 1, Tinto's model consists of five

major constructs or variable sets in a causal sequence: (a)

background characteristics (family background, individual

attributes, and pre-college schooling); (b) initial commitments

(goal commitment and institutional commitment); (c) integration

(academic system and social system); (d) subsequent goal and

institutional commitments; and (e) withdrawal decisions.

Five constructs, background characteristics, initial

commitments, academic system, social system, and withdrawal

decisions, were operationalized as follows. In addition the

measurements of the variables under consideration were selected

using the following criteria.












Background characteristics

The background characteristics' value for each student was

the sum of the Z-scores from family background, individual

attributes, and pre-college schooling divided by 3. These

Z-scores resulted from changing raw scores to standard scores,

adding a constant of 10, and expressing the scores in standard

deviation units. This approach of standardizing the scores was

used by Terenzini, Pascarella, Theophilides, and Lorang (1983)

and was adopted for this study to be consistent for comparison

purposes.

Family background. Parental education was the most

frequently used measurement of family background in the studies

reviewed. Two studies, Pascarella and Terenzini (1983) and

Pascarella, Duby, and Iverson (1983), used, in addition to

parental education, parental income and parental financial

support respectively. Neither of these measuremnets were used in

this study since the average age of PHCC students was 26 years

and they were considered adult learners.

Family background was a single variable, item 7, consisting

of the average of each parents' level of formal education. A

seven point scale was used with a value of 1 being assigned to

"some grammar school" to a value of 7 assigned to "graduate

degree." After dividing the total of both parents' score by 2,

this raw score was converted to a Z score or if only one parent's

education was reported, then the single score was converted to a

Z score, then a constant of 10 was added.












Individual attributes. Scholastic Aptitude Test (SAT) scores

were used in the majority of studies for. academic aptitude with

American College Test (ACT) scores being used in one additional

study. Since the majority of PHCC students do not take the SAT or

ACT tests, another standardized instrument was used to measure

academic aptitude. The Comprehensive Guidance Placement test

(English and Reading) is administered to virtually all entering

students at PHCC and was the instrument utilized. The

Comprehensive Guidance Placement test scores (English and

Reading) were furnished by the PHCC registrar. These two scores

were divided by 2 after being converted to Z-scores and adding a

constant of 10, resulting in a single Z score measurement for

individual attributes. Due to the variety of math competencies

of students entering PHCC, three different levels of exams must

be administered. These exams vary to such a degree, that for

standardization purposes the math scores were not used.

A few studies requested information concerning "major area

of study." The wording in these studies was inconsistent, and

these studies were conducted in four-year institutions, rather

than two-year; therefore this item was omitted as one of the

measurements of individual attributes.

Sex, item 3, was coded O=male and 1-female. Race, item 4,

was coded 0Owhite and I-non-white. To be consistent with

previous research these items were not included as measurements

of individual attributes. Both items are generally considered as

descriptive variables in reference to dropouts.












Pre-college schooling. The two most popular measurements of

pre-college schooling in the research were (a) students'

percentile rank in high school, item 6, and (b) indication of

high school grade point average or grade achievement, item 5.

Other variables, such as high school preparation (Terenzini &

Pascarella, 1983) and extracurricular activities in high school

(Pascarella & Terenzini, 1983), were used in previous research,

but their isolated usage eliminated them from consideration in

this research.

Percentile rank in high school used a seven ordinal category

assigning a value of 1 to "70% or below" through a value of 7 for

"top 10%," and the grade point average in high school used a

seven point scale assigning a value of 1 to "D or below" through

a value of 7 for "A/A+." Each score was converted into Z-scores,

adding a constant of 10, summed, then divided by 2.

Initial commitments

The commitment value was the sum of the Z-score of goal

commitment, plus ten, and institutional commitment, plus ten,

divided by 2.

Goal Commitment. Highest degree expected, item 9, and

importance of graduating from college, item 11, were consistently

used as measurements of goal commitment. A value of I was

assigned to "Associate of Arts/Science" through a value of 6 for

"LL.B. or J.D. (law)." In reference to importance of graduating,

a value of 4 was assigned to "extremely important"












through 1 for "not at all important." Each score was converted

into a Z-score, adding a constant of 10, -summed, then divided by

2.

Institutional commitment. The following were used by all or

a majority of the studies to measure institutional commitment:

(1) institutional rank as a college choice, item 10; (2)

probability of transferring before graduation, item 13; and (3)

confidence or satisfaction that choosing the subject institution

was the right choice, item 12.

A value of 4 was assigned to "1st choice" through a value of

1 for "4th choice" on item 10, a value of 5 to "SD" through I for

"SA" on item 13, and a value of 4 to "extremely confident"

through 1 for "not at all confident" on item 12. These three

values were converted to Z-scores, adding a constant of 10 to

each, summed, and then divided by 3.

Academic system

Academic system was operationalized as the sum of the

following scales or variables: (1) grade point average, provided

by the registrar; (2) a seven-item factorially derived scale

measuring a student's perceived level of intellectual

development, items 15-21; (3) a five-item, factorially derived

scale measuring a student's perception of faculty members concern

for student development and teaching, items 22-26; and (4) the

frequency of a student's out-of-class contact with faculty of 10

minutes or more for each of the following purposes: (a) "to get

basic information and advice about my academic program";












(b) "to discuss intellectual or course-related matters"; (c) to

discuss matters related to my future career", item 14(1,2 & 3).

The factorially derived scales were originally developed by

Pascarella and Terenzini (1980). Initially 55 items were

constructed and subsequently reduced to 34 items. The specific

factorially derived scales used in this study to meausre the

academic system were taken directly from Terenzini, Pascarella,

Theophilides, and Lorang (1983) and Pascarella and Terenzini

(1983). In these two studies an internal consistency (alpha)

reliability of .60 and .64, respectively, were reported for the

academic scale.

The above mentioned four variables were used in virtually

all research investigated. Value placement and/or Z score

conversions were as follows: (1) GPA was converted to a Z-score,

plus ten; (2) a value of 5 was assigned to "SD" through 1 for

"SA" for item 15 and the reverse order being used for 16-21. The

sum of these items was divided by seven and converted to a

Z-score, plus 10; (3) a value of 5 was assigned to "SA" through

1 for "SD" for items 32, 23, and 26 and the reverse values for

items 24 and 25. The sum of these items was divided by 5 and

converted to a Z-score, plus 10; (4) The sum of each of these

items was divided by 3 and the Z-score calculated.

The sum of these four Z scores, calculated from the raw

scores of the academic system variables, was divided by 4. This

quotient represented the academic system measurement.














Social system

Social system integration was operationally defined as the

sum of the Z-scores of peer-group interaction and faculty-student

interaction variables divided by 2. The factorially derived

scales used to measure peer-group interaction and faculty-student

interaction were originally developed by Pascarella and Terenzini

(1980). Terenzini, Pascarella, Theophilides, and Lorang (1983)

reported an internal consistency (alpha) reliability of .47 for

these items and Terenzini and Pascarella (1983) reported .46.

Peer-Group interaction. The vast majority of research

studies operationalized peer-group interaction as the sum of the

scores for (1) the number of hours spent per week in

extracurricular activities, item 40; and (2) a seven-item

factorially derived scale measuring the extent and quality of a

student's interaction with peers, items 27-33. Items 27-30 of

the peer-interaction question were assigned a value of 1 for "SD"

through 5 for "SA" and the values were reversed for items 31-33.

The total score was divided by 5 and converted into a Z-score,

adding a constant of 10. This Z-score was summed with the

Z-score conversion of the raw score for extracurricular

activities, then divided by 2.

Faculty-Student interaction. The majority of the research

studies operationalized faculty-student interaction as the sum of

the scores for (1) a five-item factorially derived scale

measuring the quality and impact of a student's out-of-class

contact with faculty, items 34-38, and (2) the frequency of











student non-classroom contact of 10 minutes or more with faculty

concerning personal and/or social matters, item 39(1, 2, & 3).

For the items concerning quality of faculty contact, a value of 5

was assigned to "SA" through 1 for "SD" for items 34, 36, 37, and

38. The reverse value assignment was used for item 35. The

frequency scores for items 39(1), 39(2), and 39(3) were summed,

divided by 3, then converted into a Z-score, adding a constant of

10. The frequency score was summed with the Z-score which was

the result of totaling the values from the items 34-38, dividing

by 5, then transforming into a Z-score, adding a constant of 10.

The sum of these two Z-scores was divided by 2, resulting in the

faculty-student interaction measurement.

Dropout decision

The majority of the research studies used an intent item

(intention of remaining in school) and official records from the

registrar to measure withdrawals. Dropout decisions, in this

study, was operationally defined as the student's perceived

educational plans for the future, item 41. Each student was

placed in a group according to his or her degree of intent to

persist as indicated by his or her selection of one of these five

options: (1) I plan on returning to PHCC next term; (2) I plan on

returning to PHCC but not necessarily next term; (3) I plan on

attending another institution next term; (4) I plan on attending

another institution, rather than PHCC, but not necessarily next

term; or (5) I am not planning to attend this or any other

institution anytime in the foreseeable future. These responses











were then converted to a dichotomously coded dependent measure

with response (1) indicating persistence (coded 1) and responses

(2), (3), (4), and (5) indicating withdrawal (coded 0). In

addition, the dropout decision variable was also operationalized

as actual persistence or non-persistence the following term based

on school records.

Four university professors reviewed the preliminary

instrument, Dr. Al Smith, Dr. Steve Olejnik, Dr. Gordon Lawrence,

and Dr. Paul Fitzgerald. These individuals were instructed to

take note of possible areas of revision in terms of clarity or

wording in instructions, possible ambiguity of items, and

relevance of items to the variables under consideration in this

research study.

Pilot study. The investigator conducted a pilot study to

determine the suitability of the instrument format and to provide

data for analysis of the items.

Subjects. The pilot sample consisted of a total of 40

students. Ten subjects were selected randomly from the East

Campus of PHCC, 10 subjects from the North Campus of PHCC, and 20

subjects from the West Campus of PHCC. The West Campus has a

student population approximately equal to the East and North

combined; therefore twice the number of subjects was required to

increase the generalizability of the pilot study findings. A

total of 38 usable surveys was returned. The survey












questionnaire proved to be an adequate and serviceable instrument

in investigating variables of interest.

The same two criteria for selection that were used in the

present study applied to the pilot study with the exception of

number of hours completed. In the pilot study students were

eliminated, as possible subjects, if they were within nine hours

of graduation, indicating a persister. These students from the

pilot study could graduate at the end the 1984 Summer term by

taking an acceptable load. Therefore, students were eliminated

from participating in the pilot study if they had accumulated more

than 50 semester hours.

Present Study

Subjects

The study sample consisted of a total of 200 students at

Pasco-Hernando Community College who were enrolled for the Fall

term of 1984. A total of 152 useable questionnaires were

received for a 76 percent response rate. Since the West Campus of

PHCC was approximately twice the size of either the East or North

campuses of PHCC, which were approximately equal in size, 100

students were sampled from this campus and 50 from each of the

remaining two campuses. A random selection process was used to

select subjects from all students who had declared an Associate

in Arts degree and/or Associate of Science degree on their

Program Declaration Form (Appendix A). This limitation (a)

assured relatively equal degree of commitment to the college on

the part of the students and (b) attempted to eliminate











confounding variables involved with individuals who might be

taking a limited number of courses to complete a certificate

program, vocational certification program, personal objectives

(i.e.,teacher recertification) or have declared themselves in the

category of undecided. The only other students who were excluded

from participation in the study were individuals who were within

15 semester hours of completing their degree program. These

students, by nature of their accumulated hours, were considered

persisters.

Data Collection

The survey questionnaire was distributed to the randomly

selected students, in their classes, on each of the three

campuses by their classroom instructors. This took place during

the eleventh week of the fifteen week term, three weeks after the

distribution of mid-term grades and one week after the last day

of official withdrawal from classes without penalty. Any

student, from the original sample, withdrawing prior to the

distribution date was contacted, by mail or personally, in an

attempt to complete the survey questionnaire. Each participating

student received in class a survey questionnaire (see Appendix D)

and was asked to complete the form in class as accurately as

possible. The instructions provided to the monitors are found in

Appendix E. All forms were received and then analyzed by the

researcher.











Data Analysis

The following null hypotheses were investigated:

Hypothesis 1. A significant proportion of the variation in

student dropout rates is not explained by selected social

system variables after controlling for student background

characteristics, student commitments, and the student

academic system (student grade performance and student

intellectual development).

Hypothesis 2. A significant proportion of the variation in

-student dropout rates is not explained by peer-group

interaction after controlling for student background

characteristics, student commitments, the academic system,

and faculty-student interaction.

Hypothesis 3. A significant proportion of the variation in

student dropout rates is not explained by faculty-student

interaction after controlling for student background

characteristics, student commitments, the academic system,

and peer-group interaction.

Hypothesis 4. There is no interaction effect between peer-group

interaction and faculty-student interaction.

Hypothesis 5. There is no significant difference between white

and non-white student population measurements on the social

system variable.

Hypothesis 6. There is no significant difference between white

and non-white student population measurements on the

peer-group interaction variable.











Hypothesis 7. There is no significant difference between white

and non-white student population measurements on the

faculty-student interaction variable.

Hypothesis 8. There is no significant difference between male and

female student measurements on the social system variable.

Hypothesis 9. There is no significant difference between male and

female student measurements on the peer-group interaction

variable.

Hypothesis 10. There is no significant difference between male

and female student measurements on the faculty-student

interaction variable.

Hypothesis 11. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the social

system variable.

Hypothesis 12. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the

peer-group interaction variable.

Hypothesis 13. There is no significant difference between

students who have taken a human relations type course and

students who have not on student measurements of the

faculty-student interaction variable.

Hypothesis 14. There is no correlation between student semester

hours completed and the social system variable.












Hypothesis 15. There is no correlation between student semester

hours completed and the peer-group interaction variable.

Hypothesis 16. There is no correlation between semester hours

completed and the faculty-student interaction

variable.

Hypothesis 17. There is no correlation between student age and

the social system variable.

Hypothesis 18. There is no correlation between student age and

the peer-group interaction variable.

Hypothesis 19. There is no correlation between student age and

the faculty-student interaction variable.

Multiple linear regression analysis was used to test

hypotheses 1-4. Hypotheses 5-13 were analyzed using a

t-statistic. Hypotheses 14-19 used a Pearson product moment

correlation. An alpha level of .05 was used in each case to

reject the hypothesis.

In all instances where scales operationalizing components of

the model were constructed from variables with different metrics

(e.g. academic and social integration), the same two-step

procedure was employed. First, each individual item or scale was

standardized to provide the same metric (Z score), and second, a

constant of 10 was added to eliminate negative numbers. The

scale was then formed by summing across the standardized items

(Armor, 1973-1974).











Multiple linear regression analysis was employed to

determine the incremental increase in the explained variance in

the persistence/withdrawal behavior (R2 increase) associated with

different variable sets in Tinto's model. The sets of variables

were entered in an a priori, hierarchical manner consistent with

the causal sequence of the model: (a) background characteristics

(family background, individual attributes, and pre-college

schooling), (b) commitments (goal and institution), (c) academic

system, (d) peer-group interaction, (e) faculty-student

interaction, and social system.

Summary of the Chapter

This chapter contains the methodological procedures used in

this investigation. The development of the survey questionnaire

was described and justified. Finally, this chapter contains a

description of subjects, data collection, and data analysis

techniques.

















CHAPTER FOUR

FINDINGS

The purpose of this study was to determine what relationship

exists between social system integration variables (peer-group

interaction and faculty-student interaction) and student dropout

decisions in a two-year community college. The investigation

used Tinto's (1975) conceptual framework model to guide the

research. The student's home campus, age, sex, race, total

semester hours completed, and whether a student had completed a

human relations type course were the demographic variables

considered. Background characteristics, commitment (goal and

institutional), academic integration, and social integration

(peer-group interaction and faculty-student interaction) were the

independent variables under investigation.

Two different measurements were used for the dependent

variable. The first dependent variable was students' perceptions

of whether or not they would return the following term. The

second dependent variable was whether the student actually

returned the next term. This was determined from the official

registration of Term II 1985. Even though the total dropout rate

was similar for both, 13.8 percent for dropout perception and

14.5 percent for actual dropout, the individuals differed

greatly. Of the 21 students who replied on the Student Survey

they would not be returning the following term, only 10

57












ultimately withdrew. This resulted in 52.4 percent change of

response. Of the 131 students who said they would return to PHCC

the following term, 119 actually did return; this resulted in a

9.2 percent change in students' decisions concerning dropout.

Therefore, two different dependent variables were independently

measured and analyzed: (1) students' perceptions of whether they

would return to Pasco Hernando Community College the following

term and (2) actual dropout rate the following term.

The researcher pilot tested the survey instrument to be used

in the study on students attending all three campuses of Pasco

Hernando Community College in the Summer term of 1984.

Permission was obtained from the administration of PHCC to run

the full study on the student body of PHCC the Fall term of

1984. The Student Survey (appendix D) was designed to obtain

information concerning the independent and dependent variables

under investigation.

The original intent of this study was to test 19 hypotheses

on the total population of 152 subjects. An additional

consideration of interest developed; specifically, was there

differences between the three individual campuses that comprise

the total population in reference to the 19 hypotheses. Because

of this concern a total of four different population groups was

tested.

This chapter describes the results of the study. First,

demographic data of the participants are presented and discussed.

Then results pertaining to each of the hypotheses under












investigation are described in terms of four groups: total campus

of PHCC, East Campus of PHCC, North Campus of PHCC, and West

Campus of PHCC. The four groups are discussed in reference to

the influence social integration, peer-group interaction,

faculty-student interaction, and the interaction of peer-group

and faculty-student variables had on dropouts with reference to

both dependent variables, perception of dropout decision, and

actual dropout decision.

Multiple linear regression was used to test each of the

first four hypotheses. Each of the four hypotheses was tested for

each of the population groups, total campus, East Campus, North

Campus, and West Campus, using first the students' perceptions of

their dropout decisions as the dependent variable then the

students' actual dropout rate. The total number of analyses was

32. The next nine hypotheses investigated whether there was a

difference between white and non-white students, male and female

students, and students who had taken a human relations course and

those who had not on the social system, peer-group interaction,

and faculty-student interaction variables. A t-test was used to

test these hypotheses. Each of the nine hypotheses was tested

using each of the four groups as separate populations. This

resulted in 36 different analyses. The remaining six hypotheses

investigated whether there was a relationship between accumulated

hours and age with social system, peer-group, and faculty-student

interaction variables. Each of the six hypotheses was tested

using each of the four groups as separate populations. This












resulted in a total of 24 analyses. The total number of tests

for the four separate groups was 92. A significance criterion of

.05 was used to reject each of the 19 hypotheses.

Finally, an ANOVA was used to analyze differences between

individual campuses on variables of interest. Variables that

resulted in a significant F-statistic were analyzed with a

computed Bonferroni-statistic. A .05 level of statistical

significance was used to indicate a difference.

Descriptive Analysis

A subprogram of the Northwest Analytical Statpak computer

program was used to calculate the frequencies and percentages for

the demographic variables. Other subprograms of the NWA were

used to calculate the ANOVA, t-statistic, correlation

coefficients, and multiple linear regression results. A total of

200 questionnaires were distributed with 152 useable surveys

being returned. This resulted in a 76 percent response rate

available for analysis.

Demographic Variables

The data regarding the demographic variables are presented

in Table 1. Inspection of Table I revealed the proportion of

usable responses from each of the three campuses was proportional

to the total student population attending those individual

campuses. The total population under investigation was 1146

students, East Campus (23 percent), North Campus (25.7 percent),

and West Campus (51.3 percent). All statistics

























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concerning the total population were obtained from the Office of

the Registrar. The sample consisted of 152 students, East Campus

(25.6 percent), North Campus (25.6 percent), and West Campus

(48.6 percent). There were slight variations in percentages

between the sample and the actual percentage enrollment figures

for the total population of each of the three campuses.

Slightly more than half of the respondents (54.6 percent)

were between the ages of 17 and 21. The remaining age groups and

percentages were, 22-26 (13.2 percent), 27-31 (13.8 percent),

32-36 (5.9 percent), 37-41 (3.9 percent), 42-46 (5.3 percent),

47-51 (1.3 percent), 52-56 (1.3 percent), and 57+ (.7 percent).

The mean age for the sample subjects was 25.1, which approximated

the mean age of the total student population of 26.

The females out-numbered the males slightly better than two

to one, with 67.1 percent of the respondents being female and

32.9 percent being males. These percentages are comparable to

the total population, which contained 61.5 percent females and

38.5 percent males. Each of the three campuses was represented

by percentages that were within 5 percent of the percentages of

their respective total populations.

The white and non-white participants showed the same

proportional trend that was reported for the different sexes.

The sample population of 93.4 percent white and 6.6 percent

non-white was within 2 percent of the total college student

population of 5.4 percent non-white and 94.6 percent white.

Different percentages were reported for each campus, but these












differences adequately reflected the percentages of white and

non-white students attending those individual campuses.

The percentage of students, in the sample, who had had a

human relations type course was 38.8 percent. Similar

percentages were found on the East and West campuses, 38.5

percent and 36.5 percent respectively. A higher number of

subjects had a human relations type course on the North Campus

(43.6 percent). Even though accurate records were not available

for the total population, in reference to this variable, this

researcher's general impression was that similar participation

had occurred for the total population.

The next item listed in Table 1 revealed the frequency range

of accumulated credit hours. Students with 1 to 9 hours account-

ed for (28.2 percent) of the total population, 10 to 18 (28.9

percent), 19 to 27 (18.4 percent), 28 to 36 (11.1 percent), 37 to

45 (7.8 percent), 46 to 54 (4.6 percent), and 55+ (.6 percent).

Differences appeared in accumulated semester hour frequency

figures between campuses. The total campus and East Campus had

similar percentages of students with less than 28 semester credit

hours accumulated, 75.5 percent and 76.8 percent respectively .

These percentages indicated a larger number of freshmen in

attendance than sophomores. West Campus had an even larger

proportion of freshmen with 85 percent. North Campus appeared to

have the most balanced freshmen and sophomore classes with 56.3

percent of the students having less than 28 semester hours

accumulated.











The mean for accumulated semester credit hours for the

sample was 19.0 which approximated the total population mean of

20.2. This slight difference may have been attributed to the

fact the sample had a limit on the maximum number of accumulated

hours a student could have in order to be eligible for the

study.

The last variable listed was dropout decision, both the

students' perceptions and actual dropout decision. The number of

individuals who perceived themselves as not returning was 21.

This was very close to the actual dropout rate of 22. The range

between campuses was 3.2 percent for the perceived decision and

5.9 percent for the actual decision. East Campus was very

consistent with 15.4 percent recorded for both perceived decision

to drop out and actual dropout decision. North Campus lost two

fewer students than perceived which decreased their perceived

percentage from 15.4 percent to a 10.3 actual dropout

percentage. West Campus lost three more students than

anticipated which increased their percentages of dropouts from a

perceived dropout rate of 12.2 percent to an actual dropout rate

of 16.2 percent.

Additional statistics of comparative value, which are not

recorded in Table 1, were the English and reading scores from the

Guidance Placement Test (Appendices B and C). These entrance

tests reflected students' ability in reading comprehension and

English usage. The total college population mean for reading was

24.7 and 25.1 for the sample under consideration. The











total college population mean for English was 26.5 and 26.8 for

the sample. These data, combined with the demographic

information in Table 1, reflected very similar data between the

sample and the total population under consideration.

Correlations

Pearson product moment correlations for all variables under

investigation for the sample are shown in Table 2. Correlations

for East Campus are listed later in Table 3, North Campus Table

4, and West Campus Table 5. The dichotomous variables were coded

as follows: persisters 1, withdraws 0; males 0, females 1; white

students 0, non-white 1; and having a human relations type course

1, not having the course 0.

Most of the intercorrelations for total campus were

non-significant. Only fourteen, out of 91 correlations, were

found to be significant at the .05 level. Because retention was

the dependent variable the two significant correlations relating

to retention are presented first. The higher one's background

support scores, the more likely one would actually remain in

school (r=.197). The only other variable relating to actual

dropout rate was perception of dropout decision and it showed a

positive correlation (r=.377) with the actual dropout rate. The

following correlations are presented in the order in which they

appear in Table 2. Older students seemed to be academically

integrated to a greater degree than younger students (r-.272).

More females had had a human relations type course (r--.691), and

were more committed than males (r=.206). The more

























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credit hours a student accumulated, the higher were the scores on

the three measurements that comprised background characteristics

(r=.194) and the more likely the students were to have had a

human relations type course (r-.384). The following

relationships were found to have a positive correlation with

academic integration: commitment (r=.296), peer-group interaction

(r=.208), faculty-student interaction (r=.415), and social

integration (r=.200). Peer-group interaction also had a positive

correlation with faculty-student interaction (r-.318) and social

integration (r-.575). Finally, faculty-student interaction was

positively correlated with social integration (r=.612).

East Campus

Among the 78 correlations related to the East Campus, only

eight were significant at the .05 level (see Table 3). The two

statistically significant correlations relating to the dependent

variable are presented first. The higher the academic

integration the more likely the students were to actually stay in

school (r=.446). Second, females perceived themselves as

returning to school more often than males (r=.486). The

remaining six statistically significant correlations are

presented in the order in which they appear in Table 3. Female

students scored higher on the peer-group interaction scale

(r=.357) than male students. The more credit hours accumulated

by a student indicated a greater likelihood of a student taking a

human relations type course (ri.476). The more a student

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the higher the tendency for academic integration (r=.360).

Peer-group interaction was positively correlated with

faculty-student interaction (r=.506) and both peer-group

interaction (r=.522) and faculty-student interaction (r-.512)

were correlated with social integration in a positive direction.

North Campus

Eleven of the 78 correlations involving North Campus

students were found to be significant at the .05 level (see Table

4). There was only one statistically significant correlation

involving dropout rate at this level. Students' perceptions of

dropout decisions were positively correlated with actual dropout

decision (r=.324). The remaining 10 correlations are presented in

the order in which they appear in Table 4. Older students tended

to have lower levels of background characteristics (r--.511) and

females appeared more committed (r-.379) than males. A human

relations type course was more likely to be taken by students

with more accumulated credit hours (r=.340). Those students with

higher peer-group interaction scores (ri-.384) and social

integration scores (r=-.399) were less likely to have taken a

human relations type course. Students with higher academic

integration had higher levels of faculty-student interaction

(r=.482) and social integration (r=.341). Peer-group interaction

was positively related to both faculty-student interaction

(r-.385) and social integration (r-.836). Faculty-student

interaction was also related to social integration in a positive

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West Campus

West Campus had the highest number of statistically

significant correlations of the three campuses with 15, out of

78, being significant at the .05 level (see Table 5).

The only statistically significant correlation related to

the dependent variable was background characteristics. The

higher the student's level of background characteristics the

more likely a student was to persist (r-.288). The remaining 14

correlations are presented according to the frequency a

particular variable achieved statistical significance. Levels

of academic integration correlated positively with levels of

background characteristics (r=.233), age (ri.339), degree of

student commitment (r=.285), peer-group interaction (r-.325),

faculty-student interaction (r=.549), and social integration

(r-.545). Peer-group interaction correlated positively with

levels of student commitment (r=.237), faculty-student

interaction (r=.254), and social integration (r=.809). Social

integration was correlated positively with levels of commitment

(r-.287) and faculty-student interaction (r-.772). Number of

accumulated hours correlated positively with levels of

background characteristics (r=.270) and students who took a

human relations type course tended generally to have more

accumulated credit hours (r-.357). Female students had a higher

level of commitment than male students (r=.275).























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As might be expected the peer-group interaction,

faculty-student interaction, and social integration variables

were all highly correlated. This is understandable since

peer-group interaction and faculty-student interaction variables

comprise the social integration variable. Only two variables

were significantly correlated with actual dropout rates. For

the total and West campuses the higher the student's background

characteristics the more likely the student would persist. East

Campus students with higher academic integration levels were

more likely to persist. The remaining statistically significant

correlations between the variables under study showed a variety

of relationships. These relationships indicated various degrees

of support for Tinto's inclusions of these variables in his

model.

Regression Analysis

Tinto's conceptual model considered in this study was

given in Figure 1 (see page 3).

Test of Hypotheses 1-4

Hypothesis 1. A significant proportion of the variation

in student dropout rates is not explained by

selected social system variables after controlling

for student background characteristics, student

commitments, and the academic system.

The test of the full model was a test of the regression

coefficients background characteristics, commitments, academic











2
system, and social system. The full model yielded an R2 of .022

with an F-statistic of .835 which was not significant at the .05

level. The test of this hypothesis was a test of the partial

regression coefficient for the social system variable given that

background characteristics, commitments, and academic system

were in the model. The results of the analysis are presented in

Table 6.

For the total campus when the dependent variable was

students' perceptions of dropout decision, the R2 with all

variables in the model was .022. Without social system in the

model it was .021. Thus adding the social system variable

explained .1% additional variation in perceived dropout. This

increase in variation resulted in a computed F-statistic of

.192, which did not exceed the critical F-statistic at the .05

level. Therefore the conclusion was to fail to reject

Hypothesis 1. The social system variable does not help predict

dropout rate.

The full model for East Campus resulted in an R of .185

with an F-statistic of 1.933, which was not significant at the

.05 level. The R2 increase and computed F-statistic for East

Campus for the partial regression coefficient were .062 and

2.569. This was not significant at the .05 level.
2
The full model for North Campus yielded an R of .029 with

a non-significant F-statistic of .253 at the .05 level. The

partial regression coefficient had an R increase of .024 and an
partial regression coefficient had an R increase of .024 and an













Table 6

2 2
R- R- Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficents Relating Students' Perceptions of
Dropout Decisions With Social System Integration by Campus


Dependent Variable: Students' Perceptions of Dropout Decisions


2 2
Campus R full F R increase F partial


Total .022 .835 .001 .192

East .185 1.933 .062 2.569

North .029 .253 .024 .837

West .042 .748 .006 .448


* p<.05




Table 7

2 2
R-2 R- Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students'Actual Dropout
Decisions With Social System Integration by Campus


Dependent Variable: Students' Actual Dropout Decisions


2 2
Campus R full F R increase F partial


Total .055 2.152 .004 .686

East .258 2.962* .058 2.651

North .041 .364 .001 .009

West .124 2.435 .034 2.704


*<-.05












F-statistic of .837. This was also non-significant at the .05

level.

2
The full model for West Campus resulted in an R of .042

with an F-statistic of .748, which was non-significant at the

.05 level. The partial regression coefficient also was

2
non-significant at the .05 level with an R increase of .006 and

an F-statistic of .448.

Table 7 contains the other half of the results to

Hypothesis 1 with students' actual dropout decisions as the

2
dependent variable. The test of the full model yielded an R2 of

.055 with an F-statistic of 2.152, which was not significant at

the .05 level. Without social system in the model, the R2 was
2
.051, which resulted in an R increase of .004. This increase

in variation resulted in a computed F-statistic of .686, which

did not exceed the critical F-statistic at the .05 level.

Therefore the conclusion was fail to reject at the .05 level for

Hypothesis 1.

2
The full model for East Campus had an R of .258 with an

F-statistic of 2.962, which was significant at the .05 level.

The R2 for the partial regression coefficient for East Campus
2
was .200, which resulted in an R increase of .058 and produced

a computed F-statistic of 2.651. This did not exceed the

critical F-statistic at the .05 level and the decision was not

to reject Hypothesis 1. Social system integration did not

improve prediction of dropping out. The full model for North











2
Campus had an R of .041 and an F-statistic of .364. West

Campus had an R2 of .124 and an F-statistic of 2.435. Both were

non-significant at the .05 level. The R2 increase for both North

Campus of .001 and West Campus of .034, with computed

F-statistics of .009 and 2.704 respectively, did not exceed the

critical F-statistic at the .05 level, therefore resulting in a

failure to reject decision for Hypothesis 1.

Hypothesis 1 was tested on four different populations,

total campus, East Campus, North Campus, and West Campus. Two

different dependent variables were used, students' perceptions

of dropout decisions and students' actual dropout rate. Of the

eight separate tests of Hypothesis 1, one was found to

statistically significant at the .05 level.

Hypothesis 2. A significant proportion of the variation

in student dropout rates is not explained by peer-group

interaction after controlling for student background

characteristics, student commitment, the academic system,

and faculty-student interaction.

The test of this hypothesis was a test of the partial

regression coefficient for peer-group interaction given that

background characteristics, commitments, academic system, and

faculty-student interaction were in the model. The results of

the analysis are presented in Table 8 with students' perceptions

of dropout decisions as the dependent variable.

2
The R with all variables in the full model, for total

campus was .035 with an F-statistic of 1.065. Without peer













Table 8

2 2
R-_ R- Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students' Perceptions of
Dropout Decisions With Peer-Group Interaction by Campus


Dependent Variable: Students' Perceptions of Dropout Decisions


2 2
Campus R full F R increase F partial


Total .035 1.065 .009 1.420

East .158 1.181 .016 .623

North .054 .374 .049 1.551

West .050 .715 .015 1.037


*2<.05



Table 9

2 2
R-;R- Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students' Actual Dropout
Decisions With Peer-Group Interaction by Campus


Dependent Variable: Students' Actual Dropout Decisions


2 2
Campus R full F R increase F partial


Total .060 1.875 .009 1.333

East .334 3.315* .112 5.558*

North .242 2.112 .109 4.728*

West .131 2.055 .035 2.773


*p<.05












group interaction in the model, it was .026. The peer-group

interaction variable therefore explained an additional .9

percent of the variation in dropout rate. This increase in

variation resulted in a computed F-statistic of 1.420, which did

not exceed the critical F-statistic at the .05 level. The

conclusion was to fail to reject Hypothesis 2. Peer-group

interaction did not improve prediction of dropping out.

The full models for East, North, and West campuses

resulted in R2's of .158, .054, and .050, with F-statistics of

1.181, .374, and .715. All three were non-significant at the

.05 level. The R2 increase and computed F-statistic for the

partial regression coefficients for East Campus were .016 and

.623, for North Campus .049 and 1.551, and for West Campus .015

and 1.037. In each of the three campuses the computed

F-statistic did not exceed the critical F-statistic at the .05

level. All three campuses resulted in a failure to reject

decision for Hypothesis 2.

With actual drop out as the dependent variable (Table 9),
2
the full model for total campus yielded an R of .060 with a

F-statistic of 1.875. This was not significant at the .05

level. The partial regression coefficient variable for total
2
campus had an R increase of .009. With a computed F-statistic

of 1.333, the decision was to fail to reject Hypothesis 2, since

the critical F-statistic was not exceeded at the .05 level.

East Campus full model was significant at the .05 level with an












R2 of .334 and a F-statistic Of 3.315. The partial regression

coefficient of -.199 resulted in an R2 increase of .112 and a

F-statistic of 5.558. Since this did exceed the critical

F-statistic at the .05 level the decision was to reject

Hypothesis 2. The higher the peer-group interaction score the

more likely a student would drop out.

The full model for North Campus had an R2 of .242 with an

F-statistic of 2.112 and West Campus had an R2 of .131 with an

F-statistic of 2.055. Both were non-significant at the .05

level. The partial regression coefficient of .157 for North

Campus resulted in an R2 increase of .109 and a computed

F-statistic of 4.728, which exceeded the critical F-statistic at

the .05 level. This resulted in the conclusion to reject

Hypothesis 2. The higher the peer-group interaction score the

more likely the student will remain in school. West Campus had

an R2 increase of .035 that resulted in computed F-statistics of

2.773 This did not exceed the critical F-statistic at the .05

level resulting in a fail to reject conclusion for Hypothesis 2.

Hypothesis 2 was tested on four different populations,

total, East, North, and West campuses. Two different dependent

variables were used, students' perceptions of dropout decisions

and students' actual dropout rate. Of the eight separate tests

of Hypothesis 2 only two were found to be statistically

significant. On the East and North campuses, with students'

actual dropout rate as the dependent variable, Hypothesis 2 was

found to be statistically significant.












Hypothesis 3. A significant proportion of the variation

in student dropout rate is not explained by

faculty-student interaction after controlling for student

background characteristics, student commitments, the

academic system, and peer-group interaction.

The test of the hypothesis was a test of the partial

regression coefficient for the faculty-student interaction given

that background characteristics, commitments, academic system,

and peer-group interaction were in the model. The results of

the analysis are presented in Table 10 with students'

perceptions of dropout decisions as the dependent variable.

The test of the full model with all the variables in

yielded an R2 of .035 and an F-statistic of 1.065. This was

found to be non-significant at the .05 level. The partial re-

gression coefficient for the total campus was .034. The faculty

student interaction variable therefore explained an additional

.1 percent of the variation in dropout rate. This increase in

variation resulted in a computed F-statistic of .268, which did

not exceed the critical F-statistic at the .05 level. Therefore

the conclusion was to fail to reject Hypothesis 3. Faculty

student interaction did not improve prediction of perceived

dropouts.

The full models for the East, North, and West campuses re-

sulted in R2's of .152, .054, and .050 with F-statistics of

1.181, .374, and .715. All were non-significant at the .05

level. The R2 increase and computed F-statistic for East Campus













Table 10

2 2
R- R- Increase and Computed F Ratios for the Full Model and
Partial Regrssion Coefficients Relating Students' Perceptions of
Dropout Decisions With Faculty-Student Interaction by Campus
---------------------------------

Dependent Variable: Students' Perceptions of Dropout Decisions


2 2
Campus R full F R increase F partial

Total .035 1.065 .001 .268



East .152 1.181 .025 .978



North .054 .374 .006 .192



West .050 .715 .001 .031


*E<.05



Table 11

2 2
R-, R- Increase and Computed F ratios for the Full Model and
Partial Regresson Coefficients Relating Students' Actual Dropout
Decisions With Faculty-Student Interaction by Campus



Dependent Variable: Students' Actual Dropout Decisions


2 2
Campus R F R increase F partial



Total .063 1.875 .001 .002

East .334 3.305* .086 4.453*



North .242 2.112 .167 7.284*

West .131 2.055 .005 .356


*7<.05




Full Text
43
Background characteristics
The background characteristics' value for each student was
the sum of the Z-scores from family background, individual
attributes, and pre-college schooling divided by 3. These
Z-scores resulted from changing raw scores to standard scores,
adding a constant of 10, and expressing the scores in standard
deviation units. This approach of standardizing the scores was
used by Terenzini, Pascarella, Theophilides, and Lorang (1983)
and was adopted for this study to be consistent for comparison
purposes.
Family background. Parental education was the most
frequently used measurement of family background in the studies
reviewed. Two studies, Pascarella and Terenzini (1983) and
Pascarella, Duby, and Iverson (1983), used, in addition to
parental education, parental income and parental financial
support respectively. Neither of these measuremnets were used in
this study since the average age of PHCC students was 26 years
and they were considered adult learners.
Family background was a single variable, item 7, consisting
of the average of each parents' level of formal education. A
seven point scale was used with a value of 1 being assigned to
"some grammar school" to a value of 7 assigned to "graduate
degree." After dividing the total of both parents' score by 2,
this raw score was converted to a Z score or if only one parent's
education was reported, then the single score was converted to a
Z score, then a constant of 10 was added.


92
critical F-statistic at the .05 level. The partial regression
2
coefficient resulted in an R~ increase of .006, with an
F-statistic of .298 and it was not significant at the .05
level. The decision was fail to reject Hypothesis 4. There was
no interaction effect between peer-group interaction and
faculty-student interaction variables.
Of the 32 tests involving Hypotheses 1-4, only four were
found to be significant. Hypotheses 2 and 3 were found to be
significant only when the dependent variable was students'
actual dropout decisions and only when the student population
came from the East or North campuses.
Test of Hypotheses 5-13
Hypothesis 5. There is no significant difference between
white and non-white student population measurements on
the social system variable.
The results of Hypothesis 5 are rescorded in Table 14.
The total campus mean for white students was 10.074 and 9.750
for non-white students. This resulted in a computed t-statistic
of 1.942, which did not exceed the critical t-statistic at the
.05 level. Since the alpha was set at .05 for all hypotheses,
the conclusion was to fail to reject Hypothesis 5. White
students did not score significantly higher on the social system
variable than non-white students.
White students on East Campus had a mean of 10.409 and
non-white students 9.678. The sample size and within group
variances were both unequal and proportional. Under this


55
Hypothesis 15. There is no correlation between student semester
hours completed and the peer-group interaction variable.
Hypothesis 16. There is no correlation between semester hours
completed and the faculty-student interaction
variable.
Hypothesis 17. There is no correlation between student age and
the social system variable.
Hypothesis 18. There is no correlation between student age and
the peer-group interaction variable.
Hypothesis 19. There is no correlation between student age and
the faculty-student interaction variable.
Multiple linear regression analysis was used to test
hypotheses 1-4. Hypotheses 5-13 were analyzed using a
t-statistic. Hypotheses 14-19 used a Pearson product moment
correlation. An alpha level of .05 was used in each case to
reject the hypothesis.
In all instances where scales operationalizing components of
the model were constructed from variables with different metrics
(e.g. academic and social integration), the same two-step
procedure was employed. First, each individual item or scale was
standardized to provide the same metric (Z score), and second, a
constant of 10 was added to eliminate negative numbers. The
scale was then formed by summing across the standardized items
(Armor, 1973-1974).


6
educational expectations (goal commitments) and commitments the
individual brings into the college environment (institutional
commitments). These goals and institutional commitments serve
both as predictors and reflections of the person's successes and
failures in the collegiate setting.
Tinto's model further suggests that if background
characteristics and commitments are given, then the individual's
integration into the academic and social systems of the college
is the factor that most directly affects the student's
continuance in that college. Tinto (1975) states, "Given prior
levels of goal and institutional commitment, it is the person's
normative and structural integration into the academic and social
systems that lead to new levels of commitment" (p. 96).
According to Tinto's model, other things being equal, the
higher the degree of integration of the individual into the
college system, the greater will be the student's commitment to
the goal of college completion. Through the model Tinto implies
that if preceding variables can be held constant, such as prior
college characteristics and/or experiences and commitment, then
academic and social integration will contribute to the
persistence of a student in college. According to Tinto, if
academic system variables could be controlled for, then social
system variables, specifically peer-group interaction and
faculty-interaction, would contribute to and explain the
persistence of a student in college.




25.
In line 24, "oppressor" most nearly means one who
A. takes away another's rights
B. keeps things hidden
C. wins friends easily
D. fails all the time
26. According to the passage, when open defiance fails, members
of a mistreated culture pretend that they
A. do not know what is happening
B. are better than everyone else
C. need more time to think
D. are very frightened
Hierarchies derive their authority from the asumption that
there is unequal access to information. Those at the top have
access to more information than those at the bottom, and that is
(5) why some are at the top and others are at the bottom. But
today those who are at the bottom of the school hierarchy, the
students, have access to at least as much information about most
subjects as those at the top, teachers and administrators. (10)
At present the only way control can be maintained over the
students is by carefully discriminating against what they know;
that is, by labeling what the students know as unimportant. On
the other hand, if cinematography, mass communication, (15)
popular music, race relations, or urban life were made major
subjects, even an elementary school might then find itself in a
situation where the faculty were at the bottom and its students
at the top. Certainly, it would be hard to know who were the
teachers and who the learners.
27. "Hierarchies" (line 1) most nearly means
A. subjects taught in school
B. relationships between students and teachers
C. organization of people, some having more power
D. theories of education
28. "Discriminating" suggest making a choice of subject matter
that
A. is careful and thoughtful
B. quarantees the teacher an advantage
C. helps students get good grades
D. is important but difficult
GO ON TO THE NEXT PAGE


7
There is adequate research to justify Tinto's inclusion of
social systems into his model of retention. Peer-interaction has
been shown to be an important variable in a student's decision to
stay in college (Denzin, 1966; Pancos & Astin, 1968; Slocum,
1956; Spady, 1970). Spady (1971) used a sample of 683 students
who entered the University of Chicago as freshmen in September
1965 to study interpersonal relations. He concluded that
interpersonal relationships accounted for over 12 percent of the
explained variance in social integration for the men and nearly
20 percent for the women.
The quantity and/or quality of faculty interaction has been
demonstrated as an important variable in the retention of
students in colleges (Centra & Rock, 1971; Cesa, 1980; Noel,
1976; Pascarella & Terenzini, 1976; Spady, 1971). Pascarella and
Terenzini (1977) used a sample of 536 students at Syracuse
University, to test Tinto's theoretical model of attrition.
Under discriminant analysis, Pascarella and Terenzini concluded
that informal student-faculty contact is a significant predictor
of college persistence with significant F-ratios being found on
three of the six faculty interaction catergories.
Other things being equal, the greater the college student's
level of social and academic integration, the greater his or her
subsequent commitment to the institution and commitment to the
goal of college graduation,
respectively. These subsequent


44
Individual attributes. Scholastic Aptitude Test (SAT) scores
were used in the majority of studies for. academic aptitude with
American College Test (ACT) scores being used in one additional
study. Since the majority of PHCC students do not take the SAT or
ACT tests, another standardized instrument was used to measure
academic aptitude. The Comprehensive Guidance Placement test
(English and Reading) is administered to virtually all entering
students at PHCC and was the instrument utilized. The
Comprehensive Guidance Placement test scores (English and
Reading) were furnished by the PHCC registrar. These two scores
were divided by 2 after being converted to Z-scores and adding a
constant of 10, resulting in a single Z score measurement for
individual attributes. Due to the variety of math competencies
of students entering PHCC, three different levels of exams must
be administered. These exams vary to such a degree, that for
standardization purposes the math scores were not used.
A few studies requested information concerning "major area
of study." The wording in these studies was inconsistent, and
these studies were conducted in four-year institutions, rather
than two-year; therefore this item was omitted as one of the
measurements of individual attributes.
Sex, item 3, was coded 0=male and 1-female. Race, item 4,
was coded 0=white and l=non-white. To be consistent with
previous research these items were not included as measurements
of individual attributes. Both items are generally considered as
descriptive variables in reference to dropouts.


APPENDIX C
READING
PLACEMENT TEST


60
resulted in a total of 24 analyses. The total number of tests
for the four separate groups was 92. A significance criterion of
.05 was used to reject each of the 19 hypotheses.
Finally, an ANOVA was used to analyze differences between
individual campuses on variables of interest. Variables that
resulted in a significant F-statistic were analyzed with a
computed Bonferroni-statistic. A .05 level of statistical
significance was used to indicate a difference.
Descriptive Analysis
A subprogram of the Northwest Analytical Statpak computer
program was used to calculate the frequencies and percentages for
the demographic variables. Other subprograms of the NWA were
used to calculate the ANOVA, t-statistic, correlation
coefficients, and multiple linear regression results. A total of
200 questionnaires were distributed with 152 useable surveys
being returned. This resulted in a 76 percent response rate
available for analysis.
Demographic Variables
The data regarding the demographic variables are presented
in Table 1. Inspection of Table 1 revealed the proportion of
usable responses from each of the three campuses was proportional
to the total student population attending those individual
campuses. The total population under investigation was 1146
students, East Campus (23 percent), North Campus (25.7 percent),
and West Campus (51.3 percent). All statistics


41
pre-college initial commitments (goal and institutional);
academic system (academic grade performance and intellectual
development); social system (social peer-group interaction and
faculty-student interaction); and dropout decisions. In
addition, item 8 measures whether an individual has completed a
human relations type course. The specific breakdown by category
and item number follows.
Category Item Number
Social Security Number 1
Age 2
Human Relations Course 8
Background Characteristics
Family Background
parental education 7
Individual Attributes
sex 3
race 4
Pre-college Schooling
high school percentile rank 6
high school grade point average 5
Initial Commitment
Goal Commitment
highest expected degree 9
importance of graduation 11
Institution Commitment
rank of subject institution as choice 10
probability of transfer 13
confidence of choice of subject institution... 12
Integration
Academic System
students' perceived intellectual development.. 15-21
perceived faculty concern 22-26
faculty out-of-class contact (academic) 14(1,2,3)
Social System
student extracurricular activity 40
student-peer interaction 27-33
faculty-student interaction 34-38
faculty out-of-class contact (social) 39(1,2,3)
Dropout Decisions
intent of future educational plans 41


132
faculty-student interaction having a negative influence on
dropout decision. A possible explanation is that the North
Campus has the lowest number of full time faculty of the three
campuses. This results in a large number of students being
taught by part-time instructors. This fact may restrict the
amount of faculty-student interaction that occurs. As a result
students who remain in school may have adequate peer-group
interaction but lack the opportunity for facu1ty-student
interaction.
North Campus results indicated that students who do not
take a human relations type course scored significantly higher
(t=-2.670) than students who do take the course, on the social
system variable scale (Hypothesis 11). These same students
scored significantly higher (t=-2.628) on the measurement of the
peer-group interaction variable (Hypothesis 12). One possible
explanation for this finding may be that human relations type
courses provide some social and/or peer interaction that
traditional community college settings do not provide. Since
North Campus had the highest percent of students over 32 years of
age, 23 percent, these students might not feel as great of a need
to socially interact as the younger students, therefore avoiding
the course. The younger students may seek the course to fulfill
some social interaction needs.
West Campus results indicated that students who do take a
human relations type course scored significantly higher (t2.00)
on the social system variable scale, than students who do not


180
15.
16.
17.
18.
19.
20.
21.
22.
Few of my courses this term have been
intellectually stimulating
I am satisfied with my academic
experience at PHCC
I am more likely to attend a cultural
event (for example a concert,lecture,
or art show) now than I was before
coming to PHCC
I am satisfied with the extent of my
intellectual development since enrol
ling at PHCC
In addition to required assignments,
I typically read many of the recom
mended or suggested books in my course.
My interest in ideas and intellectual
matters has increased since coming to
PHCC
My academic experience at PHCC has
had a positive influence on my intel
lectual growth and interest in ideas...
My non-classroom interactions with PHCC
faculty members have had a positive in
fluence on my intellectual growth and
interest in ideas
S
T
R
0
N
G
S
T
R
0
N
G
L
Y
L
N
D
D
Y
0
I
I
T
S
S
A
A
A
A
G
G
S
G
G
R
R
u
R
R
E
E
R
E
E
E
E
E
E
E
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
A
NS
D
SD
PLEASE CONTINUE TO THE NEXT PAGE


17
Academic system. The combined effects of grade performance
and intellectual development on the student.
Actual dropout. Students who did not return the following
term
Background characteristics. Extraneous variables
characteristic of individual students, i.e., family background,
individual attributes, and pre-college schooling.
Commi tment A degree of obligation to a goal or
institution.
Dropout decision. The perceived intent of individuals'
educational plans or the actual decisions to drop out of an
institution.
Faculty-Student interaction. The degree to which students
evaluate both the quantity and quality of their relationships
with their instructors.
Family background. The highest level of formal education
obtained by a student's parent or parents.
Goal commitment. The degree of commitment to complete a
declared college program.
Grade performance (college). The grade point average (GPA)
of a student's academic performance.
Individual attributes. Academic ability characteristics
possessed by the student prior to entering college.
Institutional commitment. The educational expectations
involving specific institutional components which predispose the
student toward attending one institution rather than another.


113
2 and 3 whereas West Campus did not. In order to determine
which variables differed on the separate campuses an ANOVA was
used. Table 25 presents the results of the ANOVA and Table 26
continued the analysis by presenting the Bonferroni confidence
intervals for all pairwise contrast.
Only one variable differed significantly at the .05 across
campuses. Faculty-student interaction with, means of 10.335 for
East Campus 9.957 for North Campus, and 9.844 for West Campus,
recorded an F-statistic of 5.260. There was a significant
difference between campuses on the faculty-student interaction
variable. Further analysis indicated that the East Campus
students, mean 10.335, scored significantly higher on the
faculty-student interaction variable than West Campus students,
mean 9.844, with Bonferroni limits of (. 14341,.83645) .
Summary of the Chapter
This chapter contains the findings of the study.
Completed and usable responses were received from 152 students
which resulted in a 76 percent response rate. These sample
subjects were found to be very similar to the total population
in reference to demographic variables obtained from the
Registrar.
Ultimately 92 test of hypotheses were analyzed. Each of
the 19 original hypotheses were tested with reference to four
different populations, i.e., total campus, East Campus, North
Campus, and West Campus. Hypotheses 1-4 were tested again using
a different dependent variable.


47
(b) "to discuss intellectual or course-related matters"; (c) to
discuss matters related to my future career", item 14(1,2 & 3).
The factorially derived scales were originally developed by
Pascarella and Terenzini (1980). Initially 55 items were
constructed and subsequently reduced to 34 items. The specific
factorially derived scales used in this study to meausre the
academic system were taken directly from Terenzini, Pascarella,
Theophilides, and Lorang (1983) and Pascarella and Terenzini
(1983). In these two studies an internal consistency (alpha)
reliability of .60 and .64, respectively, were reported for the
academic scale.
The above mentioned four variables were used in virtually
all research investigated. Value placement and/or Z score
conversions were as follows: (1) GPA was converted to a Z-score,
plus ten; (2) a value of 5 was assigned to "SD" through 1 for
"SA" for item 15 and the reverse order being used for 16-21. The
sum of these items was divided by seven and converted to a
Z-score, plus 10; (3) a value of 5 was assigned to "SA" through
1 for "SD" for items 32, 23, and 26 and the reverse values for
items 24 and 25. The sum of these items was divided by 5 and
converted to a Z-score, plus 10; (4) The sum of each of these
items was divided by 3 and the Z-score calculated.
The sum of these four Z scores, calculated from the raw
scores of the academic system variables, was divided by 4. This
quotient represented the academic system measurement.


149
Stern, G.G., Stern, M.I., & Bloom, B.S. (1959). Methods in
personality assessment. Glencoe, Ill.-, The Free Press.
Stevens, P.H. (1956). An investigation of the relationship
between certain aspects of self-concept behavior and
students' academic achievement (Doctoral Dissertation,
Mississippi State University, 1956). Dissertation
Abstracts, 2531. (University Microfilms No. 18, 067 Mic
56-5342).
Summerskill, J. (1962). Dropouts from college. In N. Sanford
(ED), The American college. New York: Wiley, 1962, 627-657.
Taylor, R., & Hanson, G. (1979). Interest and persistence.
Journal of Counseling Psychology, 17, 506-509.
Terrenzini, P., & Pascarella (1978). The relation of students'
precollege characteristics and freshman year experience to
voluntary attrition. Research in Higher Education, 9_,
347-366.
Terenzini, P.T. Pascarella, E.T., Theophi1ides, C., & Lorang,
W.G. (1983, May). A path analytic validation of Tinto's
theory of college student attrition. Paper presented
at the annual conference of the American Educational
Research Association, Montreal.
Tinto, V. (1975). Dropout from higher education: A theoretical
synthesis of recent research. Review of Educational
Research, 45 (1), 89-125.
Tinto, V. (1982). Limits of theory and practice in student
attrition. Journal of Higher Education, 53, 687-700.
Trent, J., & Ruyle, J. (1965). Variations, flow, and patterns of
college attendance. College and University, 41 61-76.
Wall, R. (1979, February). A human relations cource: Does it
make a difference? Paper presented at the Eastern
Educational Research Association Annual Meeting (ERIC
Document Reproduction Service No. ED 173 303).
Wessell, T.R. Jr., Engle, K. & Smidchens, U. (1978). Reducing
attrition on the college campus. NASPA Journal, 16, 26-32.
Wider, J. R. (1981). Attrition in higher education: Its complex
nature. Psychology, 18, 28-37.
Willner, E. (1980). Identifying concerns and potential dropouts
among community college freshman. NASPA Journal, 18, 46-53.


32
Family background. The three most accepted characteristics
of family background were (1) socioeconomic status, (2) parental
education, and (3) quality of relationship.
Research has shown that the socioeconomic status of the
family is inversely related to student dropout rates from college
(Astin, 1964b; Brown, 1980; Pancos & Astin, 1968; Pascarella &
Terenzini, 1983). Even when intelligence was held constant,
children from lower status families exhibited higher rates of
dropout than did children of higher status families (Sewell 6
Shah, 1967).
The educational status of the student's parents is another
variable related to dropout from college. The higher the level
of formal education by the parents the more likely the student
will persist in college (Chase, 1970; Jaffe & Adams, 1970;
Kowalski, 1982; Pascarella & Chapman, 1983; Pascarella, Duby &
Iverson, 1983; Ramist, 1981; Spady, 1971; Terenzini, Pascarella,
Theophilidles, & Lorang, 1983). Bennet and Bean (1983) found this
particularly true for black students.
Additional research has indicated that the quality of
relationships between parents and students is an important factor
related to dropout rates from college. The quality of
relationships not only includes the quality of communication
within the family but the expectations that parents and/or family
members have concerning the student's education (Bean, 1981).
College persisters' home environments tend to be characterized by


124
being related in Tinto's conceptual model and the dropout
decision.
It was apparent that a positive relationship existed
between social system integration and its components, peer-group
interaction and faculty-student interaction. This relationship
was significant at the .05 level for all four student campus
groups. This association was also true for peer-group
interaction and faculty-student interaction. In addition, the
variables of faculty-student interaction and social system
integration were positively related to academic integration in
all groups except on the East Campus. This information was
expected and provided support for the inclusion of peer-group and
faculty-student interaction as components of social system
integration.
When considering actual dropout rates, only two variables
had significant correlations at the .05 level. In reference to
the total campus and West Campus, the higher one's background
characteristics the less likely one was to withdraw. With East
Campus students, the higher the student's academic integration
the more likely the student was to persist. Both of these
variables, student background characteristics and academic
integration, have been sighted as relating directly or indirectly
to persistence and withdrawal.
From the analysis of the correlational data, it would
appear that the conceptual framework model by Tinto does comprise
variables that relate to each other as theorized. These


28
Another possible explanation for this negative influence of
social integration is evidence suggested by Astin (1973) and
Chickering (1974). They reported that commuter college students
are a different population to begin with than residential college
students. These initial differences may be a significant factor
affecting the patterns of variables involved in the retention
process across commuter and residential institutions.
If these explanations are feasible, then what is the
possible flaw in Tinto's model that accounts for this negative
influence. As Pascarella, Duby, and Iverson (1983) suggested,
the flaw may not be in the model, but rather in the population to
which it is applied. When Tinto's model is applied to
residential schools, then Tinto's assumption that the institution
provides ample opportunities for social integration applies. But
when Tinto's model is applied to commuter school samples, the
social integration component of the model may have an influence
quite different from the initially hypothesized model.
Reconceptualization of Tinto's Model
The reported negative influence of social integration on
persistence of college students ( Pascarella, Duby, & Iverson,
1983; Terenzini, Pascarella, Theophilides, & Lorang, 1983) may
have important implications in reference to the association
between person-environment fit and college persistence.
Possibly, this person-environment fit only influences persistence
when institutions provide means for students to achieve social
integration.


23
1968; Wessell, Engle, & Smidchens, 1978); (2) lack institutional
commitment (Gottfredson, 1982; Hackman & Dysinger, 1970); (3)
lack interpersonal orientation and friendship support to some
degree (Astin, 1964a; Fiedler & Vance, 1981; Medsker & Trent,
1968; Spady, 1971; Yourglich, 1966); (4) have less success in
academic areas (Aitken, 1982; Baumgart & Johnstone, 1977; Slocum,
1956); (5) lack either insight and/or capacities for
self-analytic, critical thinking or reject these processes as
important parts of their personality (Daniel, 1963; Faunce,
1966); (6) lack acceptance of themselves to some degree (Lavin,
1965; Stevens, 1956); (7) are less conforming, flexible, or
adaptable (Gurin, Newcomb, & Cope, 1968; Stern, Stern, & Bloom,
1956; Summerskill, 1962); and (8) possess fewer social skills
that provide for positive social integration (Bourn, 1976; Spady,
1971; Tinto, 1975).
Of the many variables associated with attrition, two
particularly stand out: social integration and academic
integration (Spady, 1971; Tinto, 1975; Wider, 1981). The degree
and the direction to which these variables affect college student
retention varies. This variation is partially dependent on the
type of institution under investigation (residential or commuter)
and the uniqueness of the individual study (Pascarella & Chapman,
1983; Pascarella, Duby, & Iverson, 1983; Terenzini, Pascarella,
Theophilides, & Lorang, 1983).


121
North Campus students who had not had a human relations
course scored higher than students who had the course on the
social system variable. West Campus students who had had a human
relations course scored higher than students who did not have the
course.
The following hypothesis was found to be significant at the
.05 level for the North Campus only, resulting in a decision to
reject the hypothesis for this campus.
Hypothesis 12. There is no significant difference between
students who have taken a human relation type course and
students who have not on student measurements of the
peer-group interaction variable.
Students on the North Campus who had not had a human
relations course scored higher than students who had the course
on the peer-group interaction variable.
All other hypotheses not reported here were found to be
non-significant at the .05 level. These results partially
supported the specified model under study.
When considering the results of this study, certain
limitations in regard to their generalizability should be kept in
mind. One limitation was the issue of student volunteers. Even
though 76 percent of the student sample completed the
questionnaire, there is the possibility that these respondents
differed from the non-respondents. This limitation was lessened


Schmit, Dora Mae O'brien, Rindy Penegor, Debbi Amburgey, Juan
Burbano, Bob Judson, Debbie Depoy, Don Lester, Hugh Turner, Dave
Helfirch, and Susan Anderson. In addition much appreciation goes
to the staff, faculty, and administration at Pasco Hernando
Community College for their support of this project.
To my family, Lucile my wife, David my son, and Michele my
daughter, I pledge my deepest love and appreciation. Seven
years ago if I had known what I was going to ask of you, I would
not have. My ignorance of the sacrifices you would have to make
the next seven years allowed me to forge on step by step. I not
only thank you for standing by me when I needed you but I truly
thank you for doing this tremendous task with me. We finally
made it and received our Ph.D.'s. Thank you Drs. Lucile, David
and Michele Rom, Ph.D.'s for all your love and congratulations
for a well deserved honor.


39
Seminar (HPS), which is part of the freshman orientation, has
proven to be a successful retention strategy; (b) the dropout
rate for HPS students was less than for students without HPS; (c)
follow-up studies, approximately one year later, showed the HPS
dropout rate was 15 percent, compared to 29 percent among those
without HPS; (d) on an evaluation questionnaire, 99 percent of
the students responded that the HPS was helpful. This research
supported the concept promoted by Tinto (1975) that peer-group
interaction and to some extent, faculty-student interaction are
important ingredients for social integration, and this
integration is advantageous to a successful retention program.
The important issue is whether the increased retention of
college students in these institutions is due to a cummulative
affect of many variables as Tinto suggested or whether programs
of this type can stand on their own merit as vital retention
programs. In addition, can the same results be expected
regardless of the type of institutional setting in which the
programs are being conducted, either residential or commuter.


168
leadership, on the other hand, rests on the frailest of rank, and
file participation. A drive for civil rights that involves all
Mexican Americans may yet develop, but even the most (10)
optomistic of the leaders of the group believe it to be far in
the future.
Unfortunately, sympathy for minorities in the U.S. seems to
flourish only when their persecution is well publicized. At
present, oppression (15) of the Mexican-American minority is
little known to the general public. No doubt, then it is true
that the plight of the Mexican-American citizen will not become a
burden on the conscience of America unless a large, well
organized protest (20) movement develops among these oppressed
citizens and brings a touch of drama to their struggle.
13. Which statement best summarizes the passage?
A. Mexican Americans leaders have hopes for the future
B. Mexican Americans problems have become more serious
C. Many Americans understand the Mexican Americans' effort
D. The Mexican Americans' struggle for civil rights is not
effective but may become so.
14. The word "flourish" in line 13 most nearly means
A. be amazed
B. show gratitude
C. struggle
D. blossom
15.Which of the following does the author suggest do a great
deal to help the Mexican Americans gain their civil rights?
A. More optimistic leaders
B. More news stories about their problems
C. Joining the Blacks' civil rights drive
D. An organization with a loose structure
16.
In line 14, "persecution" most nearly means
A. dramatic action
B. unjust treatment
C. desire for equality
D. attempt to organize
17. The
A.
B.
C.
D.
"plight" is the result of which of the following
Failure to give Mexican Americans their rights
Guilty conscience of the American people
The success of a drive for civil rights
Plans of those who lead the Mexican Americans
GO ON TO THE NEXT PAGE


10
Hypothesis 3. A significant proportion of the variation in
student dropout rates is not explained by faculty-student
interaction after controlling for student background
characteristics, student commitments, the academic system,
and peer-group interaction.
Hypothesis 4. There is no interaction effect between peer-group
interaction and faculty-student interaction.
Hypothesis 5. There is no significant difference between white
and non-white student population measurements on the social
system variable.
Hypothesis 6. There is no significant difference between white
and non-white student population measurements on the
peer-group interaction variable.
Hypothesis 7. There is no significant difference between white
and non-white student population measurements on the
faculty-student interaction variable.
Hypothesis 8. There is no significant difference between male
and female student measurements on the social system
variable.
Hypothesis 9. There is no significant difference between male
and female student measurements on the peer-group
interaction variable.
Hypothesis 10. There is no significant difference between male
and female student measurements on the faculty-student
interaction variable.


16
by Wall (1979). Recent evidence of programs designed to improve
retention through improving the degree of social integration has
been cited by Beck (1980).
In light of the expressed need to retain students, and
considering the importance of student retention to the sustenance
of institutional vitality, the investigation of Tinto's
theoretical model of retention, specifically, social system
integration (peer-group and faculty-student interaction) and how
it related to dropout decisions in a two-year commuter
institution seemed appropriate. This study contains a description
of the contributions made by peer-group interaction and/or
faculty-student interaction variables toward the process of
dropout decisions described by Tinto (1975). Information provided
by this research should encourage educational institutions to
investigate whether single retention models are applicable to any
one institutional type or if a combination of theoretical models
might be more advantageous.
Definition of Terms
The following definitions were cited from Tinto (1975). A
complete operational definition of each term is provided in
Chapter 3.
Academic integration. Meeting certain explicit standards of
the academic system (grade performance) and identification with
the norms of the academic system (intellectual development).


CHAPTER THREE
METHODOLOGY
Using Tinto's (1975) conceptual framework, the purpose of
this study was to determine what relationships exist between
social system integration variables (peer-group interaction and
faculty-student interaction) and student dropout decisions in a
two-year community college.
Instrumentation
The survey questionnaire developed for this research
investigation was formulated by this researcher using the most
recent and popular measurements of the variables under
consideration. The questionnaire provided measures of each of the
concepts in Tinto's (1975) theoretical model under investigation,
except for those provided by the institution: the students' grade
point average, number of college semester hours completed, the
actual dropout rate and the Guidance Placement Test scores
(Appendix B and C). In addition, the instrument obtained
information regarding demographic characteristics, i.e. social
security number, age, sex, and race. The instrument contains
forty-one items and appears in Appendix D.
Description of Student Survey
The Student Survey Questionnaire (Appendix D) provides
measures of five main areas under consideration: background
characteristics (family background; individual attributes;
40


TABLES-continued
TABLES PAGE
2 2
11 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Faculty-Student Interaction by Campus 87
2 2
12 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With the Interaction Effect of Peer-Group and
Faculty-Student Interaction by Campus 90
2 2
13 R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With the Interaction Effect of Peer-Group and
Faculty-Student Interaction by Campus 90
14 Means, S.D., and Computed t-Statistic
Comparing White and Non-White Students
on the Social System Variable 93
15 Means, S.D., and Computed t-Statistic
Comparing White and Non-White Students
on the Peer-Group Interaction Variable 95
16 Means, S. D., and Computed t-Statistic
Comparing White and Non-White Students
on the Faculty-Student Interaction Variable 97
17 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Social System Variable 99
18 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Peer-Group Interaction Variable 100
19 Means, S.D., and Computed t-Statistic
Comparing Male and Female Students
on the Faculty-Student Interaction Variable 102
20 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who
Have Not on the Social System Variable 104
viii


83
Table 8
2 2
R, R Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students' Perceptions of
Dropout Decisions With Peer-Group Interaction by Campus
Dependent
Variable:
Students 1
Perceptions
of Dropout Dec
Campus
R2 full
F R2
increase
F partial
Total
.035
1.065
.009
1.420
East
.158
1.181
.016
.623
North
.054
.374
.049
1.551
West
.050
.715
.015
1.037
*£<05
Table 9
2 2
R, R Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students' Actual Dropout
Decisions With Peer-Group Interaction bv Campus
Dependent Variable: Students' Actual Dropout Decisions
Campus
R2 full F
_ 2 .
R increase
F partial
Total
.060 1.875
.009
1.333
East
.334 3.315*
.112
5.558*
North
.242 2.112
. 109
4.728*
West
.131 2.055
.035
2.773
*£<.05


176
STUDENT SURVEY


159
WRITTEN ENGLISH EXPRESSION
Part 2
Time-15 minutes
20 Questions
21. Maria especially disliked winters in New York and her
tenement apartment had little heat.
A. York and
B. York because
C. York, while
D. York, insofar as
22. Senator Brooks became ill just before the lecture, he had to
cancel it.
A. lecture, he had to cancel
B. lecture, so canceling
C. lecture, and he had to cancel
D. lecture and having to cancel
23. Mary Well's version of "My Guy" is my most favorite one that
I like best.
A. my most favorite one that I like best
B. my favorite one that I like best
C. my most favorite
D. my favorite
24. Howard seemed wiser than his brother's plan, which was very
foolish.
A. than his brother's plan, which was very foolish
B. than the very foolish plan of his brother
C. than his brother, whose plan was very foolish
D. than his brother and his very foolish plan
25. Because the girls admire James Taylor, they had almost
listened to every one of his recordings.
A. had almost listened to
B. had listened to almost
C. have almost listened to
D. have listened to almost
GO ON TO THE NEXT PAGE


122
because of the similarities found, in regard to demographic
variables, between the student sample and the total college
student population.
Another limitation was that the sample was drawn from one
multi-campus community college. Since the research involved just
one particular community college, generalizations to other
institutions would be restricted. In addition the small sample
size on each campus may limit the validity of some of the
statistical analysis.
Conclusion
The first conclusion drawn from this study was the need for
a second dependent variable. Even though perception of a
student's decision to drop out may be a good indicator of real
performance in some situations, this study did not confirm this
fact. With 53.4 percent of the sample changing their decisions
from what they perceived to what actually was done, it was
apparent that actual dropout decision was the more accurate
measure of the dropout decisions.
The correlational data (Tables 2,3,4, and 5) indicated
relationships that occurred within the total campus, the East
Campus, the North Campus, and the West Campus students. In
synthesizing the data, relationships were found that were common
to all groups, some common to three groups, a few common to just
two groups, and several that were unique to individual campuses.
Some general conclusions and trends are reported here concerning
variables of major interest.


178
8. Have you taken and completed a human relations type course
(Human Development, Individual Discovery, etc.) at the
college level?
yes or no
SECTION TWO: Commitment
This information concerns to what degree an
individual may be committed to a certain goal
and/or a particular educational institution.
Directions: Please continue to check JUST one of the options that
MOST CLOSELY FITS your situation
9. What is the highest academic degree you expect to obtain
anywhere?
_Associate of Arts/Science (A.A. or A.S.)
Bachelor's Degree (B.A. or B.S.)
Masters Degree (M.A..M.S., etc.)
Doctorate Degree (Ph.D. or Ed. D.)
Medical doctorate (M.D.,D.D.S.,D.V.M., etc.)
Bachelor's or doctorate in Law (LL.B. or J.D.)
10. In applying to college, was Pasco Hernando Community College
(PHCC) your:
_lst choice 2nd choice 3rd choice 4th choice
11. How important is it to you to graduate from college?
_extremely
very important
somewhat important
not at all important
12. How confident are you that you made the right decision in
choosing to attend PHCC?
_extremely confident
very confident
_somewhat confident
not at all confident
PLEASE CONTINUE TO THE NEXT PAGE


Table 21
Means,
S D. and
Computed
t-Statistic Comparing.
Students
Who Have Had
a Human
Relations
Type Course With
Students
Who Have
Not on the Peer-Group
Interaction
Variable
HUMAN RELATIONS
COURSE
NO HUMAN
RELATIONS COURSE
CAMPUS
HYP.
NO.
MEAN
S.D.
NO.
MEAN
S.D.
df t
Total
12
59
10.051
. 842
93
9.976
.696
150 .419
East
12
15
10.067
.920
24
9.771
.599
37 1.108
North
12
17
9.792
.548
22
10.337
.746
37 -2.628*
West
12
27
10.162
.940
47
9.912
.668
72 1.215
*£<05
106


APPENDIX A
PROGRAM DECLARATION


179
13. To what degtee do you agree with this statement. "I will
probably transfer from PHCC before graduation."
_strongly agree
agree
not sure
disagree
strongly disagree
SECTION THREE: Academic Integration
This information concerns whether individuals
meet certain explicit standards of the academic
system (grade performance) and identify with the
norms of the academic system.
Directions: Please record the accurate number in the space
provided.
14. Students have a variety of contact with faculty members. In
the blank to the right, please estimate the number of times
this semester you have met with a faculty member outside the
classroom for each of the following reasons. Record only
the number of those conversations that lasted 10 minutes or
more.
1. To get basic information and advice about my academic
program _
2. To discuss matters related to my future career _
3. To discuss intellectual or course related matters..
Directions: Following is a list of statements characterizing
various aspects of academic and social life at
Pasco Hernando Community College (PHCC) and with
which you may or may not agree. Using the scale
to the right of each statement, please indicate,
the extent of your agreement or disagreement with
each statement, as it applies to your PHCC
experience, by circling the appropriate
abbreviation. PLEASE circle ONLY ONE
abbreviation for each statement.
PLEASE CONTINUE TO THE NEXT PAGE


Table 3
Pearson Product Moment Correlation for Endogenous and Exogenous VariablesEast Campus
VARIABLES
1
2
3
4
5
6
7
1.
Age
.201
-.008
-.109
.024
-.273
.057
2.
Sex
-.101
-.189
.144
.157
-.142
3.
Race
-.017
.012
-.137
-.045
4.
Accumulated Hours
.476*
.263
.269
5.
Human Relations Course
.291
-.016
6.
Background Characteristics
.125
7.
Commitment
8.
Academic Integration
9.
Peer-group Interaction
10.
Faculty-student Interaction
11 .
Social Interaction
12.
Dropout Perception
13.
Dropout Actual
(continued)
*£<.05
o


107
variable. The North Campus had a computed t-statistic of
-2.628, with means of 9.792 for students with the course and
10.337 for
students
without
the
course
This
exceeded the
critical t-
statistic
at the
.05
level in
f avor
of no human
relations course and the decision was to reject Hypothesis 12.
Students on the North Campus who had not had a human relations
course scored higher than students who had the course on the
peer-group interacton variable.
Hypothesis 13. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
faculty-student interaction variable.
The results of Hypothesis 13 are found in Table 22. The
computed t-statistics for total campus equalled 1.07, East
Campus equalled .917, North Campus equalled -1.624, and West
Campus equalled 1.781. All four failed to exceed the critical
t-statistic at the .05 level of significance. The decision for
all four groups was fail to reject Hypothesis 13. There is no
difference between students who had a human relations course and
students who had not on the facu1ty-student interaction
variable.
Test of Hypotheses 14-19.
All data concerning hypotheses 14-16 are presented in
Table 23.
Hypothesis 14. There is no correlation between student
semester hours completed and the social system variable.


65
The mean for accumulated semester credit hours for the
sample was 19.0 which approximated the total population mean of
20.2. This slight difference may have been attributed to the
fact the sample had a limit on the maximum number of accumulated
hours a student could have in order to be eligible for the
study.
The last variable listed was dropout decision, both the
students' perceptions and actual dropout decision. The number of
individuals who perceived themselves as not returning was 21.
This was very close to the actual dropout rate of 22. The range
between campuses was 3.2 percent for the perceived decision and
5.9 percent for the actual decision. East Campus was very
consistent with 15.4 percent recorded for both perceived decision
to drop out and actual dropout decision. North Campus lost two
fewer students than perceived which decreased their perceived
percentage from 15.4 percent to a 10.3 actual dropout
percentage. West Campus lost three more students than
anticipated which increased their percentages of dropouts from a
perceived dropout rate of 12.2 percent to an actual dropout rate
of 16.2 percent.
Additional statistics of comparative value, which are not
recorded in Table 1, were the English and reading scores from the
Guidance Placement Test (Appendices B and C). These entrance
tests reflected students' ability in reading comprehension and
English usage. The total college population mean for reading was
24.7 and 25.1 for the sample under consideration. The


15
More could be done in two-year colleges toward both
redirecting non-persisters and increasing important recruitment
markets for student enrollment. There exists a great need in
community colleges to service all students who enter. Student
retention should not be promoted to the extent that students see
leaving community college as a failure. Students should feel
comfortable to come and go as they please (Hahn, 1974). There is
a need, however, to provide structured programs to assure that
potentials are realized by both students and the institution.
Students should be given every opportunity to become socially and
academically integrated into an existing college environment.
Programs presently exist that attempt to improve on those
personal and social 'qualities that are advantageous for social
integration into the college environment. Meyer (1975) concluded
the following concerning the impact of a human development course
on community college students: (a) a human development course can
have a significantly positive impact on college students'
self-esteem, definiteness about self, and sense of purpose and
meaning in life; (b) participation in a human development course
can significantly strengthen students' interpersonal feelings,
parti cu1ari 1y feelings toward others; and (c) the human
development course is strongly endorsed by participants as being
personally relevant and meaningful. Similar findings supporting a
human relations-type course by actual participants were reported


138
Campus. Even when applying Tinto's model or the reconceptualized
model to the appropriate campuses, the general process seems to
fit but not all of the relative variables act as theorized. The
strongest implication of this study is that there may not be any
serious flaws in either model, but rather in the inclusive manner
in which the models are applied. Both models may be very useful
in explaining the dropout process in educational institutions.
The flaw suggested by research was that Tinto's model was applied
to all institutional settings, therefore the need for a
reconceptualized model. Pascarella, Duby, and Iverson (1983) and
Terenzini, Pascarella, Theophi1ides, and Lorang (1983) may have
promoted the same error in suggesting that the reconceptualized
model would apply to all commuter schools. This research implies
that the model, its process and variable relations, cannot be
applied across any one type of institutional setting without
careful consideration of the institution and its student
population characteristics. Within certain residential schools
there may exist retention variable relationship more
characteristic of typical commuter school and as shown in this
study, within a particular commuter school there may be
individual campuses that are more similar to residential colleges
in their retention variable relationships.
Possibly the most important implication of this study is
the philosophy of the purpose for the development of such
retention models. Retention models designed to assist
institutions to better understand variables relative to the


82
2
Campus had an R of .041 and an F-statistic of .364. West
2
Campus had an R of .124 and an F-statistic of 2.435. Both were
2
non-significant at the .05 level. The R increase for both North
Campus of .001 and West Campus of .034, with computed
F-statistics of .009 and 2.704 respectively, did not exceed the
critical F-statistic at the .05 level, therefore resulting in a
failure to reject decision for Hypothesis 1.
Hypothesis 1 was tested on four different populations,
total campus, East Campus, North Campus, and West Campus. Two
different dependent variables were used, students' perceptions
of dropout decisions and students' actual dropout rate. Of the
eight separate tests of Hypothesis 1, one was found to
statistically significant at the .05 level.
Hypothesis 2. A significant proportion of the variation
in student dropout rates is not explained by peer-group
interaction after controlling for student background
characteristics, student commitment, the academic system,
and faculty-student interaction.
The test of this hypothesis was a test of the partial
regression coefficient for peer-group interaction given that
background characteristics, commitments, academic system, and
faculty-student interaction were in the model. The results of
the analysis are presented in Table 8 with students' perceptions
of dropout decisions as the dependent variable.
2
The R with all variables in the full model, for total
campus was .035 with an F-statistic of 1.065. Without peer


STUDENT SURVEY
Directions: Please read all directions and questions completely
before giving your honest answer. All questions
MUST be answered completely in order for this
questionnaire to be valid.
SECTION ONE: Background Information
This information concerns characteristics and/or
behaviors that might be unique to you prior to
attending PHCC.
Directions: Please fill in the blanks or check JUST one of the
options that MOST CLOSELY FITS your situation.
1. Social Security Number:
2. Age: years
3. Sex: male or female
4. Racial/Ethnic Identification: white or non-white
5. What was your grade point average in high school?
A/A+ A- B+ B- C+ C- D or below
6. What was your class percentile rank in high school? (please
check the closest to yours)
Top 10% 20% 30% 40% 50% 60% 70% or below
7. What is the highest level of formal education obtained by
your parents?
Father Mother
Grammar school or less (1-8 years)
Some high school (9-11 years)
High school graduate (12 years)
Some college
College graduate (Bachelor's Degree)
Some graduate study
Received graduate degree(Masters or Doctorate)
PLEASE CONTINUE TO THE NEXT PAGE


48
Social system
Social system integration was operationally defined as the
sum of the Z-scores of peer-group interaction and faculty-student
interaction variables divided by 2. The factorially derived
scales used to measure peer-group interaction and faculty-student
interaction were originally developed by Pascarella and Terenzini
(1980). Terenzini, Pascarella, Theophilides, and Lorang (1983)
reported an internal consistency (alpha) reliability of .47 for
these items and Terenzini and Pascarella (1983) reported .46.
Peer-Group interaction. The vast majority of research
studies operationalized peer-group interaction as the sum of the
scores for (1) the number of hours spent per week in
extracurricular activities, item 40; and (2) a seven-item
factorially derived scale measuring the extent and quality of a
student's interaction with peers, items 27-33. Items 27-30 of
the peer-interaction question were assigned a value of 1 for "SD"
through 5 for "SA" and the values were reversed for items 31-33.
The total score was divided by 5 and converted into a Z-score,
adding a constant of 10. This Z-score was summed with the
Z-score conversion of the raw score for extracurricular
activities, then divided by 2.
Faculty-Student interaction. The majority of the research
studies operationalized faculty-student interaction as the sum of
the scores for (1) a five-item factorially derived scale
measuring the quality and impact of a student's out-of-class
contact with faculty, items 34-38, and (2) the frequency of


Ill
Table 24
Interaction, and
Facultv-Student
Interaction
Variables
by Campus
TOTAL
EAST
NORTH
WEST
HYPOTHESIS 17
age and social
system
-.048
-.058
O'
t
o

1
.014
HYPOTHESIS 18
age -and
peer-group
interaction
.008
-.149
1

o

.034
HYPOTHESIS 19
age and
faculty-student
interaction
-.047
.079
-.034
-.022
'£<.05


162
36. The girl standing next to the potted palm In the yellow
dress is Luellen Hayes.
A. The girl standing next to the potted palm in the yellow
dress is huellen Hayes.
B. In the yellow dress standing next to the potted palm is
the girl. Luellen Hayes.
C. Luellen Hayes is the girl standing next to the potted
palm in the yellow dress.
D. Standing next to the potted palm is Luellen Hayes, the
girl in the yellow dress.
37. Some automobiles now use natural gas instead of gasoline for
fuel, this change reduces the pollutants in their exhaust by
ninety percent.
A. fuel, this change reduces
B. fuel, and it reduced
C. fuel, reducing
D. fuel, by which it reduces
38. Despite official efforts to stop the heroin trade, great
quantities of the drug still enter the U.S. each year.
A. still enter
B. would still enter
C. has still entered
D. is still entering
39. Ted Martinez was struck by a pitched ball, fortunately, not
seriously injured.
A. ball, fortunately, not seriously injured
B. ball, fortunately, not with serious injury
C. ball, but, fortunately, there was not serious injury
D. ball, but, fortunately, he was not seriously injured
o
40. Sometimes you can be in 60~temperature in San Francisco and,
just a few miles away, they have 95~.
A. you can be in 60 temperature in San Francisco and, just
a few miles away, they have 95 .
B. when you have 60 intemperature in San Francisco, it is
95 just a few miles away
o
C. San Francisco can have 60 and, just a few miles away,
you have 95
D. the temperature in San Francisco is 60 and a few miles
_ o
away it is 95
STOP
IF YOU FINISH BEFORE TIME IS IS UP, CHECK YOUR WORK ON THIS PART
ONLY. DO NOT GO BACK TO THE FIRST PART.


114
Table 25
ANOVA Between East, North, and West Campuses on Variables of
. r. t ; r i,"r . r: r
Interest
Variables
df
F
Age
2/149
2.639
Sex
2/149
.283
Race
2/149
2.200
Hours enrolled
2/149
2.415
Accumulated hours
2/149
2.496
Background Characteristics
2/149
2.806
family background
2/149
.674
English/reading
2/149
3.817
Commitment
2/149
1.009
goal
2/149
.725
institution
2/149
.234
Academic System
2/149
.745
Social System
2/149
2.260
peer-group interaction
2/149
.793
qualitative (survey items 27-33)
2/.149
1.003
quantitative (survey item 40)
2/149
.076
faculty-student interaction
2/149
5.260*
qualitative (survey items 34-38)
2/149
3.884
quantitative (survey item 39)
2/149
2.347
Perception of Dropout Decision
2/149
.208
Actual Dropout Decision
2/149
.378
Completion of Human Relations Course
2/149
.268
*£<.05


4
Tinto states that social integration occurs primarily
through informal peer-group associations, semi-formal
extra-curricular activities, and interaction with faculty and
administration within the college. Tinto's theoretical model
implies that successful social integration, via the above means,
results in increased retention of students in an educational
institution. Tinto stated:
Successful encounters in these areas result in varying
degrees of social communication, friendship support,
faculty support, and collection affiliation, each of
which can be viewed as important social rewards that
become part of the person's generalized evaluation of
the cost and benefits of the college attendance and
that modify his educational and institutional
commitments. Other things being equal, social
intergation should increase the likelihood that the
person will remain in college, (p. 107)
Pascarella and Chapman (1983), using 2,326 freshmen from 11
postsecondary institutions, and Pascarella and Terenzini (1983),
using a longitudinal study with three data collections and a
sample of 763 freshmen, verified the direct influence of social
integration on college dropouts as theorized by Tinto. These
studies were conducted in four-year residential schools. However
when Tinto's model was applied to both four and two-year commuter
schools, the results were non-supportive (Pascarella & Chapman,
1983; Pascarella, Duby, & Iverson, 1983). Pascarella and Chapman
(1983) found no direct nor indirect effects of social integration
on persistence in four or two-year commuter institutions. In
addition, Pascarella, Duby, and Iverson (1983), using 269 in
coming freshmen, reported a negative direct effect of social


38
model, the influences of these variables are dependent on
preceding and related variables, background characteristic,
commitments, and academic integration. The strength of the
research concerning social integration may lie in variables not
adequately under the researchers control such as type of
institutional setting. Additional variables not under the
researchers control are family background, individual attributes,
pre-college schooling, commitments, and academic system.
If the research on social integration is to be valid and
useful in the educational system, investigators must control
adequately for extraneous variables. Programs developed to
enhance the educational climate of students should be based on
the best available data on college student persistence.
Retention programs emphasizing human relations type courses
have been promoted in educational settings to improve individual
interpersonal skills and a sense of purpose in life (Meyer,
1975). Little (1971) and Wall (1979) found that a human
relations course significantly strengthened students'
interpersonal feelings, particularly feelings towards others. If
these courses and programs are successful, then according to the
research improved retention should be a by-product.
Recent evidence of programs designed to improve
interpersonal skills and therefore improve retention have been
cited by Beck (1980). He reported the following findings from
Lurleen B. Wallace Junior College: (a) the Human Potential


= ACADEMIC
>= INTEGRATION =
BACKGROUND
CHARACTERISTICS
COMMITMENTS
COMMITMENTS
E.G.*
*
*
*
*
sex =
race =
academic =
aptitude =
affiliation =
needs =
secondary =
school =
grades =
GOAL
COMMITMENT
INSTITUTIONAL
COMMITMENT
a
a
# =
GOAL
S
. =
. COMMITMENT .
=
->=
=
.=
INSTITUTIONAL.
=_a_>=
. =
. COMMITMENT .
=
>= PERSISTANCE =
a/
INTENTION = -
>= SOCIAL = -
= INTEGRATION =
a
a .
new or revised
effects based on
the present study
u>
o
Figure 2. Suggested Reconceptualization of Tinto's Model
(printed with permission Pascarella, Duby, and Iverson, 1983)


118
characteristics (family background, individual attributes, and
pre-college schooling), commitments (goal and institutional),
academic system integration, social system integration
(peer-group interaction and faculty-student interaction), and
students' perceived dropout decisions. In addition, the
questionnaire requested the respondent to identify his/her sex,
age, race, and whether or not he/she had taken a human relations
type course.
A pilot study of 40 students was conducted to assess the
feasibility of the instrument. Thirty-eight of the 40 subjects
responded and the usability of the instrument was varified. The
final survey was distributed to 200 students on three different
campuses of Pasco Hernando Community College. The response rate
was 76 percent with 152 subjects being used for the final
analysis.
Multiple linear regression was used to test the first four
of the 19 hypotheses. Four separate analyses were performed on
each of the four separate groups, i.e., total campus, East
Campus, North Campus, and West Campus using two different
dependent variables. This resulted in 32 analyses tests
involving the first four hypotheses. East Campus and North
Campus were the only groups to reach significance at the .05
level for both Hypotheses 2 and 3. In all four situations the
dependent variable was actual dropout decision. The following


CHAPTER FIVE
SUMMARY, CONCLUSION, IMPLICATIONS, AND RECOMMENDATIONS
This chapter presents a summary of the study, conclusions,
implications, and recommendations related to the findings.
Summary
The purpose of this study was to determine whether
relationships existed between social system integration variables
(peer-group interaction and faculty-student interaction) and
student dropout decisions in a two-year community college. The
investigation was guided by the theory of dropout decisions being
a longitudinal process of interactions between the individual
student and the academic and social systems of the college, as
formulated by Vincent Tinto (1975). Tinto believed that students
enter college with certain background characteristics which
influence the development of goal and institutional commitments.
He believed that these commitments in turn have influence on the
academic and social integration of the student into their college
environment. Tinto hypothesized that the degree to which students
are integrated into a college will have a direct affect on the
students' decisons to either drop out or remain in school (Figure
1, P.3).
A Student Survey (Appendix D) was developed for this
research. The Student Survey was designed to measure background
117


123
Background characteristics had a positive correlation with
accumulated hours in the total campus and West Campus groups.
Also the higher the background characteristics in these two
groups the less likely the students were to actually drop out.
The higher the background characteristics for West Campus
students the higher the academic integration. These data gave
some support for the notion that background characteristics play
a role in the student's dropout decision process.
There was a positive correlation between commitments and
academic integration in all groups except on the North Campus.
In addition, females appeared more committed to college
completion on the total and West campuses. West Campus students'
responses showed a positive relationship between their commitment
and their peer-group interaction and social system integration.
There was the same indication that commitment was related to
academic integration, accumulated credit hours, and possibly
peer-group and faculty-student interaction.
Academic integration was positively correlated with both
social system integration and faculty-student interaction for all
student groups except on the East Campus. For two groups, total
and West, the older student was more academically integrated.
Even though the East Campus was not included, academic
integration on East Campus indicated that the student would be
less likely to withdraw from school. These trends lend support
to social system integration and academic system integration


54
Hypothesis 7. There is no significant difference between white
and non-white student population measurements on the
faculty-student interaction variable.
Hypothesis 8. There is no significant difference between male and
female student measurements on the social system variable.
Hypothesis 9. There is no significant difference between male and
female student measurements on the peer-group interaction
variable.
Hypothesis 10. There is no significant difference between male
and female student measurements on the faculty-student
interaction variable.
Hypothesis 11. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the social
system variable.
Hypothesis 12. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
peer-group interaction variable.
Hypothesis 13. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
faculty-student interaction variable.
Hypothesis 14. There is no correlation between student semester
hours completed and the social system variable.


interaction), and perceived dropout decision. In addition, other
demographic variables were requested via this questionnaire.
Four different population groups were considered; the total
student population, students attending the East, the North, and
the West campuses. Each of the 19 hypotheses was tested using
the four different population groups. Hypotheses 2 and 3, which
related peer-group and faculty-student interaction to the actual
dropout decision, showed significance at the .05 level for the
East and North campuses.
For East Campus students a significant proportion of the
variation in dropout decisions (11.2%) was explained by the
peer-group interaction variable (negative influence) and the
faculty-student interaction variable (8.6%), which was a positive
influence. For North Campus students a significant proportion of
the variation in dropout decisions (10.9%) was explained by the
peer-group interaction variable (positive influence) and the
faculty-student interaction variable (16.7%), which was a
negative influence.
Of the remaining 15 hypotheses relating age, sex, race,
accumulated semester hours, and a human relations type course
with the social integration, peer-group interaction, and
faculty-student interaction variables, six were found to have
statistically significant relationships at the .05 level.
The study showed that similarities between campus
populations were greater than the differences. The two main
xii


34
( 1968) confirmed that GPA in high school is one of the best
predictors of college persistence. Tinto (1975) also supported
Astin's (1973) conclusion that measures of ability, as obtained
on a standardized test, are a significant predictor of college
persistence.
Pre-ColleRe schooling. Nelson (1972) suggested that the
characteristics of the high school attended by students were
important variables in determining the probability of a student
either persisting in college or dropping out. Two variables
confirmed as predictors of college persistence by Davis (1966),
Nelson (1972), and St. John (1971) were the students' ability
level and their social status composition in the school. These
two variables not only appear to affect the individuals'
perception of their own ability but also their expectations for
future college education. Additional research by Pascarella and
Chapman (1983) found students' percentile rank in high school and
high school GPA to be consistent predictors of college
persistence.
Institutional commitment. In researching the variables that
may influence an individual's decision to remain in school or
dropout, one would have to investigate to what extent an
individual was committed to a particular institution (Pascarella
& Chapman, 1983). A valid procedure would be to determine
whether specific institutional components exist that would
predispose a student toward attending one institution rather than
another (Pascarella & Chapman; Spady, 1970; Tinto, 1975).


101
mean for males of 10.001 and females 9.996, which did not exceed
the critical t-statistic at the .05 level. The conclusion was
to fail to reject Hypothesis 9. There is no difference between
male and female students' scores on the peer-group interaction
variable. With means for males of 9.468 and females 10.049,
East Campus resulted in a -2.437 computed t-statistic, which was
significant at the .05 level in favor of female students.
Because the within group variances were approximately equal it
was not necessary to consider the difference in sample size.
Therefore the null hypothesis was rejected for Hypothesis 9.
East Campus female students scored higher than male students on
the peer-group interaction variable. North Campus means for
males was 10.057 and females 10.123 and West Campus means for
males was 10.204 and females 9.900. Both resulted in
non-significant results with t-statistics of -.280 and 1.312
respectively. This resulted in a failure to reject decision on
these campuses in relationship to Hypothesis 9. There is no
difference between male and female students' score on the
peer-group interaction variable on the North and West campuses.
Hypothesis 10. There is no significant difference between
male and female student measurements on the
faculty-student interaction variable.
Table 19 contains the data of Hypothesis 10. The computed
t-statistic for the total campus was -1.372 with means for males
9.883 and females 10.056. This did not exceed the critical
t-statistic at the .05 level; therefore the decision was fail to


Table 5-continued
VARIABLES
8
9
10
11
12
13
1.
Age
.339*
.034
-.022
.014
.090
.009
2.
Sex
.117
-.182
-.017
-.140
-.052
-.082
3.
Race
-.064
-.050
-.050
-.021
.039
.073
4.
Accumulated Hours
.049
.012
.062
.030
-.075
.186
5.
Human Relations Course
. 170
.163
.218
.227
-.111
. 105
6.
Background Characteristics
.233*
.023
.090
.077
-.035
.288*
7.
Commitment
.285*
.237*
.207
.287*
.160
.103
8.
Academic Integration
.325*
.549*
.545*
. 105
.132
9.
Peer-group Interaction
.254*
.809*
.171
.217
10.
Faculty-student Interaction
.772*
.059
.136
11.
Social Integration
.146
.217
12.
Dropout Perception
. 121
13.
Dropout Actual
*£<.05


53
Data Analysis
The following null hypotheses were investigated:
Hypothesis 1. A significant proportion of the variation in
student dropout rates is not explained by selected social
system variables after controlling for student background
characteristics, student commitments, and the student
academic system (student grade performance and student
intellectual development).
Hypothesis 2. A significant proportion of the variation in
student dropout rates is not explained by peer-group
interaction after controlling for student background
characteristics, student commitments, the academic system,
and faculty-student interaction.
Hypothesis 3. A significant proportion of the variation in
student dropout rates is not explained by faculty-student
interaction after controlling for student background
characteristics, student commitments, the academic system,
and peer-group interaction.
Hypothesis 4. There is no interaction effect between peer-group
interaction and faculty-student interaction.
Hypothesis 5. There is no significant difference between white
and non-white student population measurements on the social
system variable.
Hypothesis 6. There is no significant difference between white
and non-white student population measurements on the
peer-group interaction variable.



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125
correlations partially supported relationships, but they are not
presented here to imply any path or causal relationships. The
data presented here were for background information and were not
intended to varify the validity of Tinto's model.
In the present study, the results of multiple linear
regression indicated that social integration, peer-group
interaction, and facu1ty-student interaction did not
significantly affect the perceived dropout decision in any of the
four student groups. Interaction effects between peer-group
interaction and faculty-student interaction were also found to be
non-significant. This was also the case in reference to the
actual student dropout decision on the total campus and West
Campus. East Campus and North Campus showed a statistically
significant association between the variables of peer-group
interaction and faculty-student interaction and the actual
dropout decision. These last results are partially supportive of
Tinto's conceptual model. Tinto hypothesized that social system
integration, comprised of peer-group interaction and
faculty-student interaction, has a direct and significant
influence on the student dropout decision.
The previous results indicating no significance between
social system variables and dropout rate were more supportive of
the reconceptualized model of Tintos' model suggested by
Pascarella, Duby, and Iverson (1983) and Terenzini, Pascarella,
Theophilides, and Lorang (1983). This model hypothesized that
the direct effect of social integration on dropout decision was


146
Jacobs, L.C., Bringman, S.L., & Friedman, C.B. (1982).
Nonreturning university students: Who are they and
why did they leave? Indiana Studies in Higher Education No.
47, Bureau of Evaluative Studies and Testing, Indiana
University, Bloomington, 1-31.
Jaffe, A., & Adams, W. (1970). Academic and socio-economic
factors related to entrance and retention at two and
four-year colleges in the late 1960's. Proceedings of the
American Statistical As so iciation Social Statistics
Section.
Keim, H.D. Ill, Van Allen, G., & Anderson, G.J. (1982). A model
for determining student attrition. Occupational
Education Research Project Final Report, North Carolina
Department of Community Colleges, 1-68.
Kolwalski, Casimir J. (1982). College dropouts: Some research
findings. Psychology, 19 (No 2/3) 45-49.
Lavin, D. (1965). The prediction of academic performance. New
York: Russell Sage Foundation.
Lenning, O.T., Sauer, K., & Beal, P.E. (1980). Student
retention strategies. AAHE-ERIC/Higher Education Research
Report No. 8. Washington: American Association for Higher
Education.
Little, F.W. (1971). The effects of a personal growth group
experience upon measured self-concept of a selected group of
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Univeristy, Dissertation Abstracts, 32, 4956-A. (University
Microfilms No. 72-7987).
Medsker, L., & Trent, J. (1968). Beyond high school. San
Francisco: Jossey-Bass.
Meyer, B.E. (1975). The impact of a human development course on
college students' self-concept, purpose in life, and
interpersonal relations. (Doctoral dissertation, University
of Miami). Dissertation Abstracts, 36, 2671-A. (University
Microfilms No. 75-25, 437).
Moore, J. (1976). An equal opportunity program retention design.
College and University, 51, 692-699.
Munro, B. (1981). Dropouts from higher education: Path analysis
of a national sample. American Educational Research Journal,
J_8, 49-101.


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.
Paul Fitzgerald
Professor,
Counselor Education
This dissertation was submitted to the Graduate Faculty of
the College of Education and to the Graduate School and was
accepted as partial fulfillments of the requirements for the
degree of Doctor of Philosophy.
August 1985
Dean, College of Education
Dean, Graduate School


37
(Baker, 1980; Beck, 1980; Simpson, Baker, & Mellinger, 1980;
Spady, 1970; Spady, 1971; Tinto, 1975). In addition to research
indicating that informal peer-group associations are related to
persistence (Gardiner & Nazari, 1983), semi-formal
extra-curricular activities were also related to students
persisting in college (Chase, 1970; Ramist, 1981; Spady, 1971).
Faculty-Student interaction. Social interaction with
faculty by students, in various forms and degrees, has been shown
to be related to persistence in college (Bean, 1982; Gardiner &
Nazari, 1983; Noel, 1976; Pascarella & Terenzini 1976; Penick &
Morning, 1982; Tinto, 1982). Additional research has concluded
that some types of interaction are more effective than others.
The strongest form of interaction appeared to be informal contact
concerning subject and/or career related material (Pascarella &
Terenzini, 1977). A general conclusion that has been drawn from
the existing research is that increased quantity and/or quality
of faculty-student interaction is advantageous to persistence in
college (Centra, 1971; Hutchenson, 1980; Keim, Van Allen, &
Anderson, 1982; Pancos & Astin, 1968; Reed, 1981; Slocum, 1956;
Spady, 1971; Tinto, 1975; Tinto, 1982).
Summary of the Chapter
Research has shown that social system integration,
peer-group interactions, and faculty-student interaction
variables can potentially affect whether students decide to
remain in school or drop out. According to Tinto's theoretical


59
investigation are described in terms of four groups: total campus
of PHCC, East Campus of PHCC, North Campus of PHCC, and West
Campus of PHCC. The four groups are discussed in reference to
the influence social integration, peer-group interaction,
faculty-student interaction, and the interaction of peer-group
and faculty-student variables had on dropouts with reference to
both dependent variables, perception of dropout decision, and
actual dropout decision.
Multiple linear regression was used to test each of the
first four hypotheses. Each of the four hypotheses was tested for
each of the population groups, total campus, East Campus, North
Campus, and West Campus, using first the students' perceptions of
their dropout decisions as the dependent variable then the
students' actual dropout rate. The total number of analyses was
32. The next nine hypotheses investigated whether there was a
difference between white and non-white students, male and female
students, and students who had taken a human relations course and
those who had not on the social system, peer-group interaction,
and faculty-student interaction variables. A t-test was used to
test these hypotheses. Each of the nine hypotheses was tested
using each of the four groups as separate populations. This
resulted in 36 different analyses. The remaining six hypotheses
investigated whether there was a relationship between accumulated
hours and age with social system, peer-group, and faculty-student
interaction variables. Each of the six hypotheses was tested
using each of the four groups as separate populations. This


DEDICATION
To my parents Jean and George Rom,
Who taught me to accept challenges and conquer fear
To my son David who had to play ball by himself,
Because I was not there;
To my daugher Michele who because of my absence,
Fell asleep while shedding a tear;
To my ever loving wife Lucile,
Who was both mother and father when I was not near;
To my God who when things appeared the darkest,
Gave me strength to see things clear;
This dissertation is dedicated in your honor.


CHAPTER FOUR
FINDINGS
The purpose of this study was to determine what relationship
exists between social system integration variables (peer-group
interaction and faculty-student interaction) and student dropout
decisions in a two-year community college. The investigation
used Tinto's (1975) conceptual framework model to guide the
research. The student's home campus, age, sex, race, total
semester hours completed, and whether a student had completed a
human relations type course were the demographic variables
considered. Background characteristics, commitment (goal and
institutional), academic integration, and social integration
(peer-group interaction and faculty-student interaction) were the
independent variables under investigation.
Two different measurements were used for the dependent
variable. The first dependent variable was students' perceptions
of whether or not they would return the following term. The
second dependent variable was whether the student actually
returned the next term. This was determined from the official
registration of Term II 1985. Even though the total dropout rate
was similar for both, 13.8 percent for dropout perception and
14.5 percent for actual dropout, the individuals differed
greatly. Of the 21 students who replied on the Student Survey
they would not be returning the following term, only 10
57


126
either non-significant or negative (see Figure 2, p.31). In
fact, where the total campus and West Campus data showed no
significant proportion of the variation in dropout rate due to
social system integration, the data did indicated that the higher
the students' background characteristics were the more likely the
student would persist (.05 level).
Table 27 summarizes the results of the 92 test of the 19
hypotheses in this study. Results from the East Campus, with
actual dropout rate as the dependent variable, showed a
significant proportion (11.2%) of the variation in dropout rate
was explained by peer-group interaction (Hypothesis 2) and a
significant proportion (8.6%) of the variation in dropout was
explained by facu1ty-student interaction (Hypothesis 3).
Students who remain in school scored higher on the
faculty-student interaction variable and lower on the peer-group
interaction variable than students who withdrew from school.
Students remaining in school with higher facu1ty-student
interaction scores follow Tinto's theory that the higher the
integration the more likely a student would remain in school. A
possible explanation for the reverse being true for peer-group
interaction was offered by Pascarella and Chapman (1983). They
concluded that students with high levels of peer-group
interaction tend to have high affiliation needs. In an attempt
to fulfill these needs students may transfer to other
institutions and therefore be considered dropouts.


control all
extraneous variables and to manipulate independent
variables.
2. The results of the study were interpreted within the
limitations imposed by the validity and reliability of the survey
instrument used in the investigation and the decisions made
concerning which items to include in the constructed scale scores
for each variable.
3. The generalizability of the findings was limited because
the subjects were not selected randomly from the total population
of two-year college students. They were randomly selected from
within the population of degree seeking students enrolled at
Pasco-Hernando Community College for the Fall term of 1984. Even
though Pasco-Hernando Community College students were felt to be
respresentative of other community college students, further
empirical study must determine the extent to which the findings
will be applicable in other two-year colleges or other
educational institutions.
4. Subjects were limited to students who had declared
programs on the Pasco-Hernando Community College Program
Declaration form (see Appendix A), of either an Associate of Arts
or Associate of Science degree. This assured at least a minimum
commitment to a college education by the students. This
eliminated students from the sample who declared undecided,
certificate program, vocational certificate program, or personal


105
computed t-statistic was 2.00, with means of 10.102 for students
with the course and 9.817 for students without the course. The
test of Hypothesis 11, for both North and West campuses,
exceeded the critical t-statistic at the .05 level of
significance. The decision was to reject Hypothesis 11. North
Campus students who had not had a human relations course scored
higher than students who had the course on the social system
variable. West Campus students who had had a human relations
course scored higher than students who did not have the course.
Hypothesis 12. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
peer-group interaction variable.
Table 21 presents the results for Hypothesis 12. As
indicated, the computed t-statistic for total campus equalled
.419, with means of 10.031 for students with the course and
9.976 for students without the course. East Campus had a
t-statistic of 1.108 and means of 10.067 for students with the
course and 9.771 for students without the course. West Campus
had a t-statistic of 1.215, with means of 10.162 with the course
and 9.912 for students without the course.
The test of Hypothesis 12, in each of the three groups,
failed to exceed the critical t-statistic at the .05 level. The
decision for all three was fail to reject Hypothesis 12. There
was no difference between students who had a human relations
course and students who had not on the peer-group interaction


exceptions were peer-group and faculty-student interaction. The
variable relationships in Tinto's model did not appear to apply
evenly to this commuter school. When commuter populations have
characteristics in common with residential schools, then Tinto's
model of the dropout process may be more applicable than recent
research indicated.
xiii


56
Multiple linear regression analysis was employed to
determine the incremental increase in the explained variance in
2
the persistence/withdrawal behavior (R increase) associated with
different variable sets in Tinto's model. The sets of variables
were entered in an a priori, hierarchical manner consistent with
the causal sequence of the model: (a) background characteristics
(family background, individual attributes, and pre-college
schooling), (b) commitments (goal and institution), (c) academic
system, (d) peer-group interaction, (e) faculty-student
interaction, and social system.
Summary of the Chapter
This chapter contains the methodological procedures used in
this investigation. The development of the survey questionnaire
was described and justified. Finally, this chapter contains a
description of subjects, data collection, and data analysis
techniques.


APPENDIX D
STUDENT SURVEY


58
ultimately withdrew. This resulted in 52.4 percent change of
response. Of the 131 students who said they would return to PHCC
the following term, 119 actually did return; this resulted in a
9.2 percent change in students' decisions concerning dropout.
Therefore, two different dependent variables were independently
measured and analyzed: (1) students' perceptions of whether they
would return to Pasco Hernando Community College the following
term and (2) actual dropout rate the following term.
The researcher pilot tested the survey instrument to be used
in the study on students attending all three campuses of Pasco
Hernando Community College in the Summer term of 1984.
Permission was obtained from the administration of PHCC to run
the full study on the student body of PHCC the Fall term of
1984. The Student Survey (appendix D) was designed to obtain
information concerning the independent and dependent variables
under investigation.
The original intent of this study was to test 19 hypotheses
on the total population of 152 subjects. An additional
consideration of interest developed; specifically, was there
differences between the three individual campuses that comprise
the total population in reference to the 19 hypotheses. Because
of this concern a total of four different population groups was
tested.
This chapter describes the results of the study. First,
demographic data of the participants are presented and discussed.
Then results pertaining to each of the hypotheses under


Table 20
Means, S.
D. ,
and Computed
t-Statistic Compari
nf> Students
Who Have
Had a Human
Relations
e Course With
Students
Who Have
Not on the
Social System Variable
HUMAN RELATIONS COURSE
NO HUMAN
RELATIONS
COURSE
CAMPUS
HYP.
NO.
MEAN
S.D.
NO.
MEAN
S.D.
df
t
Total
1 1
59
10.061
.706
93
10.047
1.079
150
.098
East
11
15
10.300
.982
24
10.324
1.869
37
-.052
North
1 1
17
9.787
.502
22
10.237
.546
37
-2.670*
West
1 1
27
10.102
.594
47
9.817
.578
72
2.000*
*£<.05
104


BIOGRAPHICAL SKETCH
Michael G.Rom was born in Pittsburgh, Pennsylvania. He
attended elementry and secondary schools in Orlando, after moving
to Florida in 1953. He graduated from Edgewater High School in
Orlando, Florida in 1965. In 1969 he received his Bachelor's of
Arts degree in Psychology from the University of South Florida.
He worked in Dade City, Florida teaching special education while
receiving his Masters of Education degree in 1972. During his
employment with Pasco County as Dean of Students and Assistant
Principal, he continued his education resulting in administration
certification.
When he started his full-time employment at Pasco Hernando
Community College, in 1978, he also began work on his doctorate
at the University of Florida. During this time he was employed
full-time by Pasco Hernando Community College, with additional
part-time employment by St. Leo College and First United
Methodist Church. He plans on continuing his full-time career at
Pasco Hernando Community College as a classroom instructor.
186


33
more open democratic, supportive, and less conflicting
relationships (Congdom, 1964; Trent 6 Ruyle, 1965; Willner,
1980). In addition, these parents expressed more interest and
offered more advice concerning college experience than
non-persisters 1 parents (Trent & Ruyle, 1965). Hackman and
Dysinger (1970) also confirmed that the greater the parental
expectations the more likely the student would remain in school.
Slocum, in his 1956 study, received a postive response from 81
percent of college persisters and only 35 percent from the
dropouts to the following question, "Do your parents want you to
finish college?"
Individual attributes. There are many individual
characteristics that could be correlated with dropout behavior,
such as personality traits and attitudinal differences. These
variables certainly should not be discredited concerning their
possible influence. Two particular characteristics have received
the most research support concerning their relationship to
student persistence in college: grade point average (GPA) in high
school and scores on a standardized test.
The grade point average in high school indicates the
students' ability and serves as a measurement of their past
success (Bean, 1982; Blanchfield, 1971; Chase, 1970; Coker, 1968;
Hutchenson, 1980; Jaffe 6 Adams, 1970; Lavin, 1965; Pancos &
Astin, 1968; Prather, 1982; Taylor & Hanson, 1979; Willner,
1980). Tinto (1975), Edwards and Waters (1982), and Pascarella


94
condition the independent sample t-test tends to be
conservative. Even with a conservative test the results met the
criterion for significance at the .05 level. East Campus
students showed a significant difference at the .05 level with a
computed t-statistic of 2.134 in the direction of white
students. North Campus reported means of 10.064 for white
students and 9.758 for non-white students with a computed
t-statistic of .714. West Campus students means were 9.921 for
white students and 9.919 for non-white students with a reported
t-statistic of .014.
The conclusion for East Campus was to reject Hypothesis 5
and fail to reject it for the North and West campuses. East
Campus white students scored higher on the social integration
variable than did the non-white students. There were no
differences between the white and non-white students on the
social system variable by students on either the North or West
campuses. v
Hypothesis 6. There is no significant differences
between white and non-white student population
measurements on the peer-group interaction variable.
Table 15 contains the data for Hypothesis 6. The computed
t-statistic for total campus was 1.336 with means of 10.017 for
white students and 9.724 for non-white students. Since this did
not exceed the critical t-statistic at the .05 level the result
was fail to reject the Hypothesis 6. There was no difference
between white and non-white students' scores on the peer-group


Table 14
Means, S.D., and Computed t-Statistic Comparina White
and Non-White Students on the Social System Variable
CAMPUS
HYP .
NO.
WHITE STUDENTS
MEAN
S.D.
NON-
NO.
-WHITE STUDENTS
MEAN S.D.
df
t
Total
5
142
10.074
.972
10
9.750
.460
150
1.942
East
5
34
10.409
1.658
5
9.678
.426
37
2.134*
North
5
36
10.064
.559
3
9.758
.726
37
.714
West
5
72
9.921
.604
2
9.919
.199
72
o

*£<.05


Table 15
Means, S.D., and Computed t-Statistlc Comparing White and \
Non-White Students on the Peer-Group Interaction Variable
CAMPUS
HYP.
NO.
WHITE STUDENTS
MEAN
S.D.
NON
NO.
-WHITE STUDENTS
MEAN
S.D.
df
t
Total
6
1 42
10.017
.758
10
9.724
.664
150
1.336
East
6
34
9.943
.761
5
9.491
.481
37
1.796
North
6
36
10.101
.710
3
10.076
.923
37
.045
West
6
72
10.009
.785
2
9.775
.830
72
.394
*£<.05


Table 10
R, R~ Increase and Computed F Ratios for the Full Model and
Partial Regrssion Coefficients Relating Students' Perceptions of
Dropout Decisions With Faculty-Student Interaction by Campus
Dependent
Variable:
Students'
Perceptions
of Dropout Decisions
Campus
2 2
R full F R
increase
F partial
Total
.035
1.065
.001
.268
East
.152
1.181
.025
.978
North
.054
.374
.006
.192
West
.050
.715
.001
.031
*£<.05
Table 11
2 2
R, R Increase and Computed F ratios for the Full Model and
Partial Regresson Coefficients Relating Students' Actual Dropout
Decisions With Faculty-Student Interaction by Campus
Dependent
Variable:
Student s'
Actual Dropout
Decisions
Campus
R2
F R
2
increase
F partial
Total
.063
1.875
.001
.002
East
.334
3.305*
.086
4.453*
North
.242
2.112
.167
7.284*


29
Pascarella, Duby, and Iverson (1983) have revised Tinto's
model to better reflect their findings. Based on their research,
a reconceptualization of Tinto's model was offered (Figure 2
p.30). This revised model was intended to provide more
explanatory power in a non-residential institution.
*
The model assumes that the characteristics which students
bring to college will not only influence their interactions with
the college environment, but will also have important direct
effects on persistence. In Tinto's original model, these
characteristics were seen basically as determinants of students'
integration with the academic and social systems rather than
having any direct influence.
Even though social and academic integration were retained
as major elements of the model, some revisions were made.
Academic integration was hypothesized as having a direct
influence on persistence and an indirect effect through its
influence on goal commitment. This was consistent with Tinto's
model. The direct effect of social integration was hypothesized
to be either non-significant (suggested by Pascarella & Chapman,
1983) or negative. This departure of social intergrations'
influence from Tinto's model was based on two assumptions.
First, commuter schools generally provide fewer social
integration opportunities than residential schools and second
this fact may lead to a more complex relationship between social
integration and persistence than originally hypothesized by
Tinto.


WRITTEN ENGLISH
Part I
Directions: In each of the following sentences find out what is
wrong, if anything. In deciding whether there is something wrong
with the sentence, consider the way a sentence should be written
in standard written English, the kind of English usually found in
textbooks. Remember that standard written English is sometimes
different from conversational English.
Some sentences are acceptable without change.
No sentence contains more than one error.
If the sentence has an error, you will find the error is
underlined and lettered. Assume that all other parts of the
sentence are acceptable and cannot be changed.
When you find an error, select the one underlined part that must
be changed in order to make the sentence acceptable, and put an X
in the corresponding blank on the answer sheet.
If there is no error, mark D.
Sample Questions
1. Tom ate the hamburger, which
A
was piled high with onions, it was
B C
good. No error
D
2. Next week Mrs. Wilson has visted 2. A B C D
A
her sister in Chicago. No error
B CD
You will have 10 minutes to work on the 20 questions in Part 1.
Sample Answers
1 A B C D
DO NOT TURN THIS PAGE UNTIL YOU ARE TOLD TO DO SO
(OR, IF SELF-ADMINISTERED,
UNTIL YOU HAVE BEGUN TO TIME YOURSELF)
154


134
significant results in relationship to Hypothesis 3 and North
Campus, with significant results in relationship to Hypothesis 2
certainly demonstrated a direct and positive relationship between
the variables faculty-student interaction and peer-group
interaction respectively and the student's decision to drop out.
It is important to note that even though these results supported
Tinto's model, the negative influence of peer-group interaction
on the East Campus and the faculty-student interaction on the
North Campus tended to support the reconceptualized model.
Other relationships, in Tinto's model, that existed to some
extent were the academic system variable correlated at a
significant level with the dropout decision variable (£<.05), and
the variable commitments with the academic system variable
(£<.05). There were other variable relationships notably
missing, i.e., background characteristics with commitments,
commitments with social system, and academic system with social
system. It should be noted that two of these relationships in
Tinto's model, missing from East Campus, exsisted on other
campuses. West Campus showed a positive correlation between
commitment and social system variable at the .05 level of
significance. Total, North, and West campuses, all recorded
positive correlations, significant at the .05 level, between the
academic system and social system variables. These concluding
remarks are not meant to imply path relations that might result
from path analysis, there inclusion is to imply that an exact fit
of Tinto's model to the East Campus was not achieved.


Table 18
Means, S.D., and Computed t-Statistic Comparing Male and
Female Students on the Peer-Group Interaction Variable
CAMPUS
HYP.
NO.
MALE STUDENTS
MEAN S D.
NO.
FEMALE STUDENTS
MEAN S D.
df
t
Total
9
50
10.001
.935
102
9.996
.652
150
.035
East
9
1 1
9.468
.650
28
10.049
.721
37
-2.437*
North
9
14
10.057
.677
25
10.123
.746
37
-.280
West
9
25
10.204
1.088
49
9.900
.552
72
1.312
*p<.05
100


THREE METHODOLOGY 40
Instrumentation 40
Description of Student Survey 40
Development of Student Survey 42
Variables 42
Pilot Study 50
Present Study 51
Subjects 51
Data Collection 52
Data Analysis 52
Summary of the Chapter 56
FOUR FINDINGS 57
Descriptive Analysis 60
Demographic Variables 60
Correlations 66
Regression Analysis 78
Hypotheses 1-4 78
Hypotheses 5-13 92
Hypotheses 14-19 107
Anova Between Campuses 112
Summary of the Chapter 113
FIVE SUMMARY, CONCLUSIONS, IMPLICATIONS,
AND RECOMMENDATIONS 117
Summary 117
Conclusion 122
Implications 134
Recommendations 138
REFERENCES 142
APPENDIX
A PROGRAM DECLARATION 152
B WRITTEN ENGLISH EXPRESSION PLACEMENT
TEST 154
C READING PLACEMENT TEST 164
D STUDENT SURVEY 175
E MONITOR INSTRUCTIONS 185
BIOGRAHICAL SKETCH 186
vi


24
Validity of Tinto*s Model in Residential Settings
Research findings related to Tinto's (1975) model by
Pascarella and Terenzini (1983) concluded that
persistence/withdrawal behavior is essentially the result of a
longitudinal process of person-environment fit as theorized by
Tinto. Specifically, background characteristics and
institutional commitments explained little variance in
2
persistence with reported R increases of only .9 percent and 1.3
percent respectively. With alpha levels set at .01, significant
2
R increases occurred with the addition of the academic and
social integration scales. Therefore, both academic integration
and social integration had a direct influence on persistence.
Terenzini, Pascarella, Theophilides, and Lorang (1983)
support the major constructs and their causal linkages in Tinto's
model of college student attrition, with some noteworthy
exceptions. In comparing their study of a public, residential
school (study 2) with Pascarella and Terenzini's (1983) study of
a private, residential school (study 1), the following
differences were reported. In the second study the investigators
found that a significant and direct path was lacking between
students' level of academic integration, as was reported in the
first study and college persistence. This direct path was
present until subsequent institutional commitment was added to
the model. It is suggested that this non-significant direct path
may be artifical due to the fact that academic integration still
has a strong indirect effect on persistence.


91
The full models for total, East, North, and West campuses
2
yielded R 's of .024, .155, .064, and .055, with F-statistics of
.587, .981, .365, and .644 respectively. All four were non
significant at the .05 level. When the dependent variable was
students' perceptions of dropout decisions, the partial
2
regression coefficients' R increase and computed F-statistic
were .004 and .001 for total campus, .004 and .137 for East
Campus, .010 and .357 for North Campus, and .005 and .327 for
West Campus. None of these computed F-statistics exceeded the
critical F-statistic at the .05 level. The decision in all four
cases was a fail to reject Hypothesis 4. There was no
interaction effect between the peer-group interaction variable
and the faculty-student interaction variable.
When the dependent variable was students' actual dropout
2
decisons (Table 13), the full models yielded R and F-statistics
2
as follows: for total campus R .064 and F-statistic 1.875, for
2
North Campus R .292 and F-statistic 2.198, and for West Campus
2
R 1.32 and F-statistic 1.695. All were non-significant at the
.05 level. The partial regression coefficients of the total
2
campus had an R increase of .003 and a computed F-statistic of
2
.522, North had an R increase of .049 and an F-statistic of
2
2.232, and West Campus had an R increase of .001, with an
F-statistic of .107. Each failed to exceed the critical
F-statistic and resulted in a conclusion of a fail to reject
Hypothesis 4. East Campus's full model had a computed
2
F-statistic of 2.746, with an R of .340, which did exceed the


133
take the course (Hypothesis 11). These results are in line with
several authors who have indicated that human relations type
courses are advantageous to social integration (Meyer, 1975;
Wall, 1979; & Beck, 1980). There is some difficultly in
explaining why on the West Campus, human relations type courses
were related to social integration in a positve direction, on the
North Campus related in a negative direction, and on the East
Campus there was no significant relationship. The only real
significant student difference between campuses was the
faculty-student interaction variable.
East Campus students scored significantly higher on the
facu 11y-student interaction ( £<.05) than West campus
students. This difference between campuses was of interest
because faculty-student interaction was a component of the social
system integration variable. The difference between
faculty-student interaction between campuses involved the whole
faculty body not just the instructors of human relations type
courses. Therefore, it would be wrong to place too much emphasis
on human relations instuctors as an influence on the
faculty-student interaction on any given campus. Even though
there may be implications drawn from these differences in social
systems and human relations type course offerings, it would be
inappropriate to assume human relations type courses caused these
differences in campus social system.
This study does partially confirm Tinto's (1975) conceptual
framework model for dropout decisions. East Campus, with


APPENDIX B
WRITTEN ENGLISH EXPRESSION
PLACEMENT TEST


Table 16
Means, S.D., and Computed t-Statlstic Comparing White and
Non-White Students on the Faculty-Student Interaction Variable
CAMPUS
HYP.
NO.
WHITE STUDENTS
MEAN
S.D.
NON-
NO.
-WHITE STUDENTS
MEAN
S.D.
df
t
Total
7
142
10.015
.802
10
9.777
.499
150
1.386
East
7
34
10.404
.959
5
9.866
.487
37
1.973
North
7
36
9.999
.648
3
9.438
.530
37
1.731
West
7
72
9.838
.734
2
10.063
.433
72
-.704
*£<.05


25
Another discrepancy reported by study 2 was that the direct
path between social integration and persistence was marginally
reliable (£<.15) and the influence was negative. This finding
was in direct conflict with Tinto1s theory and previous
research. Possible speculative explanations were provided by the
authors of study 2. They suggested excessive social involvement
may reduce time spent studying, and withdrawal due to the
student's recognition of poor academic performance was preferred
over academic dismissal. The authors emphasized the fact that
these were only speculations.
Study 2 confirmed findings in study 1 that indicated
students' background characteristics had no direct effect on
retention of students. Instead, background characteristics
influence was dependent on the student's interaction with the
institution and the student's experience in college.
Validity of Tinto*s Model in Non-residential Setting
There is a growing body of research investigating the
appropriateness of Tinto's model in relationship to
non-residential schools. The research of Pascarella and Chapman
(1983) compared the validity of Tinto's (1975) model of college
withdrawal in three different types of institutions: four-year
residential institutions, four-year commuter institutions, and
two-year commuter institutions. The pooled analysis generally
supported a number of Tinto's theoretical expectations, but there
were variations between institutional setting types which were
relative to this study.


18
Intellectual development. The se1f-perceived growth of a
student in the areas of: general knowledge, reasoning skills,
critical thinking skills, and appreciation of new ideas.
Peer-Group interaction. The degree to which a student
perceives an institution as being receptive socially and the
degree the student feels accepted by the institution. Also the
degree to which a student feels other individuals demonstrate
accepting behaviors and to what degree a student feels accepted
by others.
Pre-College schooling. Characteristic of the school setting
that students were exposed to prior to entering college.
Social system. The combined effects of peer-group
interaction and faculty-student interaction on the students'
integration into the social setting of an institution.
Social integration. The degree of social communication,
friendship support, faculty support, and collective affiliation
students perceive they possess in a social environment.
Organization of Remainder of the Research Report
The following chapters are utilized in the remainder of the
research report. Chapter Two discusses dropouts in general and
additional research and literature that were pertinent to the
investigation. Chapter Three contains the procedures used to
formulate the survey instrument, the pilot study, along with the
complete methodology used in the study. Three campuses of a


181
23.My non-classroom interactions with PHCC
faculty members have had a positive in
fluence on my career goals and aspir-
ations.....................................SA A NS D SD
24. Only a few of the PHCC faculty members
I have had contact with are genuinely
outstanding or superior teachers SA A NS D SD
25. Only a few of the PHCC faculty members
I have had contact with are genuinely
interested in students SA A NS D SD
26. Most PHCC faculty members I have had
contact with are genuinely interested
in teaching SA A NS D SD
SECTION FOUR: Social Integration
This information is concerned with the combined
effects of peer-group interaction and faculty
interaction on the students' integration into the
social setting of an institution.
Directions: Please follow the same directions outlined in
Section Three.
27.
28.
29.
30.
My interpersonal relationships with
other students at PHCC have had a pos
itive influence on my intellectual
growth and interest in ideas
Since coming to PHCC I have develpoed
close personal relationships with other
students
The student friendships I have developed
at PHCC have been personally satisfying..
My interpersonal relationships with other
students at PHCC have had a positive in
fluence on my personal growth,values, and
attitudes
A
NS
D
SD
A
NS
D
SD
. .SA
A
NS
D
SA
A
NS
D
SA
PLEASE CONTINUE TO THE NEXT PAGE


Table 1-continued
PHCC
TOTAL
EAST
CAMPUS
NORTH
CAMPUS
WEST
CAMPUS
VARIABLES
FREQ.
PERCENT
FREQ.
PERCENT
FREQ.
PERCENT
FREQ.
PERCENT
Human
Relations
yes
59
38.8
15
38.5
17
43.6
27
36.5
no
93
61.2
24
61.5
22
56.4
47
63.5
Accumulated
Credit Hours
1- 9
43
28.2
15
38.4
10
25.6
18
24.3
10-18
44
28.9
10
25.6
8
20.5
26
35.1
19-27
28
18.4
5
12.8
4
10.2
19
25.6
28-36
17
11.1
5
12.8
8
20.5
4
5.4
37-45
12
7.8
2
5.1
8
20.5
2
2.7
46-54
7
4.6
2
5.1
1
2.5
4
5.4
5 5+
1
.6
0
0.0
0
0.0
1
1.3
Dropout
Decision
Perception
return
131
86.2
33
84.6
33
84.6
65
87.8
dropout
21
13.2
6
15.4
6
15.4
9
12.2
Dropout
Decision
Actual
return
130
85.5
33
84.6
35
89.7
62
83.8
dropout
22
14.5
6
15.4
4
10.3
12
16.2
O'
ro


86
Hypothesis 3. A significant proportion of the variation
in student dropout rate is not explained by
faculty-student interaction after controlling for student
background characteristics, student commitments, the
academic system, and peer-group interaction.
The test of the hypothesis was a test of the partial
regression coefficient for the faculty-student interaction given
that background characteristics, commitments, academic system,
and peer-group interaction were in the model. The results of
the analysis are presented in Table 10 with students'
perceptions of dropout decisions as the dependent variable.
The test of the full model with all the variables in
2
yielded an R of .035 and an F-statistic of 1.065. This was
found to be non-significant at the .05 level. The partial re
gression coefficient for the total campus was .034. The faculty
student interaction variable therefore explained an additional
.1 percent of the variation in dropout rate. This increase in
variation resulted in a computed F-statistic of .268, which did
not exceed the critical F-statistic at the .05 level. Therefore
the conclusion was to fail to reject Hypothesis 3. Faculty
student interaction did not improve prediction of perceived
dropouts.
The full models for the East, North, and West campuses re-
2
suited in R~' s of 152, .054, and .050 with F-statistics of
1.181, .374, and .715. All were non-significant at the .05
2
level. The R increase and computed F-statistic for East Campus


145
Faunce, P. (1966). Personality characteristics and vocational
interests related to the college persistence of academically
gifted women. (Doctoral dissertation, University of
Minnesota, 1966). Dissertation Abstracts, 2 8 338-B.
(University Microfilms, Abstract No. 67-7722.
Fiedler, D., & Vance, E.B. (1981, August). To stay or leave
the university: Every student's dilemma. Paper presented at
the American Psychological Association, Los Angeles, CA.
Flacks, R. (1963). Adaptations of deviants in a college
community. Unpublished doctoral dissertation, University
of Michigan.
Gardiner, J.J., & Nazari, R.A. (1983). Student attrition
research: Implications for retention strategies. NASPA
Journal, 20, 25-33.
Gottfredson, D. C. (1982). Personality and persisence in
education: A longitudinal study. Journal of Personality
and Social Psychology, 43, 532-545.
Grant, V. W., & Eiden, L. J. (1982). Digest of Education
Statistics 1982, 14.
Gurin, G. Newcomb, T.M., & Cope, R.G. (1968). Characteristics
of entering freshmen related to attrition in the
literary college of a large university. Office of
Education, U.S. Department of Health, Education, and Welfare
Project No. 1938. Ann Arbor, Mich.: Survey Research
Center, Institution for Social Reserch, University of
Michigan.
Hackman, J., & Dysinger, W. (1970). Research notes: Commitment
to college as a factor in student attrition. Sociology
of Education, 43, 311-324.
Hahn, R. ( 1 974). In defense of dropping out. Communit y
College Review, 35-40.
Hanson, G., & Taylor, R. (1970). Interaction of ability and
personality: Another look at the dropout problem in an
institute of technology. Journal of Counseling Psychology
17, 540-545.
Hutchenson, S. M. (1980, April). The influence of academic and
social integration on upper class college student attrition.
Paper presented at the American Educational Research
Association, Boston.


112
Hypothesis 17. There is no correlation between student
age and the social system variable.
All four hypotheses were found to be non-significant at
the .05 level. Coefficients for total campus -.048, for East
-.058, for North -.019, and for West .014 resulted in a failure
to reject decison for Hypothesis 17. There is no correlation
between students' age and the social system variable.
Hypothesis 18. There is no correlation between student
age and peer-group interaction.
Correlation coefficients recorded were total campus .008,
East -.149, North .014, and West .034. None of these were found
to be significant at the .05 level and therefore a fail to
reject decision was made for Hypothesis 18. There is no
correlation between students' age and the peer-group interaction
variable.
Hypothesis 19. There is no correlation between student
age and faculty-student interaction variable.
As a result of the correlation coefficients recorded by
the different campuses, total -.047, East .079, North -.034, and
West -.022, a decision of fail to reject Hypothesis 19 was made.
None of the four correlation coefficients were found to be
significant at the .05 level. There is no correlation between
students' age and the faculty-student interaction variable.
ANOVA Between Campuses
When the dependent variable was students' actual dropout
rate, East and North campuses showed significance on Hypotheses


21
individual student. The concept of personal-institutional fit as
an explanatory concept for student dropout has created much
interest in postsecondary research (Aitken, 1982; Baumgart &
Johnstone, 1977; Bean, 1981). It would follow then that the
validity of Tinto's (1975) model has been the focus of recent
research (Pascarella & Chapman, 1983; Pascarella, Duby, &
Iverson, 1983; Pascarella & Terenzini, 1983; Terenzini,
Pascarella, Theophilides, & Lorang, 1983).
Pascarella and Terenzini (1980) generally supported the
predictive validity of the major dimensions of the Tinto model
after sampling 763 students at Syracuse University. By adding
five institutional integration scales to a discriminant analysis
based on fourteen pre-college characteristics, freshman year
academic performance, and extracurricular involvement, they were
able to increase the correct identification of persisters and
dropouts from 58.2 percent to 81.4 percent.
Additional support for Tinto1s model was reported by
Terenzini, Pascarella, Theophilides, and Lorang (1983) in which
an earlier path analytic study (Pascarella & Terenzini, 1983) of
the predictive validity of Tinto's theory of college student
attrition was replicated. The study by Pascarella and Terenzini
(1983) produced 24 significant paths in Tinto's model and
Terenzini, Pascarella, Theophilides, and Lorang (1983) identified
22. Sixteen or 72.7 percent of these paths were common to the
two studies. Both institutions were large, comprehensive,


155
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Part 1
Time-10 minutes
20 Questions
1. In 1968 Julian Bond could not accept the vice-presidential
A
nomination he was too young to qualify for the position. No
B C
error
D
2. The strike came at a time where the public supported efforts
A
to improve the lot of the farm workers. No error
B C D
3. I_f one wants to prepare drawings for an engineer, they must
A B C
work with accuracy and precision. No error
D
A. Like many other young boys, Samuel likes both playing
A
football and he watches games on television. No error
B C D
5. Nathan was scarce more interested in hiking than he was in
A B
poetry. No error
C D
6. Montoya's latest photographs show with great clarity the joy
A B
that adopting a baby brings. No error
C D
7. Because General MacArthur and General Eisenhower were the
Allied commanders, we studied that general1s strategy Ln history
A B C
class. No error
D
GO ON TO THE NEXT PAGE


157
16.Trying to understand the formula i^£ as difficult as
A B
Einstein. No error
C D
17.The researchers hope to use the armadillo to help them study
A
leprosy, which until now can be studied only in humans. No error
BCD
18.The Quinault tribe finally closed the land to vacationers,
A B
they had defaced sacred rocks with spray paint and left tons of
C
litter on the beaches. No error
D
19.Waste poured into the upper reaches of the Susquehanna has
A
begun to pollute that river. No error
B C D
20.Leroy enjoyed installing air-conditioning equipment more
A
than repairing them. No error
B CD
STOP
IF YOU FINISH BEFORE TIME IS UP, CHECK YOUR WORK ON THIS PART
ONLY. DO NOT GO ON TO PART 2 OF THIS TEST UNTIL YOU ARE TOLD.


Table 1
Frequency and Percentage Distribution for Demographic Variables
VARIABLES
PHCC TOTAL
FREQ. PERCENT
EAST
FREQ.
CAMPUS
PERCENT
NORTH CAMPUS
FREQ. PERCENT
WEST
FREQ.
CAMPUS
PERCENT
Subjects
152 100
39
25.6
39 25.6
74
48.6
Ages
17-21
83
54.6
26
66.6
21
53.8
36
48.6
22-26
20
13.2
6
15.3
5
12.8
9
12.2
27-31
21
13.8
3
7.6
4
10.2
14
18.9
32-36
9
5.9
2
5.1
2
5.1
5
6.8
37-41
6
3.9
1
2.5
2
5.1
3
4.1
42-46
8
5.3
0
0.0
5
12.8
3
4.1
47-51
2
1.3
1
2.5
0
0.0
1
1.3
52-56
2
1.3
0
0.0
0
0.0
2
2.7
57+
1
.7
0
0.0
0
0.0
1
1.3
Sex
males
50
32.9
11
28.2
14
35.9
25
33.8
females
102
67.1
28
71.8
25
64.1
49
66.2
Race
white
142
93.4
34
87.2
36
92.3
72
97.3
non-white
10
6.6
5
12.8
3
7.7
2
2.7
(continued)


64
differences adequately reflected the percentages of white and
non-white students attending those individual campuses.
The percentage of students, in the sample, who had had a
human relations type course was 38.8 percent. Similar
percentages were found on the East and West campuses, 38.5
percent and 36.5 percent respectively. A higher number of
subjects had a human relations type course on the North Campus
(43.6 percent). Even though accurate records were not available
for the total population, in reference to this variable, this
researcher's general impression was that similar participation
had occurred for the total population.
The next item listed in Table 1 revealed the frequency range
of accumulated credit hours. Students with 1 to 9 hours account
ed for (28.2 percent) of the total population, 10 to 18 (28.9
percent), 19 to 27 (18.4 percent), 28 to 36 (11.1 percent), 37 to
45 (7.8 percent), 46 to 54 (4.6 percent), and 55+ (.6 percent).
Differences appeared in accumulated semester hour frequency
figures between campuses. The total campus and East Campus had
similar percentages of students with less than 28 semester credit
hours accumulated, 75.5 percent and 76.8 percent respectively .
These percentages indicated a larger number of freshmen in
attendance than sophomores. West Campus had an even larger
proportion of freshmen with 85 percent. North Campus appeared to
have the most balanced freshmen and sophomore classes with 56.3
percent of the students having less than 28 semester hours
accumulated.


115
Table 26
Survey Questionnaire
LIMITS
LIMITS
LIMITS
VARIABLE EAST/NORTH
EAST/WEST
NORTH/WEST
FACULTY-
STUDENT
INTERACTION (-.0144,.7710)
*(.1434,.8365)
(-.2344,.4586)
'
*£<05


APPENDIX E
MONITOR INSTRUCTIONS


88
were .025 and .978, for North Campus .006 and .192, for West
Campus .001 and .031. In each case the computed F-statistic did
not exceed the critical F-statistic at the .05 level and the
decision was to fail to reject Hypothesis 3.
2
The full model R for total campus, with students' actual
dropout decisions as the dependent variable, was .063. This
resulted in a non-significant F-statistic of 1.875. Without
2
faculty-student interaction in the model, the R for the partial
regression coefficient was .062. Thus facu 11y-student
interaction explained .1 percent additional variation in
dropout. This increase in variation gave a computed F-statistic
of .002, which did not exceed the critical F-statistic at the
.05 level. The conclusion was to fail to reject Hypothesis 3.
2
The full model on East Campus had an R of .334 and an
F-statistic of 3.305, which was significant at the .05 level.
The East Campus partial regression coefficient of .136 had an
2
increase in R of .086, which gave a computed F-statistic of
2
4.253. This variation in R was significant at the .05 level,
since the computed F-statistic exceeded the critical
F-statistic. The conclusion was to reject Hypothesis 3.
Students who had high scores on faculty-student interaction were
less likely to drop out. The full model of North and West
2
campuses resulted in R 's of .242 and .131 and non-significant
F-statistics of 2.112 and 2.055 at the .05 level. The partial
regression coefficient for West campus did not achieve
2
significance at the .05 level, with R increase of .005 and an


14
objectives as their anticipated goal. By eliminating these four
groups, potential dropouts would not be eligible for the sample,
and therefore would limit the generalizability of the findings.
5. The dropout rate for degree seeking students in this
study was approximately 15 percent. This low dropout rate plus
the small sample size from each individual campus may limit the
validity of some of the statistical analysis.
6. Because of the large number of tests of hypotheses (92)
it might be expected, due to the error rate, that at least one
hypothesis might be found statistically significant in reference
to any given campus.
Significance of the Study
Academic failures are generally accepted as a category of
dropouts from educational institutions. There is a second
category of students, although academically capable, who lack
forms of personal and/or social qualities that prevent them from
becoming properly integrated into the college social environment.
Noel (1976), reporting on the findings of a national seminar on
retention, stated that the seminar group realized the need to
study the interaction between students and their institutional
environment. The University of California, Los Angeles, Academic
Advancement Program has also identified difficulty in adjusting
to campus life as one of the central areas of students' problems
(Moore, 1976). Edwards and Waters (1983) also suggested that lack
of satisfaction with the non-academic part of college could
contribute to students dropping out.


TABLE OF CONTENTS
PAGE
ACKNOWLEDGEMENTS iii
LIST OF TABLES vii
LIST OF FIGURES x
ABSTRACT xi
CHAPTER
ONE INTRODUCTION I
Tinto's Model 5
Statement of the Problem 9
Hypotheses 9
Assumptions 12
Delimitations 12
Limitations 12
Significance of the Study 14
Definition of Terms 16
Organization of the Dissertation 19
TWO REVIEW OF THE LITERATURE AND RELATED RESEARCH 20
Review of the Literature 22
Validity of Tinto's Model in Residential
Settings 24
Validity of Tinto's Model in Non-residential
Settings 25
Reconceptualization of Tinto's Model 28
Variables 31
Family Background 32
Individual Attributes 33
Pre-College Schooling 34
Institutional Commitment 34
Goal Commitment 35
Grade Performance 35
Intellectual Development 36
Peer-Group Interaction 36
Faculty-Student Interaction 37
Summary of the Chapter 37
v


144
Churchill, W.D., & Iwai, S.I. (1981). College attrition,
student use of campus facilities, and a consideration of
self-reported personal problems. Research in Higher
Education, 14 (4), 353-365.
Coker, D. (1968). Diversity of intelligence and non-intel-
lective characteristics between persisting students and
non-persisting students among campuses. Washington, DC:
Office of Education Report, BR-6-2728. (ERIC
Reproduction Service No. 033 645).
Congdon, R.G. (1964). Personality factors and the capacity to
meet curriculum demands. Personnel and Guidance Journal,
42, 17-31.
Cope, R., & Hannah, W. (1975). Revolving college doors: The
causes and consequences of dropping out, stopping out and
transferring. New York: Wiley-interscience.
Creamer, D. G. (1980). Educational advising for student
retention: An institutional perspective. Community College
Review, 7, 11-18.
Daniel, K.L.B. (1963). A study of dropouts at the University of
Alabama with respect to certain academic and personality
variables. (Doctoral dissertation, University of Alabama,
1963). Dissertation Abstracts, 25, 173-B. (Ann Arbor, MI:
University Microfilms, No. 64-9118).
Davis, J.A. (1966). The campus as a frog-pond. American Journal
of Sociology, 72, 17-31.
Day, V. H. (1982). Validity of an attributional model for a
specific life event. Psychological Reports, 50, 434.
Denzin, N.K. (1966). The significant others of a college
population. Sociological Quarterly, 7_, 298-310.
Durkheim, E. (1961). Suicide. (J. Spaulding & G. Simpson,
Trans). Glencoe, Ill., The Free Press.
Edwards, J.E., & Waters, L.K. (1982, Winter). Involvement,
ability, performance, and satisfaction as predictors of
college attrition. Education and Psychological
Measurement, 42, 1149-1152.
Edwards, J.E., & Waters, L.K. (1983). Predicting university
attrition: replication and extension. Educational and
Psychological Measurement, 43, 233-236.


CHAPTER ONE
INTRODUCTION
Substantial time and interest have been dedicated to college
student attrition as is represented in the work of by Spady
(1970); Cope and Hannah (1975); Tinto (1975); Pantages and
Creedon (1978); and Lenning, Sauer, and Beal (1980). Despite all
the research, community college attrition rates have remained
high and virtually unchanged.
A national survey conducted in the spring of 1979 by the
American College Testing (ACT) Program and the National Center
for Higher Education Management Systems verified this consistency
in attrition rates (Beal & Noel, 1979). Retention after one year
in two-year public institutions was 55 percent in 1975-76, 55
percent in 1976-77, and 53 percent in 1977-78 as reported by 74,
82, and 92 two-year institutions respectively. More recent
statistics also confirmed a 50 percent dropout rate in
postsecondary schools (Grant & Eiden, 1982).
Prior to the 1970's, much of the research on attrition was
atheoretical, identifying a variety of associations among various
student and institutional characteristics and attrition, but
lacked a theoretical base by which attrition could be studied.
Tinto (1975) attempted to bring some coherence to this research
as well as provide a conceptual framework to guide future
research. Tinto expanded Spady1s (1970) work on student
1


Table 5
Pearson Product Moment Correlation for
Endogenous
and Exogenous
VariablesWest
Campus
VARIABLES 1
2
3
4 5
6
7
1 .
Age
.178
-. 0A0
.030 .125
.054
.022
2.
Sex
-.057
.125 .126
.036
.275*
3.
Race
.171 .220
-.044
.064
4.
Accumulated Hours
.357*
.270*
.154
5.
Human Relations Course
.126
.105
6.
Background Characteristic
.168
7.
Commitment
8.
Academic Integration
9.
Peer-group Interaction
10.
Faculty-student Interaction
11.
Social Integration
12.
Dropout Perception
13.
Dropout Actual
(continued)
*p<.05


52
confounding variables involved with individuals who might be
taking a limited number of courses to complete a certificate
program, vocational certification program, personal objectives
(i.e.,teacher recertification) or have declared themselves in the
category of undecided. The only other students who were excluded
from participation in the study were individuals who were within
15 semester hours of completing their degree program. These
students, by nature of their accumlated hours, were considered
persisters.
Data Collection
The survey questionnaire was distributed to the randomly
selected students, in their classes, on each of the three
campuses by their classroom instructors. This took place during
the eleventh week of the fifteen week term, three weeks after the
distribution of mid-term grades and one week after the last day
of official withdrawal from classes without penality. Any
student, from the original sample, withdrawing prior to the
distribution date was contacted, by mail or personally, in an
attempt to complete the survey questionnaire. Each participating
student received in class a survey questionnaire (see Appendix D)
and was asked to complete the form in class as accurately as
possible. The instructions provided to the monitors are found in
Appendix E. All forms were received and then analyzed by the
researcher.


REFERENCES
Aitken, N. D. (1982). College student performance, satisfaction,
and retention: Specification and estimation of a structural
model. Journal of Higher Education, 53, 32-50.
Armor, D. (1973-1974). Theta reliability and factor scaling. In
H. Costner (Ed.), Sociological methodology, 17-50. San
Francisco: Jossey-Bass.
Astin, A. (1964a). Personal and environmental factors associated
with college dropouts among high aptitude students.
Journal of Educational Psychology, 55 (4), 219-227.
Astin, A. (1964b). College dropouts: A national profile. ACE
Research Reports, 7_. Washington, DC: American Council on
Education.
Astin, A. (1973). The impact of dormitory living on students.
Educational Records, 54, 204-210.
t
Avakian, A.N., Mackinney, A.C., & Allen, G.R. (1982).
Race and sex differences in student retention at an urban
university. College And University, 57, 160-165.
Baker, R. W. (1980). Alienation and freshman transition into
college. Journal of College Student Personnel, 21 ,
437-432.
Baumgart, N., & Johnstone J. (1977). Attrition at an Australian
university: A case study. Journal of Higher Education. 48
(5), 553-570.
Bayer, A. (1968). The college dropout: Factors affecting senior
college completion. Sociology of Education, 41, 305-316.
Beal, P.E., & Noel L. (1979). What works in student retention.
A Preliminary Summary of a National Survey Conducted Jointly
by The American College Testing Program and the National
Center for Higher Education Management Systems. (Eric
Reproduction Service No. ED 180 348).
Bean, J. (1980). Dropout and turnover: The synthesis and test
of a causal model of student attrition. Research in
Higher Education, 12, 155-187.
142


LIST OF TABLES
TABLE
PAGE
10
Frequency and Percentage Distribution for
Demographic Variables 61
Pearson Product Moment Correlation for
Endogenous and Exogenous Variables
Total Campus 67
Pearson Product Moment Correlation for
Endogenous and Exogenous Variables
East Campus 70
Pearson Product Moment Correlation for
Endogenous and Exogenous Variables
North Campus 73
Pearson Product Moment Correlation for
Endogenous and Exogenous Variables
West Campus 76
2 2
R~, R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dtopout Decisions
With Social System Integration by Campus 80
2 2
R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Social System Integration by Campus 80
2 2
R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With Peer-Group Interaction by Campus 83
2 2
R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Actual Dropout Decisions
With Peer-Group Interaction by Campus 83
2 2
R R Increase and Computed F Ratios for the
Full Model and Partial Regression Coefficients
Relating Students' Perceptions of Dropout Decisions
With Faculty-Student Interaction by Campus 87
vii


12
Assumptions
The assumptions for this study were as follows:
1. The testing of some of the hypotheses relied on
self-reported data. Systematic error caused by method bias,
therefore, may have affected any relationships that have been
confirmed or questioned. However, there was evidence that
suggested that one's perception of social integration most
directly relates to college persistence (Pervin, Reik, &
Dalrymple, 1966; Rootman, 1972; Spady, 1971). This research was
relevant since the responses on the instrument used in this study
were based on the student's perception.
2. It was assumed the dropout rate for Associate of Arts
and Associate of Science degree seeking students would be
approximately 30 percent.
3. Decisions to remain in school or drop out are tentative
decisions and therefore conclusions derived from such data should
be considered in the same reference.
Delimitations
This study was confined to the student population of Pasco
Hernando Community College, a tri-campus college located in Dade
City, Brooksville, and New Port Richey, Florida.
Limitations
1. The ex post facto design of the study and the fact that
questionnaires were administered only once precluded advantages
inherent in experimental designs. The researcher was not able to


Table 4-continued
VARIABLES
8
9
10
11
12
13
1.
Age
.267
.014
-.034
-.019
.129
-.063
2.
Sex
.099
.045
.077
.089
-.023
.099
3.
Race
-.161
-.009
-.233
-.146
-.144
.098
4.
Accumulated Hours
-.101
-.160
-.106
-.184
-.007
-.224
5.
Human Relations Course
CO
o
1
-.384*
-.251
-.399*
-.198
-.044
6.
Background Characteristics
o
r-H
o
1
.060
.181
.135
-.023
.113
7.
Commitment
.251
00
CO

1
.069
-.055
-.062
-.173
8.
Academic Integration
.097
.482*
.341*
-.036
.061
9.
Peer-group Interaction
.385*
.836*
.207
.210
10.
Faculty-student Interaction
.817*
-.010
-.264
1 1 .
Social Integration
.134
-.012
12.
Dropout Perception
.324*
13. Dropout Actual
*£<05


90
Table 12
2 2
R, R Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students' Perceptions of
Dropout Decisions With The Interaction Effect of Peer-Group and
Faculty-Student Interaction by Campus
Dependent Variable: Students' Perceptions of Dropout Decisions
Campus
Total
East
North
West
*£<.05
R2 full F
.024 .587
.155 .981
.064 .365
.055 .644
R increase
.004
.004
.010
.005
F partial
.001
.137
.357
.327
Table 13
_ 2 2 .
_* v" r.:: : r r..
Partial Regression Coefficients Relating Students' Actual Dropout
Decisions With The Interaction Effect of
Peer-Group Interaction
and Faculty-Student Interaction by Campus
Dependent Variable: Students' Actual
Dropout Decisions
Campus
R2 full
F
2 .
R increase
F partial
Total
.064
1.875
.003
.522
East
.340
2.746*
.006
.298
North
.292
2.198
.049
2.232
West
.132
1.695
.001
. 107
*£<05


160
26. Surprisingly enough, some of the young people in Tulsa have
been meeting in storm sewers to play their guitars.
A. Tulsa have been meeting in storm sewers to play
B. Tulsa, who have been meeting in storm sewers, where
they play
C. Tulsa, have been meeting in storm sewers, there they
play
D. Tulsa, meeting in storm sewers and playing
27. The whale and the porpoise are an unusal mammal, for they
live in the sea.
A. an unusual mammal, for they live
B. unusual mammals, for they live
C. an unusual mammal, living
D. unusual mammals, which lives
28. Wanting a better job, it seemed to Joseph continuing his
education is the best way to do it.
A. Wanting a better job, it seemed to Joseph continuing his
education is the best way to do it.
B. Because he wanted a better job, Joseph thought the best
way to do it was to continue his education.
C. Joseph thought that the best was to get a better job was
to continue his education.
D. It seemed to Joseph, wanting a better job, that the best
way was to continue his education
29. In this book they saw that we may be unable to deal with the
rapid changes taking place in out style of living
A. In this book they say
B. This book tells us
C. It says in this book
D. They tell us in this book
30. Doctors finally traced the headaches that Emma had had for
many years to an allergy
A. Doctors finally traced the headaches that Emma had had
for many years to an allergy.
B. Doctors finally traced the headaches to an allergy, Emma
having had them for many years.
C. Finally Emma's headaches that she had had for many years
was traced to an allergy by doctors.
D. For many years Emma had had headaches, and doctors
finally traced it to an allergy.
GO ON TO THE NEXT PAGE


27
settings and in addition the students enrolled in these
institutions usually spent less time on campus (Chickering,
1974). From this research one could assume that the background
characteristics which the commuter student brings to college
might have a stronger direct impact on subsequent persistence
than the background characteristics of residential students.
Additional findings showed that academic integration had a
direct effect on persistence, a finding which was consistent with
several previous studies conducted in residential schools (Bean,
1980; Munro, 1981; Pascarella 6. Terenzini, 1983; Terenzini &
Pascarella, 1978). Social integration was found to have a
negative influence on persistence. This was inconsistent with
previous research in residential institutions (Pascarella &
Terenzini, 1983; Pascarella & Chapman, 1983) but supported the
findings of Terenzini, Pascarella, Theophilides, and Lorang
( 1983).
A possible explanation for this negative influence was
given by the authors based on findings by Pascarella and Chapman
(1983). They concluded that students with high levels of social
integration tend to have high affiliation needs. Because of
these needs, these students may be more sensitive to the limited
opportunities for social integration satisfaction than their less
socially integrated counterparts. This may increase the chance
of the socially integrated student transferring to a residential
school in order to fulfill these affiliation needs.


150
Yourglich, A. (1966). A four-phase study of value homophily
friendship, social participation and college dropouts
Sociological Analysis, 27, 19-26.


81
F-statistic of .837. This was also non-significant at the .05
level.
2
The full model for West Campus resulted in an R of .042
with an F-statistic of .748, which was non-significant at the
.05 level. The partial regression coefficient also was
2
non-significant at the .05 level with an R increase of .006 and
an F-statistic of .448.
Table 7 contains the other half of the results to
Hypothesis 1 with students' actual dropout decisions as the
2
dependent variable. The test of the full model yielded an R of
.055 with an F-statistic of 2.152, which was not significant at
2
the .05 level. Without social system in the model, the R was
2
.051, which resulted in an R increase of .004. This increase
in variation resulted in a computed F-statistic of .686, which
did not exceed the critical F-statistic at the .05 level.
Therefore the conclusion was fail to reject at the .05 level for
Hypothesis 1.
2
The full model for East Campus had an R of .258 with an
F-statistic of 2.962, which was significant at the .05 level.
2
The R for the partial regression coefficient for East Campus
2
was .200, which resulted in an R increase of .058 and produced
a computed F-statistic of 2.651. This did not exceed the
critical F-statistic at the .05 level and the decision was not
to reject Hypothesis 1. Social system integration did not
improve prediction of dropping out. The full model for North


116
Of the 32 hypotheses analyzed for Hypotheses 1-4, each
hypotheses being tested in reference to the four different
groups using two different dependent variables, only four were
found to be significant at the .05 level. All four significant
hypotheses involved East and North campuses and were in
reference to the actual drop out rate as the dependent
variable. Of the remaining 60 hypotheses, Hypotheses 5-19, each
being tested in reference to four different groups, only six
were found to be significant at the .05 level. Three of the six
involved East Campus students, one involved North Campus
students, and two involved West Campus students.
Considering all variables of interest, the similarities
between campuses were greater than the differences. The one
major exception was faculty-student interaction. Tinto' s
conceptual framework seemed to be supported, with reference to
the faculty-student interaction variable on the East Campus and
peer-group interaction variable on the North. This was not the
case on the West Campus and all campuses combined.


42
Development of the Student Survey
The student survey utilized in this study was formulated
from the combined information received from the following
research:
A Multiinstitutional, Path, Analytic Validation of Tinto's
Model of College Withdrawal by E.T. Pascarella and D.W. Chapman
(1983);
A Test and Reconceptualization of a Theoretical Model of
College Withdrawal in a Commuter Institution Setting by E.T.
Pascarella, P.B. Duby, and B.K. Iverson (1983);
Predicting Voluntary Freshman Year Persistenece/Withdrawal
Behavior in a Residential University: A Path Analytic Validation
of Tinto's Model by E.T. Pascarella and P.T. Terenzini (1983);
and Path Analytic Validation of Tinto's Theory of College
Student Atrition by P.T Terenzini, E.T. Pascarella, C.
Theophilides, and W. G. Lorang (1983).
Variables
As presented in Figure 1, Tinto's model consists of five
major constructs or variable sets in a causal sequence: (a)
background characteristics (family background, individual
attributes, and pre-college schooling); (b) initial commitments
(goal commitment and institutional commitment); (c) integration
(academic system and social system); (d) subsequent goal and
institutional commitments; and (e) withdrawal decisions.
Five constructs, background characteristics, initial
commitments, academic system, social system, and withdrawal
decisions, were operationalized as follows. In addition the
measurements of the variables under consideration were selected
using the following criteria.


51
questionnaire proved to be an adequate and serviceable instrument
in investigating variables of interest.
The same two criteria for selection that were used in the
present study applied to the pilot study with the exception of
number of hours completed. In the pilot study students were
eliminated, as possible subjects, if they were within nine hours
of graduation, indicating a persister. These students from the
pilot study could graduate at the end the 1984 Summer term by
taking an acceptable load. Therefore, students were eliminated
from participating in the pilot study if they had accumlated more
than 50 semester hours.
Present Study
Sub jects
The study sample consisted of a total of 200 students at
Pasco-Hernando Community College who were enrolled for the Fall
term of 1984. A total of 152 useable questionnaires were
received for a 76 percent response rate. Since the West Campus of
PHCC was approximately twice the size of either the East or North
campuses of PHCC, which were approximately equal in size, 100
students were sampled from this campus and 50 from each of the
remaining two campuses. A random selection process was used to
select subjects from all students who had declared an Associate
in Arts degree and/or Associate of Science degree on their
Program Declaration Form (Appendix A). This limitation (a)
assured relatively equal degree of commitment to the college on
the part of the students and (b) attempted to eliminate


CHAPTER TWO
REVIEW OF THE LITERATURE AND RELATED RESEARCH
Postsecondary institutions are facing a serious situation
that has a number of important implications for institutions as
well as students. Considering the economic times and the
evolving demographics of student populations, there has been an
increased interest in research studies concerning student
retention. Until recently little attention has been directed to
the underlying dynamics of the phenomenon of student withdrawal,
rather the main emphasis has been atheoretical and descriptive.
A number of theoretical papers (e.g., Bean, 1981; Spady,
1970; Tinto, 1975) have developed conceptual models. These
studies have made an important contribution to our understanding
of dropout behavior in postsecondary institutions. These models
provide both a comprehensive and an explanatory view of attrition
which provides direction to researchers confronted with the
problem of student dropout.
Tinto's (1975) schema has generated perhaps the most
extensive body of research. Using the work of Spady (1970),
Tinto has developed a longitudinal model which attempts to
explain the persistence/withdrawal process in postsecondary
education. This process is largely based on the degree of
personal fit between the institutional environment and the
20


Table 19
Means, S.D., and Computed t-Statistic Comparing Male and
Female Students on the Faculty-Student Interaction Variable
CAMPUS
HYP.
NO.
MALE STUDENTS
MEAN
S.D.
1
z
O 1

1
FEMALE STUDENTS
MEAN
S.D.
df
t
Total
10
50
9.883
.671
102
10.056
.835
150
-1.372
East
10
1 1
9.912
.743
28
10.501
.948
37
-2.056*
North
10
14
9.890
.566
25
9.994
.704
37
-.499
West
10
25
9.867
.718
49
9.833
.738
72
.189
*£<.05
102


75
West Campus
West Campus had the highest number of statistically
significant correlations of the three campuses with 15, out of
78, being significant at the .05 level (see Table 5).
The only statistically significant correlation related to
the dependent variable was background characteristics. The
higher the student's level of background characteristics the
more likely a student was to persist (r=.288). The remaining 14
correlations are presented according to the frequency a
particular variable achieved statistical significance. Levels
of academic integration correlated positively with levels of
background characteristics (r=.233), age (r=.339), degree of
student commitment (r=.285), peer-group interaction (r=.325),
faculty-student interaction (r=.549), and social integration
(r=.545). Peer-group interaction correlated positively with
levels of student commitment (r=.237), faculty-student
interaction (r=.254), and social integration (r=.809). Social
integration was correlated positively with levels of commitment
(r=.287) and faculty-student interaction (r=.772). Number of
accumulated hours correlated positively with levels of
background characteristics (r=.270) and students who took a
human relations type course tended generally to have more
accumulated credit hours (r=.357). Female students had a higher
level of commitment than male students (r=.275).


98
Hypothesis 8. There is no significant difference between
male and female student measurements on the social system
variable.
Table 17 shows the data summary of Hypothesis 8. The
computed t-statistic for the total campus was .353 with males
having a mean of 10.102 and females 10.028. East Campus males
had a mean of 10.417 and females 10.275, which resulted in a
t-statistic of .164. North Campus males had a mean of 9.974 and
females 10.078, which resulted in a t-statistic of -.562. West
Campus males had a mean of 10.035 and females 9.862, which
resulted in a t-statistic of 1.067. In each case the computed
t-statistic did not exceed the critical t-statistic at the .05
level. It should be noted that for East Campus the sample size
and the within group variances were unequal but not
proportional. Under this condition the independent sample
t-test tends to be liberal. Even under these liberal conditions
the t-statistic for East Campus did not met the criterion for
significance. In each of the four population groups the
conclusion was to fail to reject Hypothesis 8. There was no
difference between male and female students' scores on the
social system variable.
Hypothesis 9. There is no significant difference between
male and female student measurements on the peer-group
interaction variable.
The results of Hypothesis 9 are presented in Table 18.
The computed t-statistic for the total campus was .035, with a


READING
Directions: Each passage in this test is followed by quest ions
based on its content. After reading a passage, choose the best
answer to each question and put an X in the corresponding blank
on the answer sheet. Answer all questions following a passage on
the basis of what is stated or implied in that passage.
(The passages have been adapted from published material to
provide the students with significant problems for analysis and
evaluation. The ideas contained in the passages are those of the
original author and do not necessarly represent the opinions of
the College Entrance Examination Board or Educational Testing
Services. )
You will have 25 minutes to work on the 35 questions in the
test.
DO NOT TURN THIS PAGE UNTIL YOU ARE TOLD TO DO SO (OR, IF SELF-
ADMINISTERED, UNTIL YOU HAVE BEGUN TO TIME YOURSELF)
164


Table 22
Means, S.D., and Computed t-Statistic Comparing Students Who Have Had a Human Relations
Type Course With Students Who Have Not on the Faculty-Student Interaction Variable
CAMPUS
HYP.
HUMAN
NO.
RELATIONS
MEAN
COURSE
S.D.
NO HUMAN
NO.
RELATIONS
MEAN
COURSE
S.D.
df
t
Total
13
59
10.089
.893
93
9.942
.710
150
1.070
East
13
15
10.534
1.274
24
10.211
.621
37
.917
North
13
17
9.773
.559
22
10.099
.694
37
-1.624
West
13
27
10.042
.729
47
9.731
.708
72
1.781
*£<05
108


22
research-oriented universities, with undergraduate enrollments of
approximately 11,000. The first institution (Pascarella &
Terenzini, 1983) was an independent residential, private
institution and the other was a public residential institution.
Pascarella, Duby, and Iverson (1983) partially verified
Tinto's model using a sample of 269 students from an urban,
commuter university setting, rather than a residential setting.
They suggested that when applied to a commuter institution sample
not all dimensions of Tinto's model functioned according to
expectations.
The validity of Tinto's model appears to be generally
accepted, particularily in reference to residential settings. In
addition, individual variables in Tinto's model appear to have
predictive and explanatory power concerning dropout decisions.
Despite this growing body of research on persistence/withdrawal
behavior in colleges and universities, there lacks sufficient
interest in two-year, community college commuter institutions.
Thus a major purpose of this study was to assess the relationship
between social integration variables and community college
student retention using Tinto's (1975) conceptual framework.
Review of the Literature
Research in the past has generally come to the same
conclusions concerning the particular characteristics of students
who dropout from college. Dropouts generally (1) lack direction
(Summerski11, 1962) and plans for the future (Pancos & Astin


139
dropout process should be flexible enough to adjust to the needs
and characteristics of individual institutions. There should not
necessarily be an extensive effort to adopt a retention model
that will necessitate institutions to adjust their natural
academic and social systems to accomodate any particular model or
exclude portions of their organizational processes in need of
attention.
Recommendations for Further Research
As a result of this study several recommendations for
future research are in order. These recommendations involve four
main areas, individual variables involved in the dropout process,
models developed concerning the dropout process, improvement in
methodology techniques, and application of these models to
retention programs.
The variables involved in the dropout process appeared to
be well defined and labeled. Most researchers agree on the
variables related to students who drop out and there seems to be
some concensus on how to measure these variables. One
recommendation of this study is that further attempts should be
made to better define and/or measure these variables to better
characterizes individual differences. Presently, research is
able to describe the typical dropout but lacks the ability to
isolate characteristics that may be unique to particular
individuals. These individual differences may be so great that
the task suggested is beyond the means available to researchers
today.


120
level for the East Campus only, resulting in a decision to reject
the hypothesis on this campus.
Hypothesis 5. There is no significant difference between
white and non-white student population measurements on the
social system variable.
East Campus white students scored higher on the social
integration variable than did the non-white students.
Hypothesis 9. There is no significant difference between
male and female student measurements on the peer-group
interaction variable.
Female students scored higher than male students on the
peer-group interaction variable.
Hypothesis 10. There is no significant difference between
male and female measurements on the facu 11y-student
interaction variable.
Female students scored higher than male students on the
faculty-student interaction variable.
The following hypothesis was found to be significant at the
.05 level for both the North and West campuses, resulting in a
decision to reject the hypothesis on these campuses.
Hypothesis 11. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the social
system variable.


129
Table 27-continued
HYPOTHESES CORRELATION DECISION
Total
-
.093
Fail
to
Reject
East
-
.162
Fail
to
Reject
North
-
.184
Fail
to
Reject
West
.030
Fail
to
Reject
Total

.038
Fail
to
Reject
East
-
.083
Fail
to
Reject
North
-
.106
Fail
to
Reject
West
.012
Fail
to
Reject
Total
.004
Fail
to
Reject
East
.054
Fail
to
Reject
North
-
. 106
Fail
to
Reject
West
.062
Fail
to
Reject
Total
_
.048
Fail
to
Reject
East
-
.058
Fail
to
Reject
North
-
.019
Fail
to
Reject
West
.014
Fail
to
Reject
Total
.008
Fail
to
Reject
East
-
.149
Fail
to
Reject
North
-
.014
Fail
to
Reject
West
.034
Fail
to
Reject
Total
-
.047
Fail
to
Reject
East
.079
Fail
to
Reject
North
-
.034
Fail
to
Reject
West
-
.022
Fail
to
Reject
*£<05


PASCO-HERNANDO COMMUNITY COLLEGE
PROGRAM DECLARATION.
NAME : DATE :
1. I have applied for adm i ssion/have been admitted to
Pasco-Hernando Communtiy College and wish to pursue the
following degree/certificate program (circle one).
a. Associate in Arts Degree
b. Associate in Science Degree
c. Associate in Science Certificate
d. Undecided
e. Other Personal Objectives
f. Vocational Certificate
2. The basis on which I am requesting to be accepted to the
Program I have selected above is (circle all that apply).
a. High school graduate
b. Received Certificate of Attendance from Florida high
school.
c. Completed GED test
d. Transferred from other college or university
e. Early Admission/Credit Bank
f. Over 19 years of age, but not 2a, 2b, or 2c above.
3. The Federal and State goveronments require the college to
collect the following information.
I
have a physical handicap
yes
no
I
have a mental handicap
yes
no
I
speak English well
yes
no
I
read English well
yes
no
I understand that my enrollment in the indicated Program is
tentative until all required documents are received by the
Records Office, and that my Program will be changed to
"Undecided" should these documents not be received by the end of
my first semester. I understand further that my program status
will be printed on fee invoice and semester grade report, and
that to change this Program I must submit a Change of Program
Form.
STUDENT'S SIGNATURE: DATE:
COUNSELORS SIGNATURE: DATE:
152


Dear Monitor,
First I would like to thank you very much for your time and
cooperation in this matter. Without this effort my task would be
very difficult.
Please had out the questionnaires to the students whose
names appear on the front during the week of November 26, 1984.
Read the following instructions:
"Please read the cover letter of the survey. Carefully read
all instructions and be sure to complete all items. Make sure
your social security number is correct and filled in on the
questionnaire. This questionnaire and your response is no way
connected with this particular course. Your assistance is
appreciated in helping us keep students in school."
Allow approximately 15 minutes for completion. There is no
time limit but it should take only 5 to 10 minutes to complete.
Collect all forms as completed and check to make sure the
Social Security number is listed. All surveys completed and
non-completed should be returned to Michael G. Rom by 12/3/84 if
possible. If a student can not be contacted until later please
hold until 12/7/84 at the latest.
Thank you VERY MUCH and if there are any questions please contact
me on the East Campus ext. // 24.
Sincerely,
Michael G. Rom


130
Other results from the East Campus indicated that white
students scored significantly higher (t=2.-134) on the measurement
of the social system variable than non-white students (Hypothesis
5). Female students scored significantly higher (t=-2.437) on
the measurement of the peer-group interaction variable than males
(Hypothesis 9). And females scored significantly higher
(t=-2.056) on the measurement of the faculty-student variable
than males (Hypothesis 10). The white student population
comprises 87.2 percent of the East Campus population. Even
though the non-white population was 12.8 percent, in reality
there were only five non-white subjects. This small number may
not be representative of the total population of non-white
students, therefore partially explaining the difference. The
difference may also be very real in the respect that non-white
students, being a minority, either do not make the effort, lack
the social skills, or are not given adequate opportunities to
socially integrate into the college environment.
Females on the East Campus ultimately felt more positive
interaction with their peers than males. This could partially be
due to the more than two to one ratio of female students to male
students on the East Campus. East Campus had the highest percent
of female students, of the three campuses, with an actual 65
percent of the students being female. Females may be given more
opportunities to interact with their peers because of the make-up
of the East Campus's social and extracurricular activities. It
is also possible that females may possess more adequate social


Background
Characteristics
Commitments
Academic System
Commitments
Family = Goal
Background =>= Commitment
= Grade
Performance
= Intellectual1
->= Development
= Academic
= Integration
.>.
1 >o
= Goal
= Commitment
Individual
Attributes
> =
-> =
->
>= Dropout
>= Decisions
Pre-
College
Schooling
= Institu-
-> = tional
= Commitment
->= Peer-group =
= Interactions
= Institu-
= tional
= Commitment
Faculty = =
Interactions =
=> =
Social
Integration
Social System
Figure 1. Tinto's Conceptual Schema For Dropout From College (printed with permission Short, 1979)


8
commitments, in turn, are seen, along with levels of integration,
as having a positive influence on persistence.
As suggested by Tinto's model, the student's social system
is an important part of the process that leads toward an
individual's decision to persist or dropout of college.
According to research, peer-group interaction and faculty-student
interaction have a unique contribution to student social systems
and student retention, but this may not apply across all
institutional types. Additional research needs to concentrate on
the influence of social system variables, such as peer-group and
faculty-student interaction, on college student dropout in both
residential and commuter institutions.
In order to determine the influence of social system
variables on the dropout decision, all other preceding and
related variables such as family background, individual
attributes, pre-college schooling, commitments, and academic
system need to be held constant. If this is not done, then one
cannot assume that social system variables alone contribute to
the student's decision to either leave school or remain.
This dissertation controlled for those variables in Tinto's
model, background characteristics, commitments and academic
system, while investigating the relationship between social
system variables and college student retention in a two-year
commuter community college.


Table 2
Pearson Product Moment Correlation for Endogenous and Exogenous VariablesTotal Campus
VARIABLES
1
2
3
4
5
6
1.
Age
.156
-.104
H
O

.026
-.142
2.
Sex
-.040
-.061
.691*
.007
3.
Race
.036
.115
-.153
4.
Accumulated Hours
.384*
. 194*
5.
Human Relations Course
-.127
6.
Background Characteristics
7.
Commitment
8.
Academic Integration
9.
Peer-group Interaction
10.
Faculty-student Interaction
11.
Social Integration
12.
Dropout Perception
13.
Dropout Actual
(continued)
*£<.05


84
group interaction in the model, it was .026. The peer-group
interaction variable therefore explained an additional .9
percent of the variation in dropout rate. This increase in
variation resulted in a computed F-statistic of 1.420, which did
not exceed the critical F-statistic at the .05 level. The
conclusion was to fail to reject Hypothesis 2. Peer-group
interaction did not improve prediction of dropping out.
The full models for East, North, and West campuses
2
resulted in R 's of .158, .054, and .050, with F-statistics of
1.181, .374, and .715. All three were non-significant at the
2
.05 level. The R increase and computed F-statistic for the
partial regression coefficients for East Campus were .016 and
.623, for North Campus .049 and 1.551, and for West Campus .015
and 1.037. In each of the three campuses the computed
F-statistic did not exceed the critical F-statistic at the .05
level. All three campuses resulted in a failure to reject
decision for Hypothesis 2.
With actual drop out as the dependent variable (Table 9),
, 2
the full model for total campus yielded an R of .060 with a
F-statistic of 1.875 This was not significant at the .05
level. The partial regression coefficient variable for total
2
campus had an R increase of .009. With a computed F-statistic
of 1.333, the decision was to fail to reject Hypothesis 2, since
the critical F-statistic was not exceeded at the .05 level.
East Campus full model was significant at the .05 level with an


TABLES-continued
TABLES PAGE
21 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who
Have Not on the Peer-Group Interaction Variable 106
22 Means, S.D., and Computed t-Statistic
Comparing Students Who Have Had a Human
Relations Type Course With Students Who Have
Not on the Faculty-Student Interaction Variable 108
23 Correlation Coefficients for Accumulated
Semester Hours and Social System, Peer-Group
Interaction, and Faculty-Student Interaction
Variables by Campus 109
24 Correlation Coefficients for Age and Social
System, Peer-Group Interaction, and Faculty-
Student Interaction Variables by Campus Ill
25 ANOVA Between East, North, and West
Campuses on Variables of Interest 114
26 BONFERRONI Statistics: Faculty-student
Interaction on Student Survey Questionnaire 115
27 Results of the Hypotheses 127
ix


35
Goal commitment. There seems to be little doubt that lack
of goals in life decreases our motivational drive; thus college
persistence depends on degree of career goals (Day, 1982;
Churchill & Iwai, 1981; Jacobs, Bringman & Friedman, 1982).
Previous research supports this statement: Slocum (1956)
emphasized the need for occupational plans; Summerskill (1962)
reported students need direction; Astin (1964b) implied" What to
study?" was the important question for college students; Wessell,
Engle, and Smidchens (1978) cited the need for a clear purpose
concerning educational persistence; Beck (1980) reported that an
important factor related to college dropout is inadequate
clarification; and Simpson, Baker, and Mellinger (1980)
demonstrated that voluntary withdrawals had less commitment than
persisters. Research reports that if students have some degree
of direction they are more likely to persist in college.
Grade performance. Researchers reported that grade
performance is an important variable in students' college success
(Avakian, MacKinney, & Allen, 1982; Bean, 1982; Edwards & Waters,
1983). Spady (1970) reported that grades are the single most
important factor related to persistence in college. Tinto's
(1975) synthesized research also confirmed the importance of
grade performance. There is little doubt that grades indicate to
what degree students are academically integrated into the college
environment (Creamer, 1980).


128
Table 27-continued
Hypotheses
t-statistic
Decision
8.
Total
.353
Fail to Reject
East
.164
Fail to Reject
North
- .562
Fail to Reject
West
1.067
Fail to Reject
9.
Total
.035
Fail to Reject
East
-2.437*
Reject
North
- .280
Fail to Reject
West
1.312
Fail to Reject
10.
Total
-1.372
Fail to Reject
East
-2.056*
Reject
North
- .499
Fail to Reject
West
. 189
Fail to Reject
11.
Total
.098
Fail to Reject
East
- .052
Fail to Reject
North
-2.670*
Reject
West
2.000*
Reject
12.
Total
.419
Fail to Reject
East
1.108
Fail to Reject
North
-2.628*
Reject
West
1.215
Fail to Reject
13.
Total
1.070
Fail to Reject
East
.917
Fail to Reject
North
-1.624
Fail to Reject
West
1.781
Fail to Reject
(continued)
*£<05


169
The use of coal and oil by electric power companies creates
some very serious environmental problems. One of these problems
is nitrogen oxide. When you burn the oxygen out of the air, you
are left with nitrogen. Nitrogen, when exposed to air at high
temperatures, forms nitrogen oxide. It comes out of the
powerplant stack, gets mixed with moisture in the- air to make
various acids, and these get inhaled.
When coal and oil are burned, they give off impurities that
contribute to air pollution. They all have a certain percentage
of sulfur. Surfur oxides come out of the stacks and form acids,
which are irritants to the mucous membrane, and thus a public
problem. Another pollutant is mercury. Combustion of coal and
oil is responsible for about one-third of the mercury that gets
into environment annually.
To get clean air, we invest money in a stack chemical
process plant to clean the waste gases that result from
combustion of coal and oil. Such plants are now being
experimented with, but utility companies are reluctant to install
expensive stack cleanup systems that they are not sure will work.
Solutions will be developed to handle the problem. They will be
expensive, and their use might raise the cost of power to the
public ten to twenty percent.
18. According to the passage, why may the cost of power go up?
A. Stopping pollution will be expensive
B. Companies will need to make a large profit
C. We will use more power
D. The price of coal and oil will rise
19. What does nitrogen need to form nitrogen oxide?
A. Moisture
B. Air and great heat
C. Air free of oxygen
D. The great heat caused by acids
20. What does the passage say coal and oil are used for?
A. To get rid of waste gases
B. To manufacture chemicals
C. To purify the air
D. To create electric power
21. That which is an irritant to mucous membrane would likely?
A. cause watery eyes
B. make plants grow
C. make nitrogen a poison
D. remove paint from buildings
GO ON TO THE NEXT PAGE


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 ASSESSMENT OF THE RELATIONSHIP
BETWEEN SOCIAL INTEGRATION VARIABLES AND COMMUNITY
COLLEGE STUDENT RETENTION
By
MICHAEL G. ROM
August 1985
Chairman: Albert B. Smith III
Major Department: Instruction and Curriculum
Using Tinto1s conceptual framework model, the purpose of
this study was to determine what relationships existed between
social system integration variables (peer-group and
faculty-student interaction) and student dropout decisions in a
two-year community college. Two hundred students, at Pasco
Hernando Community College, were surveyed during the Fall term of
1984, using a Student Survey Questionnaire. One hundred
fifty-two usable responses were received for a 76 percent return
rate. The instrument measured the student's background
characteristics, commitment (goal and institutional), academic
integration, social integration (peer-group and faculty-student
xi


5
integration on persistence in a commuter school. This negative
effect was also reported in a residential school by Terenzini,
Pascarella, Theophi1ides, and Lorang (1983).
Even though social integration variables have been shown to
affect dropout decisions in particular institutions, the
application of Tinto1s model across all institutional types is
still problematic. Further research is needed to verify the
influence of social integration variables, specifically
peer-group and faculty-student interaction, on college student
persistence as it relates to different types of postsecondary
institutional settings.
Tinto's Model
In the theoretical model of dropout decisions in college
diagrammed in Figure 1, Tinto suggests
the process of dropout from college can be viewed as a
longitudinal process of interactions between the
individual and the academic and social systems of the
college during which a person's experiences in those
systems (as measured by his normative and structural
integration) continually modify his goal and
institutional commitments in ways which lead to
persistence and/or to varying forms of dropout, (p.
94)
Individuals enter instituti
background characteristics, pre-co
individual attributes, and family
a possible direct and/or indirect
ons of higher education with
liege experiences, a variety of
backgrounds, each of which has
impact upon their performance
in college. In addition, these background characteristics and
individual attributes also influence the development of the


9
Statement of the Problem
A problem facing community colleges today is high student
attrition or drop out rates. There is a need to investigate what
variables relate to community college student attrition in order
to better understand and prevent the dropout process.
Using Tinto's (1975) conceptual framework, the purpose of
this study was to determine what relationships exist between
social system integration variables (peer-group interaction and
faculty-student interaction) and students dropout decisions in a
two-year community college. The researcher hoped that the
results of this study would then be used by community colleges to
develop new programs designed to reduce student attrition and
subsequently enhance support for these colleges.
Hypotheses
The following null hypotheses were tested (alpha level .05):
Hypothesis 1. A significant proportion of the variation in
student dropout rates is not explained by selected social
system variables after controlling for student background
characteristics, student commitments, and the student
academic system (student grade performance and student
intellectual development).
Hypothesis 2. A significant proportion of the variation in
student dropout rates is not explained by peer-group
interaction after controlling for student background
characteristics, student commitments, the academic system,
and faculty-student interaction.


69
credit hours a student accumulated, the higher were the scores on
the three measurements that comprised background characteristics
(r=.194) and the more likely the students were to have had a
human relations type course (r=.384). The following
relationships were found to have a positive correlation with
academic integration: commitment (r=.296), peer-group interaction
(r=.208), faculty-student interaction (r=.415), and social
integration (r=.200). Peer-group interaction also had a positive
correlation with faculty-student interaction (r=.318) and social
integration (r=.575). Finally, faculty-student interaction was
positively correlated with social integration (r=.612).
East Campus
Among the 78 correlations related to the East Campus, only
eight were significant at the .05 level (see Table 3). The two
statistically significant correlations relating to the dependent
variable are presented first. The higher the academic
integration the more likely the students were to actually stay in
school (r=.446). Second, females perceived themselves as
returning to school more often than males (r=.486). The
remaining six statistically significant correlations are
presented in the order in which they appear in Table 3. Female
students scored higher on the peer-group interaction scale
(r=.357) than male students. The more credit hours accumulated
by a student indicated a greater likelihood of a student taking a
human relations type course (r=.476). The more a student
indicated a commitment to goals and institution,


AN ASSESSMENT OF THE RELATIONSHIP BETWEEN SOCIAL INTEGRATION
VARIABLES AND COMMUNITY COLLEGE STUDENT RETENTION
BY
MICHAEL G. ROM
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


31
32.
33.
34.
35.
36.
37.
38.
It is difficult for me to meet and
make friends with other students SA A NS D
Few of the PHCC students I know would
be willing to listen to me and help me
if I had a personal problem SA A NS D
Most students at PHCC have values
and attitudes which are different
from my own SA A NS D
I am satisfied with the opportunities
at PHCC to meet and interact informally
with faculty members SA A NS D
Few of the PHCC faculty members I
have had contact with are willing to
spend time outside of class to discuss
issues of interest and importance to
students SA A NS D
Since coming to PHCC I have developed
a close,personal relationship with at
least one faculty member SA A NS D
My non-classroom interactions with PHCC
faculty have had a positive influence on
my personal growth,values, and attitudes...SA A NS D
Most of the PHCC faculty members I have
had contact with are interested in help
ing students grow in more than just aca
demic areas SA A NS D
SD
SD
SD
SD
SD
SD
SD
SD
Directions: Please record the accurate number in the space
provided.
39. Students have a variety of contact with faculty members. In
the blank to the right, please estimate the number of times
this semester you have met with a faculty member outside the
classroom for each of the following reasons. Record only
the number of those conversations that lasted 10 minutes or
more.
1. To help resolve a disturbing personal problem _
2. To discuss a campus issue or problem _
3. To socialize informally __
PLEASE CONTINUE TO THE NEXT PAGE


109
Table 23
Correlation Coefficients for Accumulated Semester Hours and
Social System, Peer
-Group Interaction,
and Faculty-
Student
Interaction Variables
by Campus
TOTAL EAST
NORTH
WEST
HYPOTHESIS 14
accumulated
semester hours
and social system
-.093 -.162
00

1
.030
HYPOTHESIS 15
accumulated
semester hours
and peer-group
interaction
-.038 -.083
-.106
.012
HYPOTHESIS 16
accumulated
semester hours
and faculty-student
.004 .054
vO
O

1
.062
interaction
*£<05


167
Adolescence is a unique period of transition, a period from
childhood to adulthood. As part of the transition comes a shift
in orientation, away from the preceeding generation, toward one's
own (5) generation. This transition has been taking place since
early childhood; even a young child often responds more to the
pressures of his fellows than to the desires of his parents. But
adolescence is a period in which parental control is in its (10)
waning days, a period in which a few teenagers have already
broken away from parental control for good.
9.The author sees adolescence primarily as
A. the most important time in life
B. a time to train to become a parent
C. a time of change
D. a time of hopefulness
10.If one shifts "orientation"
his
A. fears
B. focus
C. dreams
D. control
(line 3), he most likely changes
11.In line 10, "waning" most nearly means
A. winning
B. fading
C. useful
D. bad
12.
The author suggests that which of the following is true of
the relationship between parents and children?
A. Most parents fail to control their children.
B. Children work hard to control their parents.
C. The child's natural desire for independence often hurts
his parents.
D. Children become independent of their parents gradually.
(This passage was written in 1966)
In contrasting the protest techniques of Blacks and Mexicans
Americans, it must be remembered that the Black's drive for civil
rights is based at least partially on a mass movement with mass
(5) organization and highly vocal leadership. Mexican-American
GO ON TO THE NEXT PAGE


131
interaction skills that allow them to interact more successfully.
Females also expressed a higher degreee of faculty-student
interaction than males. Part of the explanation, for this last
finding, might be due to the fact that females perceived
themselves as persisting in school more than males. This
relationship might reinforce interaction with faculty members.
It is possible that the same social interaction skills that may
promote a higher degree of interaction with peers may also be
advantageous to social interaction with faculty. Similar
findings have been reported by Spady (1965), where a higher
degree of social integration was found for females (20 percent)
as compared to males (12 percent).
Results from the North Campus, with actual dropout rate as
the dependent variable, indicated a significant proportion
(10.9%) of the variation in dropout rate was explained by
peer-group interaction (Hypothesis 2) and a significant
proportion (16.7%) of the variation in dropout rate was explained
by faculty-student interaction (Hypothesis 3). Students who
remain in school scored higher on the peer-group interaction
variable and lower on the faculty-student interaction variable
than students who withdrew from school.
Students remaining in school with higher peer-group
interaction scores follows Tinto's theory that the higher the
peer-group interaction the more likely a student will remain in
school. It is somewhat difficult to explain the discrepancy
between peer-group interaction having a positive influence and


ACKNOWLEDGEMENTS
I would like to acknowledge several individuals for their
continual support. Without these people I might not have
completed this task.
My committee consisted of Dr. A1 Smith, Dr. Steve Olenjik,
Dr. Gordon Lawrence, and Dr. Paul Fitzgerald. I would like to
thank Steve for his patience which helped me through the final
stage of my data analysis. I would like to especially thank Al
who at times had to show me the way, at times hold me back, and
several times had to come find me because I was lost. To each of
these men I am deeply grateful.
I would like to thank all the professors, secretaries,
clerks, and students who were a part of my study and experiences
at the University of Florida. I would also like to express my
deepest appreciation to all of my friends who have given me
support and love on a daily basis. It's the contribution of the
many parts, however small, that make up the total affect of any
experience. For the part each of you played in mine I thank you.
The individuals who contributed to this study by editing,
typing, reading, or adding words of encouragement are too
numerous to list. I would like to acknowledge some special
individuals who made my task easier: David Rom, Jean Rom,
Charles and Catherine Hudson, Bill Reynolds, Larry Eason, Jane
iii


172
29. Which of the following questions does the passage answer?
A. Who knows what the best method of. teaching is?
B. What have we forbidden students to learn?
C. Do teachers always know more than their students?
D. Why is learning necesary?
30. The
A.
B.
C.
D.
source of power in school has been
physical strength
wealth
new trends
information
Black Americans love their country enough to critize her
fundamentally. Many white Americans simply cannot be bothered.
Ironically enough, in the middle of the twentieth centry, (5) the
black man is the new white hope. To live castrated in a great
white harem and yet somehow maintain his black manhood and his
humanity-this is the essence of the new man created out of the
black invention. History may render the verdict (10) that htis
was the greatest legacy handed to the New World by the West.
Western man wrote his history as if it were the history of
the entire human race. I hope that colored men all over the
world have watched (15) Western man too long to commit the fatal
folly of writing history with a colored pencil. For there is
great wisdom in the old Ghana proverb: "No one rules forever on
the throne of time."
We black folk have learned many lessons during (20) our
sojourn in this place. One of them is the truth of another Ghana
proverb: "Only a fool points to his heritage with his lefthand."
We are becomimg prouder and prouder of our heritage in America
and Africa. And we know the profound (25) difference between
pride and arrogance. Yes, we black people stand ready, eager,
willing, and able to make our contribution to the culture of the
world. Our dialoque will not be protest but affirmation of the
human dignity of all people everywhere
31. The author most strongly suggests that criticism can be
proof of
A. love
B. pride
C. eagerness
D. arrogance
GO ON TO THE NEXT PAGE


45
Pre-college schooling. The two most popular measurements of
pre-college schooling in the research were (a) students'
percentile rank in high school, item 6, and (b) indication of
high school grade point average or grade achievement, item 5.
Other variables, such as high school preparation (Terenzini &
Pascarella, 1983) and extracurricular activities in high school
(Pascarella & Terenzini, 1983), were used in previous research,
but their isolated usage eliminated them from consideration in
this research.
Percentile rank in high school used a seven ordinal category
assigning a value of 1 to "70% or below" through a value of 7 for
"top 10%," and the grade point average in high school used a
seven point scale assigning a value of 1 to "D or below" through
a value of 7 for "A/A+." Each score was converted into Z-scores,
adding a constant of 10, summed, then divided by 2.
Initial commitments
The commitment value was the sum of the Z-score of goal
commitment, plus ten, and institutional commitment, plus ten,
divided by 2.
Goal Commitment. Highest degree expected, item 9, and
importance of graduating from college, item 11, were consistently
used as measurements of goal commitment. A value of 1 was
assigned to "Associate of Arts/Science" through a value of 6 for
"LL.B. or J.D. (law)." In reference to importance of graduating,
a value of 4 was assigned to "extremely important"


80
Table 6
2 2
R~, R~ Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficents Relatina Students' Perceptions of
Dropout Decisions With Social System Integration by Campus
Dependent
Variable:
Students'
Perceptions
of Dropout Decisions
Campus
R2 full
F R2
increase
F partial
Total
.022
.835
.001
.192
East
. 185
1.933
.062
2.569
North
.029
.253
.024
.837
West
.042
.748
.006
.448
* 2<*05
Table 7
2 2
R, R~ Increase and Computed F Ratios for the Full Model and
Partial Regression Coefficients Relating Students1 Actual Dropout
Decisions With Social System Integration by Campus
Dependent Variable: Students' Actual Dropout Decisions
2 2
Campus R full F R increase F partial
Total
.055
2.152
.004
.686
East
.258
2.962*
.058
2.651
North
.041
.364
.001
.009
West
.124
2.435
.034
2.704
*£<.05


78
As might be expected the peer-group interaction,
faculty-student interaction, and social integration variables
were all highly correlated. This is understandable since
peer-group interaction and faculty-student interaction variables
comprise the social integration variable. Only two variables
were significantly correlated with actual dropout rates. For
the total and West campuses the higher the student's background
characteristics the more likely the student would persist. East
Campus students with higher academic integration levels were
more likely to persist. The remaining statistically significant
correlations between the variables under study showed a variety
of relationships. These relationships indicated various degrees
of support for Tinto1s inclusions of these variables in his
model.
Regression Analysis
Tinto's conceptual model considered in this study was
given in Figure 1 (see page 3).
Test of Hypotheses 1-4
Hypothesis 1. A significant proportion of the variation
in student dropout rates is not explained by
selected social system variables after controlling
for student background characteristics, student
commitments, and the academic system.
The test of the full model was a test of the regression
coefficients background characteristics, commitments, academic


140
A second recommendation concerns the models that are
theorized to explain dropout decisions. The models presently in
existence are the result of a considerable amount of research and
provide very useful information for practioners and educational
researchers. Further research should expand these models, not
only into other reconceptualized models, but also into more
flexible applications, such as isolating parts of the models and
developing ways to utilize the parts separately as well as the
whole. Researchers should be concerned with what particular
parts of the models are useful in particular settings and which
ones can be modified to better fit the unique institutional
settings or needs.
A third recommendation concerns the methodology.
Consideration should be given to the sample size of the
population under study. If each campus, of a multi-campus
population, is to be analyzed then a larger sample size should be
drawn for each individual campus. In additional possible
attention should be given to the total dropout rate of 40% not
just degree seeking students.
A final recommendation, and possibly the most important
one, concerns the application of retention models to individual
institutional settings. Just as there is not one instructional
method that should be applied to all students, and one curriculum
that fulfills the needs of all institutions, there should not be
one isolated retention plan utilized to retain all potential
dropouts in any one institution. A strong recommendation of this


Table 17
Means, S.D., and Computed t-Statlstic Comparing Male
and Female Students on the Social System Variable
CAMPUS
HYP.
NO.
MALE STUDENTS
MEAN S.D.
NO.
FEMALE STUDENTS
MEAN S.D.
df
t
Total
8
50
10.102
1.410
102
10.028
.616
150
.353
East
8
11
10.417
2.816
28
10.275
.715
37
.164
North
8
14
9.974
.531
25
10.078
.594
37
-.562
West
8
25
10.035
.723
49
9.862
.518
72
1.067
*£<.05


136
settings: four-year residential institutions, four-year commuter
institutions, and two-year commuter institutions. In the
residential school, social integration was found to have a direct
effect on college persistence and no direct effect in either of
the commuter schools. This was also the findings in this study.
This lack of effect was possibly attributed to the institutional
setting or the difference in commuter students and residential
students. Commuter students generally spend less time on campus
and have environments that were less rich in terms of social
integration opportunities than residential institutions
(Chickering, 1974). Another possible explanation for this lack
of effect was that students with high level social integration
tend to have high affiliation needs. Community College students
may be more sensitive to the lack of opportunity for social
interaction in communter colleges and either transfer to
residential schools or withdraw (Pascarella & Chapman, 1983).
Astin (1973) and Chickering (1974) suggested that the commuter
student may be a different type all together than the residential
student and these differences may be an important factor
effecting patterns of variables involved in the retention
process. An additional explanation might be that the low dropout
rate represented an insufficient number of subjects to allow for
complete analysis.
From these findings a reconceptualization of Tinto's model
was suggested by Pascarella, Duby, and Iverson (1983) and
Terenzini, Pascarella, Theophi1ides, and Lorang (1983). This


183
40. During this term, in how many extracurricular activities did
you spend, on the average, more than 2 hours per week?
(include clubs, organizations, organized athletics,
etc.).
SECTION FIVE: DROPOUT DECISION
This information indicates the perceived intent of
the individual's educational plan
Directiosns: Please check ONLY ONE of the available options.
41. What are your immediate future educational plans?
1. I plan on returning to PHCC next term
2. I plan on returning to PHCC but not
necessarily next term
3. I plan on attending another institution
next term
4. I plan on attending another institution,
rather than PHCC, but not necessarily next term
5. I am not planning to return to this or any
other institution anytime in the forseeable
future
Directions: Please take a few minutes to make sure you have
answered ALL questions
Thank you very much for you time and cooperation


2
attrition by developing a predictive, explanatory model of the
dropout process which has at its core the concepts of student
academic and social integration into the institution.
Tinto (1975), in his article "Dropout from Higher Education:
A Theoretical Synthesis of Recent Research," drew upon Durkeim's
(1961) theory on suicide which essentially theorizes that suicide
is more likely to occur when individuals are insufficiently
integrated into the fabric of society. Spady (1970) first
applied Durkeim's theory to college student dropouts by
suggesting that a college is a social system with its own values
and belief system.
Tinto (1975) further suggested that social conditions
affecting dropouts from college would be similar to those social
conditions resulting in suicide in society as a whole.
Specifically, he stated:
Insufficient interaction with others in the college and
insufficient congruency with the prevailing value
patterns of the college collectively ... will lead
to low commitment to that social system and will
increase the probability that individuals will decide
to leave college and pursue alternative activities.
(P-92)
The model Tinto developed to depict his theory on college
dropout decisions emphasized two main areas of integration: the
academic and social systems (see Figure 1 on p.U). These areas
of integration have been verified as causes of college dropouts
and as explanations for college student persistence (Bayer, 1968;
Denzin, 1966; Medsker & Trent, 1968; Rootman, 1972; Scott, 1976;
Spady, 1971).


148
Pervin, L., Reik, L., & Dalrymple, W. (1966). The college
dropout and the utilization of talent. Princeton:
Princeton University Press.
Prather, J. E. (1982). Persistence toward a degree at Georgia
State University. Institutional Research Report no. 82-13,
Georgia State University, 1-12.
Ramist, L. (1981). College student attrition and retention.
College Board Report no. 81-1, College Entrance Examination
Board, 1-37.
Reed, J. G. (1981). Dropping a college course: factors
influencing students' withdrawal decision. Journal of
Educational Psychology, 73, 376-385.
Rootman, I. (1972). Voluntary withdrawal from a total adult
socializing organization: A model. Sociology of Education,
45, 258-270.
Scott, N. (1976). The effects of returning to college and
assertiveness training on self-concept and personality
variables of mature women, Dissertation Abstracts, 37 ,
4873-A. (University Microfilms No. 77-32,319.
Sewell, W., & Shah, V. (1967). Socioeconomic status,
intelligence, and the attainment of higher education.
Sociology of Education, 40, 1-23.
Short, E.C. (1979, Summer). Knowledge production and untiliztion
in curriculum: a special case of the general phenomenon.
Review of Educational Research, pp. 237-301. Copyright 1979,
American Educational Research Association, Washington, D.C.
Simpson, C., Baker, K., & Mellinger, G. (1980). Conventional
failures and unconventional dropouts: Comparing different
types of university withdrawals. Sociology of Education
52, 203-214.
Slocum, W.L. (1956). Social factors involved in academic
mortality. College and University, 32 (1), 53-64.
Spady, W. (1970). Dropouts from higher education: An indis-
ciplinary review and synthesis. Interchange, 2i 64-85.
Spady, W. (1971). Dropouts from higher education: Toward an
empirical model. Interchange, 2 (3), 38-62.
St. John, N. (1971). The elementary school as a frog-pond.
Social Forces, 48, 581-595.


89
F-statistic of .356. This resulted in a fail to reject decision
for Hypothesis 3. The partial regression coefficient of -.244
2
for North Campus resulted in an R increase of .167 and an
2
F-statistic of 7.284. This variation in the R was significant
at the .05 level, since the computed F-statistic exceeded the
critical F-statistic. The conclusion was to reject Hypothesis
3. Students who had high scores on faculty-student interaction
were more likely to drop out than students who had low scores on
the variable.
Hypothesis 3 was tested on four separate groups, total,
East, North, and West campuses. Two different dependent
variables were used, students' perceptions of dropout decisions
and students' actual dropout rate. Of the eight separate tests
of Hypothesis 3, both East Campus and North Campus, with
students' actual dropout rate as the dependent variable, were
found to be significant.
Hypothesis 4. There is no interaction effect between
peer-group interaction and faculty-student interaction.
The test of the hypothesis was a test of the partial
regression coefficient for the interaction between peer-group
interaction and faculty-student interaction given background
characteristics, commitments, academic system, peer-group
interaction, and faculty-student interaction were in the model.
The results of the analysis are presented in Table 12 with
students' perceptions of dropout decisions as the dependent
variable.


26
The major difference between residential institution and
commuter institution was the role played by academic and social
integration variables. The residential sample reported academic
integration having neither direct nor indirect effect on
voluntary persistence. Social integration was found to have a
significant direct effect on persistence. Conversely, in both
the four-year and two-year commuter institutions, social
integration had neither a direct nor indirect influence on
student persistence. Academic integration indirectly influenced
persistence through its direct effects on institutional
commitment.
The pooled analysis of this study suggest that Tinto's
model is potentially useful in predicting and explaining
persistence/withdrawal behavior. Under separate analysis,
results for different institutional settings may vary
substantially.
Another study concerning the efficacy of the
person-environment fit theory promoted by Tinto was conducted in
a non-residential school by Pascarella, Duby, and Iverson (1983).
Background characteristics were reported as having greater
influence on persistence than social integration. This apparent
influence was partially explained by the differences between
residential and commuter institutions. Commuter students'
environments were found to be generally less rich in terms of
social integration opportunities than residential students'


156
8. There i^s a great many people in the United States who do not
A B
have enough to eat each day. No error
C D
9. The new film will show the different kinds of Indian arts and
A B
crafts produced in North America. No error
C D
10. Like other trucks, James must sonetimes drive his
A B
tractor-trailer through the night to reach his destination on
C
time. No error
D
11. Rita Moreno appeared in a television commercial informing
A B
people of their civil rights. No error
C D
12. Some nurses will not work for doctors in private practice,
A
and they will work in community health programs. No error
B C D
13. At the end of the meeting, Clara announced formerly that she
A B
was resigning as president. No error
C D
14. The black judges meeting in Atlanta talked of possible ways
A
of securing justice for black people under a judicial system
B C
dominated by whites. No error
D
15. One of the dangers to young children comes from their
A B
attitude of eating chips of lead paint from the walls. No error
C D
GO ON TO THE NEXT PAGE


66
total college population mean for English was 26.5 and 26.8 for
the sample. These data, combined with the demographic
information in Table 1, reflected very similar data between the
sample and the total population under consideration.
Correlations
Pearson product moment correlations for all variables under
investigation for the sample are shown in Table 2. Correlations
for East Campus are listed later in Table 3, North Campus Table
4, and West Campus Table 5. The dichotomous variables were coded
as follows: persisters 1, withdraws 0; males 0, females 1; white
students 0, non-white 1; and having a human relations type course
1, not having the course 0.
Most of the intercorre1ations for total campus were
non-significant. Only fourteen, out of 91 correlations, were
found to be significant at the .05 level. Because retention was
the dependent variable the two significant correlations relating
to retention are presented first. The higher one's background
support scores, the more likely one would actually remain in
school (r=.197). The only other variable relating to actual
dropout rate was perception of dropout decision and it showed a
positive correlation (r=.377) with the actual dropout rate. The
following correlations are presented in the order in which they
appear in Table 2. Older students seemed to be academically
integrated to a greater degree than younger students (r=.272).
More females had had a human relations type course (r=-.691), and
were more committed than males ( r=. 206) The more


127
Table 27
Results of Hypotheses
Dropout Perception
Actual
Dropout
Hypotheses
F-statistic Decision
F-statistic
Decision
1.
Total
.192
Fail
to
Reject
.686
Fail
to
Reject
East
2.569
Fail
to
Reject
2.651
Fail
to
Reject
North
.837
Fail
to
Reject
.009
Fail
to
Reject
West
.448
Fail
to
Reject
2.704
Fail
to
Reject
2.
Total
1.420
Fail
to
Reject
1.333
Fail
to
Reject
East
.623
Fail
to
Reject
5.558*
Reject
North
1.551
Fail
to
Reject
4.728*
Reject
West
1.037
Fail
to
Reject
2.773
Fail
to
Reject
3.
Total
.268
Fail
to
Reject
.002
Fail
to
Reject
East
.978
Fail
to
Reject
4.253*
Reject
North
.192
Fail
to
Reject
7.284*
Reject
West
.031
Fail
to
Reject
.356
Fail
to
Reject
4.
Total
.001
Fail
to
Reject
.522
Fail
to
Reject
East
.137
Fail
to
Reject
.298
Fail
to
Reject
North
.357
Fail
to
Reject
2.232
Fail
to
Reject
West
.327
Fail
to
Reject
.107
Fail
to
Reject
t-statistic
5.
Total
1.942
Fail
to
Reject
East
2.134*
Reject
North
.714
Fail
to
Reject
West
.014
Fail
to
Reject
6.
Total
1 .336
Fail
to
Reject
East
1.796
Fail
to
Reject
North
.045
Fail
to
Reject
West
.394
Fail
to
Reject
7.
Total
1.386
Fail
to
Reject
East
1.973
Fail
to
Reject
North
1.731
Fail
to
Reject
Reject
West
- .704
Fail
to
(continued)
*£<05


49
student non-classroom contact of 10 minutes or more with faculty
concerning personal and/or social matters, item 39(1, 2, & 3).
For the items concerning quality of faculty contact, a value of 5
was assigned to "SA" through 1 for "SD" for items 34, 36, 37, and
38. The reverse value assignment was used for item 35. The
frequency scores for items 39(1), 39(2), and 39(3) were summed,
divided by 3, then converted into a Z-score, adding a constant of
10. The frequency score was summed with the Z-score which was
the result of totaling the values from the items 34-38, dividing
by 5, then transforming into a Z-score, adding a constant of 10.
The sum of these two Z-scores was divided by 2, resulting in the
faculty-student interaction measurement.
Dropout decision
The majority of the research studies used an intent item
(intention of remaining in school) and official records from the
registrar to measure withdrawals. Dropout decisions, in this
study, was operationally defined as the student's perceived
educational plans for the future, item 41. Each student was
placed in a group according to his or her degree of intent to
persist as indicated by his or her selection of one of these five
options: (1) I plan on returning to PHCC next term; (2) I plan on
returning to PHCC but not necessarily next term; (3) I plan on
attending another institution next term; (4) I plan on attending
another institution, rather than PHCC, but not necessarily next
term; or (5) I am not planning to attend this or any other
institution anytime in the forseeable future. These responses


170
Common experience leads us to connect a number of patterns
of behavior with habitual silence. They occur in constellations:
first, shyness, timidity, and uncertainty; then pride, (5)
stubbornness, and sullenness; and finally, distance, depression,
and despair. Thus we have three groups, one connected with fear
and anxiety, one with withholding and rage, and the last with
sadness or hopelessness.
(10) These patterns can affect cultures or nations as well as
individuals, and it is evident that to understand another
person's silent behavior, one must have at least some sense of
the cultural background within such behavior originates.
(15) Suspiciousness is the most common reason for a cultural
pattern of speaking only when absolutely necessary. Such
suspiciousness is a culture usually develops when that culture
has had a long history of oppression and mistreatment by other
(20) cultures. Since open defiance has led to destruction, the
alternative for members of the culture is to see nothing, know
nothing, and, above all, say nothing. If one is dull and
unresponsive, the oppressor is unlikely to bother him for long.
(25) If you would make friends, then, with someone whose culture
has been to adopt this pattern of suspiciousness, you must
develop an understanding of the cultural position from which his
suspiciousness springs and you must again and (30) again
demonstrate unswerving trustworthiness and goodwill.
22. In line 3, "constellations" most nearly means
A. heavens
B. clusters
C. stars
D. men
23. According to the passage, a culture usually adopts the
pattern of speaking only when absolutely necessary because
it
A. likes being annoying
B. does not know the language others use
C. has reason to distrust others
D. wants to show others how to behave
24. According to the passage, to make fiends with one who is
quiet because he is a part of a mistreated culture, you
should
A. constantly tell him he is like everyone else
B. never stop studying his behavior
C. try to find common experiences
D. continually show that you are worthy of his trust
GO ON TO THE NEXT PAGE


147
Nelson, J. (1972). High school context and college plans: The
impact of social structure on aspirations. Ame rican
Sociological Review, 37, 143-148.
Noel, L. (1976). College studentA campus-wide responsibility.
National ACAC Journal. 26 (1) 33-36.
Pancos, R., & Astin, A. (1968). Attrition among college students
American Educational Research Journal, 5 (1), 57-72.
Pantages, T., & Creedon, C. (1978). Studies of college
attrition: 1950-1975. Review of Education Research,
49-101.
Pascarella, E.T. (1968). Studying student attrition. New
Direction for Institutional Research, 36, (4), 104.
Pascarella, E.T., & Chapman, D.W. (1983). A multiinstitutional
path analytic validation of Tinto's model of college
withdrawal. American Educational Research Journal, 20,
87-102.
Pascarella, E.T., Duby, P.B., & Iverson, B.K. (1983). A test
and reconceptualization of a theoretical model of
college withdrawal in a commuter institution setting.
Sociology of Education, 56, 88-100.
Pascarella, E. & Terenzini, P. T. (1976). Informal interaction
with faculty and freshmen ratings of the academic
and non-academic experience of college. Journal of
Educational Research, 70, 35-41.
Pascarella, E., & Terenzini, P. (1977). Patterns of student-
faculty informal interaction beyond the classroom and
voluntary freshman attrition. Journal of Higher
Education, 48 (5), 540-552.
Pascarella, E.T., & Terenzini, P.T. (1980). Predicting
persistence and voluntary dropout decisions from a
theoretical model. Journal of Higher Education, 61, 60-75.
Pascarella, E.T., & Terenzini, P.T. (1983). Predicting
voluntary freshman year persistence/withdrawal behavior in a
residential university: A path analytic validation of
Tinto's Model. Journal of Educational Psychology, 75 ,
215-226.
Penick, B.E., & Morning, C.A. (1982). Retaining minority
engineering students: Key factors. Engineering Education
72, 28-730.


119
hypotheses were found significant on East Campus and North Campus
and resulted in a decision to reject Hypotheses 2 and 3.
Hypothesis 2. A significant proportion of the variation in
student dropout rates is not explained by peer-group
interaction after controlling for student background
characteristics, student commitments, the academic
system, and faculty-student interaction.
Students on the North Campus who remained in school scored
higher on the peer-group interaction scale than students who
withdrew from school. The reverse is true for the East Campus.
Students who remained in school scored lower on the peer-group
interaction scale than students who withdrew from school.
Hypothesis 3. A significant proportion of the variation in
student dropout rates is not explained by faculty-student
interaction after controlling for student background
characteristics, student commitments, the academic system,
and peer-group interaction.
Students on the North Campus who remained in school scored
lower on the faculty-student interaction scale than students who
withdrew. The reverse is true for the East Campus. Students who
remained in school scored higher on the facu 11y-student
interaction scale than students who withdrew from school.
A t-test statistic was used to analyze Hypotheses 5-13.
The following hypotheses were found to be significant at the .05


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.
Albert B. Smith III, Chairman
Professor,
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
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.
Steve Olejnik
Associate Professor,
Foundations of Education


36
Intellectual development. Tinto (1975) stated that
intellectual development deals with intrinsic forms of reward;
this development is the individual's evaluation of the academic
system. Medsker and Trent (1968) referred to intellectual
development as the degree to which students value their college
education as a process of gaining knowledge and appreciating
ideas. Spady (1971) suggested that intellectual development is
exposure to stimulating ideas and experiences.
Though not as important as grade performance, intellectual
development was found to be an influencing variable in students'
decision to drop out (Rootman, 1972; Spady, 1970; Summerskill,
1962; Tinto, 1975). Tinto states,
Though grade performance and intellectual development
appear as separate components of a person's integration
into the academic system, it's clear that persons with
high grades are more likely to be high in measures of
intellectual development, (p. 106)
The distinction may be that grade performance is generally
measured objectively, whereas intellectual development is more
likely a subjective measurement.
Peer-Group interaction. Terms used to describe peer-group
interaction included friendship support (Flacks, 1963), social
fit (Rootman, 1972), supportive groups (Hanson & Taylor, 1970),
and normative congruence (Spady, 1970). In general, researchers
concluded if students perceive themselves as being accepted by
some form of peer-group, college persisters will be enhanced


79
system, and social system. The full model yielded an R of .022
with an F-statistic of .835 which was not significant at the .05
level. The test of this hypothesis was a test of the partial
regression coefficient for the social system variable given that
background characteristics, commitments, and academic system
were in the model. The results of the analysis are presented in
Table 6.
For the total campus when the dependent variable was
2
students' perceptions of dropout decision, the R with all
variables in the model was .022. Without social system in the
model it was .021. Thus adding the social system variable
explained .1% additional variation in perceived dropout. This
increase in variation resulted in a computed F-statistic of
.192, which did not exceed the critical F-statistic at the .05
level. Therefore the conclusion was to fail to reject
Hypothesis 1. The social system variable does not help predict
4
dropout rate.
2
The full model for East Campus resulted in an R of .185
with an F-statistic of 1.933, which was not significant at the
2
.05 level. The R increase and computed F-statistic for East
Campus for the partial regression coefficient were .062 and
2.569. This was not significant at the .05 level.
2
The full model for North Campus yielded an R of .029 with
a non-significant F-statistic of .253 at the .05 level. The
2
partial regression coefficient had an R increase of .024 and an


Table 2-contnued
VARIABLES
7
8
9
10
11
12
13
1.
Age
.022
.272*
.008
-.047
-.048
.091
.023
2.
Sex
.206*
.158
-.001
. 106
-.037
-.030
.030
3.
Race
-.003
-.146
-.098
-.076
-.085
-.003
. 109
4.
Accumulated Hours
.177
-.008
-.038
.004
-.093
-.059
.112
5.
Human Relations Course
.054
.054
.039
.096
.006
-.089
.082
6.
Background Characteristics
.086
.172
.075
.061
-.035
-.118
.197*
7.
Commitment
.296*
-.050
.150
-.099
.007
.055
8.
Academic Integration
.208*
.415*
.200*
.062
.143
9.
Peer-group Interaction
.318*
. 575*
.117
.130
10.
Faculty-student Interaction
.612*
.090
.083
11.
Social Integration
.056
-.048
12.
Dropout Perception
.377*
13.
Dropout Actual
*£<.05


46
through 1 for "not at all important." Each score was converted
into a Z-score, adding a constant of 10, summed, then divided by
2.
Institutional commitment. The following were used by all or
a majority of the studies to measure institutional commitment:
(1) institutional rank as a college choice, item 10; (2)
probability of transfering before graduation, item 13; and (3)
confidence or satisfaction that choosing the subject institution
was the right choice, item 12.
A value of 4 was assigned to "1st choice" through a value of
1 for "4th choice" on item 10, a value of 5 to "SD" through 1 for
"SA" on item 13, and a value of 4 to "extremely confident"
through 1 for "not at all confident" on item 12. These three
values were converted to Z-scores, adding a constant of 10 to
each, summed, and then divided by 3.
Academic system
Academic system was operationalized as the sum of the
following scales or variables: (1) grade point average, provided
by the registrar; (2) a seven-item factorially derived scale
measuring a student's perceived level of intellectual
development, items 15-21; (3) a five-item, factorially derived
scale measuring a student's perception of faculty members concern
for student development and teaching, items 22-26; and (4) the
frequency of a student's out-of-class contact with faculty of 10
minutes or more for each of the following purposes: (a) "to get
basic information and advice about my academic program";


50
were then converted to a dichotomously coded dependent measure
with response (1) indicating persistence (coded 1) and responses
(2), (3), (4), and (5) indicating withdrawal (coded 0). In
addition, the dropout decision variable was also operationalized
as actual persistence or non-persistence the following term based
on school records.
Four university professors reviewed the preliminary
instrument, Dr. Al Smith, Dr. Steve Olejnik, Dr. Gordon Lawrence,
and Dr. Paul Fitzgerald. These individuals were instructed to
take note of possible areas of revision in terms of clarity or
wording in instructions, possible ambiguity of items, and
relevance of items to the variables under consideration in this
research study.
Pilot study. The investigator conducted a pilot study to
determine the suitability of the instrument format and to provide
data for analysis of the items.
Subjects. The pilot sample consisted of a total of 40
students. Ten subjects were selected randomly from the East
Campus of PHCC, 10 subjects from the North Campus of PHCC, and 20
subjects from the West Campus of PHCC. The West Campus has a
student population approximately equal to the East and North
combined; therefore twice the number of subjects was required to
increase the generalizabi1ity of the pilot study findings. A
total of 38 usable surveys was returned. The survey


PASCO HERNANDO COMMUNITY COLLEGE
Equal Access-Equal Opportunity Institution
Dear Student,
You have been specially selected to participate in a college
wide study. This study is a combined sponsorship of the faculty,
administration, and Student Services Department of Pasco Hernando
Community College.
The study is concerned with investigating reasons why
students remain in college or choose to leave. By giving a few
minutes of your time (approximately 15 minutes) you will help
educators to better understand students' reasons for persisting
in college. In addition, your contribution will assist
educational planners develop more effective ways to prevent
student dropouts. Your concern about this matter is shared by
all of us at Pasco Hernando Community College.
Your cooperation and efforts will be greatly appreciated by
all of us associated with PHCC. You can take pride in knowing
you helped your fellow students, both present and future, better
accomplish their goal of a college education.
Sincerely,
Michael G. Rom
Research Director
From the East Campus (904) 567-6701
2401 State Highway 41 North, Dade City, Florida 33525
175


85
2
R of .334 and a F-statistic Of 3.315. The partial regression
2
coefficient of -.199 resulted in an R increase of .112 and a
F-statistic of 5.558. Since this did exceed the critical
F-statistic at the .05 level the decision was to reject
Hypothesis 2. The higher the peer-group interaction score the
more likely a student would drop out.
2
The full model for North Campus had an R of .242 with an
2
F-statistic of 2.112 and West Campus had an R of .131 with an
F-statistic of 2.055. Both were non-significant at the .05
level. The partial regression coefficient of .157 for North
2
Campus resulted in an R increase of .109 and a computed
F-statistic of 4.728, which exceeded the critical F-statistic at
the .05 level. This resulted in the conclusion to reject
Hypothesis 2. The higher the peer-group interaction score the
more likely the student will remain in school. West Campus had
2
an R increase of .035 that resulted in computed F-statistics of
2.773 This did not exceed the critical F-statistic at the .05
level resulting in a fail to reject conclusion for Hypothesis 2.
Hypothesis 2 was tested on four different populations,
total, East, North, and West campuses. Two different dependent
variables were used, students' perceptions of dropout decisions
and students' actual dropout rate. Of the eight separate tests
of Hypothesis 2 only two were found to be statistically
significant. On the East and North campuses, with students'
actual dropout rate as the dependent variable, Hypothesis 2 was
found to be statistically significant.


143
Bean, J. (1981). Student attrition, intentions and confidence:
interacion effects in a path model. Paper presented at the
annual meeting of the American Educational Research
Association, Los Angeles.
Bean, J. P. (1982, March). The interaction effects of GPA on
other determinants of student attrition in a homogeneous
population. Paper presented at American Educational
Reaseach Association, New York City.
Beck, M.C. (1980). Decreasing the risk students. Community and
Junior College Journal, 51, 4-6.
Bennet, C., & Bean, J. (1983, April). Explanations of
attrition among black students at a predominantly white
institution. Paper presented at American Educational
Reasearch Association, Montreal, Canada.
Blanchfield, W. (1971). College dropout identification: A
case study. Journal of Experimental Education, 40 (2),
1-4. "
Bourn, K. (1976, October). Self-concept development for high
risk students in the community college. Paper presented
at the annual meeting of the College Reading Associaton,
Miami, Florida.
Brown, K. G. (1980, April). Dropout rates: A longitudinal
analysis of student loan users compared with users of other
forms of financial assistance. Paper presented at the
Association for Institutional Research, Atlanta, GA.
Centra, J., & Rock, D. (1971). College environments and student
achievements. American Educational Research Journal,
623-634.
Cesa T. A. (1980). Undergraduate leavers and persisters
at Berkeley: Results of a telephone survey conducted
in Spring 1979. Berkeley, CA: University of California,
Berkeley.
Chase, C.I. (1970). The college dropout: His high-school
prologue. Bulletin of the National Association of
Secondary School Principals, 54, 66-71.
Chickering, A. (1974). Commuting versus residential students:
Overcoming education: The inequities of living off-campus.
San Francisco: Jossey-Bass.


137
model was suggested as a more adequate model to be utilized by
commuter schools than Tinto's original conceptual model. This
revised model promotes background characteristic varibales as
having greater influence on student persistence in commuter
schools than social integration and social integration having no
significant direct effect or a negative effect. This
reconceptualized model appeared more adequate for West Campus and
possibly the total campus since social integration had no direct
influence on dropout decisions in either population group.
Special consideration would have to be given to the East and
North campuses, for their characteristics favoring residential
schools, if the reconceptualized model was applied to the total
campus.
The main implications of this study centered around the
main concepts implied by earlier research. First, there may be
one model of the dropout process that applies to residential
schools and one model that applies to communter schools and
second, these models are more or less complete in their variable
relationships in reference to the two different institutional
settings. The results of this study showed that within a single
commuter school, there may be individual campuses that are more
characteristic of residential schools. Specifically, Tinto's
model may be more applicable to the East and North campuses of
PHCC, with their direct relationship between faculty-student
interaction and peer-group interaction, whereas the
reconceptualized model may be more applicable to the West


165
READING
Time-25 minutes
35 Questions
The spider is one of Nature's most successful wanderers.
Found all over the world, it is able to travel huge distances.
When a traveling spider approaches a stream or river, it uses a
unique (5) method of locomotion. Rolling over on its back, the
spider shoots out glue-tipped glob of web material attached to a
line, gradually paying out more and more line as the wind carries
the "anchor." If the arrowing line strikes a secure (10) target
on the favored side of the water, the spider then clibs a bush
and walks over the bridge. Another method of locomotion is even
more dramatic. The spider again spins out a sticky line ending
in a swollen tip. If the line is kept short (15) and the spider
does not attach itself firmly to an anchoring bush or rock, the
wind- will carry the creature far away to an unknown destiation.
Such sailing spiders have been scraped off the superstructures of
ships several hundred miles away from the nearest land.
1. The passage is mainly concerned with how spiders
A. travel
B. spin webs
C. cross rivers
D. reach ships
2. As used in lines 5 and 12, "locomotion" most nearly means
A. attacking
B. moving
C. shooting
D. spinning
3. The author feels that it is especially dramatic that the
spider
A. rolls over on its back
B. spins out a sticky line
C. anchors to rocks and bushes
D. sails through the air
4. From the way "superstructures" is used in line 19, it is
probable that the ship parts are to be found
A. inside the ship
B. at the waterline
C. near the propeller
D. on the top section
GO ON TO THE NEXT PAGE


31
This reconceptualization of Tinto1s model for use in
non-residential institutions needs to be tested across different
samples. Only a partial description of the model was included so
as not to imply a complete testing of its validity by the present
research investigation. Both models were included to provide the
reader with background information concerning existing research.
This present study mainly investigated the influence of social
integration on persistence in reference to Tinto's model.
Results obtained may, in addition, provide further information
that will enhance the promotion of the revised model of
Pascarella, Duby, and Iverson (1983).
Variables
In order to relate Tintos model of retention and
corresponding literature to this investigation, it was necessary
to isolate and document characteristics and/or measurements that
most substantially represent the variables under consideration.
The following variables in Tinto's model of retention were
investigated for research support: background characteristics
(consisting of family background, individual attributes, and pre
college schooling), commitments (consisting of goal commitment
and institutional commitment), academic system (consisting of
grade performance and intellectual development), social system
(consisting of peer-group interaction and faculty-student
interaction), and dropout decisions. The following sections
contain a review of the research in these areas.


no
Total campus had a -.093 correlation coefficient which was
not significant at the .05 level. East Campus, North Campus,
and West Campus recorded coefficients of -.162, -.184, and .030
respectively. None of these were significant at the .05 level.
The decision in all four groups was fail to reject Hypothesis
14. There is no correlation between student semester hours and
the social system variable.
Hypothesis 15. There is no correlation between student
semester hours completed and the peer-group interaction
variable.
The correlation coefficients for total campus was -.038,
East Campus -.083, North Campus -.106, and West Campus .012.
All of these groups resulted in a failure to reject decision for
Hypothesis 15, since they were not significant at the .05.
Hypothesis 16. There is no correlation between student
semester hours completed and the facu1ty-student
interaction variable.
The total campus correlation coefficient of .004 was not
significant at the .05 level, therefore resulting in a failure
to reject decision for Hypothesis 16. Each of the individual
campuses also resulted in the same decision by recording
correlation coefficients for East .054, North -.106, and West
.062. There is no correlation between student semester hours
completed and the faculty-student interaction variable.
All data concerning hypotheses 17-19 are presented on
table 24.


135
Implications
The purpose of this research was to use Tinto's (1975)
conceptual framework model of student retention to determine what
relationships exist between social system integration variables
(peer-group interaction and facu1ty-student interaction
variables) and student dropout decisions in a two-year, community
college. The model was partially verified by two of the four
population groups under study. East and North campuses, of
Pasco-Hernando Community College, did follow the general
longitudinal process of dropout decision promoted by Tinto in
reference to peer-group interaction by the North Campus, and
faculty-student interaction by the East Campus with a direct and
positive influence on the student's decision to drop out of
school. This finding showed that Tinto's model may be partially
useful in connection with studying the dropout process of
community college students.
The results in the study were consistent with other
findings (Pascarella & Terenzini, 1983) with the exception that
PHCC is a commuter school and other studies verifing Tinto's
model were residential. Terenzini, Pascarella, Theophilides, and
Lorang (1983) verified the social system's negative influence on
persistence in residential schools which was also found in the
East Campus for peer-group interaction and the North Campus for
faculty-student interaction. In considering the validity of
Tinto's model in residential or commuter schools, Pascarella and
Chapman (1983) studied three different types of institutional


103
reject Hypothesis 10. There was no difference between male and
female students' scores on the faculty-student interaction
variable. East Campus had a significant computed t-statistic of
-2.056, with means for males of 9.912 and females 10.501, in the
direction of female students. The decison was to reject the
Hypothesis 10. Female students scored higher on the
faculty-student interaction variable than male students. North
Campus means for males were 9.890 and females 9.994 and West
Campus means were 9.867 for males and 9.833 for females. Both
resulted in a fail to reject decision for Hypothesis 10, with
computed t-statistics of -.499 and .189 respectively.
Hypothesis 11. There is no significant difference
between students who have taken a human relations type
course and students who have not on student measurements
of the social system variable.
Table 20 presents the results of Hypothesis 11. The
computed t-statistic for total campus was .098, with means of
10.061 for students with the course and 10.047 for student
without the course. East Campus t-statistic was -.052, with
means of 10.300 for students with the course and 10.324 for
students without the course. The test of Hypotheis 11, for both
total and East campuses, failed to exceed the critical
t-statistic at the .05 level and concluded in decisions of fail
to reject Hypothesis 11. The computed t-statistic for the North
Campus was -2.67, with means of 9.787 for students with the
course and 10.237 for students without the course. West Campus


19
multi-campus community college were surveyed. Multiple
regression was used to analyze the main hypotheses of interest.
The findings and analysis of data are presented in Chapter Four.
Chapter Five includes a summary of the findings and the
conclusions drawn as a result of the study, as well as
implications for practices and further research.


LIST OF FIGURES
FIGURE PAGE
1 A Conceptual Schema For Dropout
From College (Tinto, 1975) 3
2 Suggested Reconceptualization of
Tinto's Model (Pascarella, Duby,
and Iverson, 1983) 31
x


158
WRITTEN ENGLISH EXPRESSION
Part 2
Directions: In each of the following sentences some part of the
sentence or the entire sentence is underlined. Beneath each
sentence you will find four ways of writing the underlined part.
The first of these repeats the underlined part in the original
sentence, but the other three are all different. If you think
the original sentence is better than any of the suggested
changes, you should choose answer A; otherwise you should mark
one of the other choices. Select the best answer and put an X in
the corresponding answer blank.
In choosing your answers, follow the requirements of standard
written English, the kind of English usually found in textbooks.
Remember that standard written English is sometimes different
from conversational English. Pay attention to how clearly ideas
are expressed, whether the words convey the meaning they are
supposed to convey, and how the sentence is constructed and
punctuated. Choose the answer that produces the most effective
sentence-clear and exact, without awkwardness or ambiguity. Do
not make a choice that changes the meaning of the original
sentence.
Sample Questions Sample Answers
1. Charoline is studying because she has A B C D
always wanted to become it.
A. it
B. one of them
C. a singer
D. one in signing
2. Because Mr. Thomas was angry, he spoke A B C D_
in a loud voice.
A. he spoke
B. and speaking
C. and he speaks
D. as he spoke
You will have 15 minutes to work on the 20 questions in Part 2.
DO NOT TURN THIS PAGE UNTIL YOU ARE TOLD TO DO SO
(OR, IF SELF-ADMINISTERED, UNTIL
YOU HAVE BEGUN TO TIME YOURSELF)


166
Snowplows never came through our neighborhood. It was good
they didn't because the snow was a wedge against reality we were
glad not to face. I thank God it snowed as much as it did when
we (5) were young. I thank God we were freed from everything
that was familiar.
Sometimes it seemed to snow for days; as if the elements had
contrived to free us by transforming ugliness into beauty. There
were other parts of (10) the city that hated to see the snow
come, and their snowplows worked almost daily trying to set the
calendar back. But we prayed for it in our neighborhood. There
were no landscaped gardens for us. There had been no year of fun
on the golf (15) course. There was no grass to be covered up,
only broken glass and pages of old newspapers dancing in the wind
with the leaves from the big cottonwoods that were always
shedding something. There were no rose bushes that had to be
protected (20) against the subzero temperature, only weeds that
were more than strong enough to fend for themselves. There was
really not much beauty at all, only a gray, dirty, sad world we
lived in for nine months, and we were delighted to see it
changed.
5. Which of the following is NOT part of the reality the author
describes as "everything that was familiar" (line 6)?
A. Broken glass
B. Leaves from cottonwood trees
C. Landscapped gardens
D. Dancing newspaper pages
6. The snow is welcome because it
A. forces people to protect their rose bushes
B. brings out the snowplows all over the city
C. makes an otherwise dreary world beautiful
D. helps to set the calendar back
7.
As used in line 8, "contrived" most nearly means
A. sadly failed
B. swiftly prepared
C. absolutely refused
D.; deliberately planned
8.
The passage is describing
A. a city in pioneer days
B. a run-down area of a city
C. the suburbs of a city
D. a city playground
GO ON TO THE NEXT PAGE


Table 4
Pearson Product Moment Correlation for Endogenous and Exogenous VariablesNorth Campus
VARIABLES
1 2
3
4
5
6
7
1.
Age
.136
-.210
-.101
-.158
-.511*
.074
2.
Sex
.015
-.245
-.097
-.214
.379*
3.
Race
-.034
.134
-.231
-.083
4
Accumulated Hours
.340*
.104
.208
5.
Human Relations Course
-.016
.037
6.
Background Characteristics
00
o

7.
Commitment
8.
Academic Integration
9.
Peer-group Interaction
10.
Faculty-student Interaction
11.
Social Integration
12.
Dropout Perception
13.
Dropout Actual
(continued)
*£<05


161
31. Ralph read Langston Hughes's "I Too Sing America, "which was
extremely interesting one to him.
A. America,"which was an extremely interesting one to him
B. America,"with its being interesting to him as he read
it
C. America" and it was found extremely interesting
D. America" and found it extremely interesting
32. Some people worry about overpopulation because of the food
and perhaps too many people to eat it in the future.
A. because of the food and perhaps too many people to eat
it in the future
B. because in the future there may be too many people and
not enough food to feed them
C. because in the future they may have too many people and
there will not be enough food to feed them
D. because of, in the future, perhaps having too little
food for all the people eating it
33. Sam and Roger have been friends ever since he moved next
door to him in 1965.
A. he moved next door to him
B. moving next door to him
C. Sam moved next door to Roger
D. Sam has moved next door to Roger
34. In his spare time, Willie liked to play pool, listen to
jazz, or go to the movies.
A. to play pool, listen to jazz, or go
B. to play pool, to listen to jazz, or he went
C. playing pool, listening to jazz, or to go
D. to play pool, to listen to jazz, or going
35. Miniskirts and other costumes are accepted dress now that
businesses would once have banned.
A. are accepted dress now that businesses would once have
banned
B. is an accepted way to dress now but businesses would
once have banned it
C. that businesses would once have banned are accepted
dress now
D. that businesses would once have banned is an accepted
way to dress now
GO ON TO THE NEXT PAGE


Table 3-continued
VARIABLES
8
9
10
11
12
13
1.
Age
.227
-.149
.079
-.058
.202
.159
2.
Sex
.314
.357*
.290
-.041
.486*
.207
3.
Race
-.257
-.206
-.196
-.157
-.049
.164
4.
Accumulated Hours
. 100
-.083
.054
-.162
-.127
.237
5.
Human Relations Course
.046
.197
.172
-.007
.045
.191
6.
Background Characteristics
.300
.171
.037
-. 108
-.019
.172
7.
Commitment
.360*
-.119
.044
-.0002
-.223
.164
8.
Academic Integration
.185
.189
-.067
.166
.446*
9.
Peer-group Interaction
.506*
.522*
.031
-.121
10.
Faculty-student Interaction
.512*
.148
.225
11.
Social Integration
-.259
-.272
12.
Dropout Perception
.212
13.
Dropout Actual
*£<05


96
interaction variable. East Campus reported means of 9.943 for
white and 9.491 for non-white students with a t-statistic of
1.796. North Campus means were 10.101 for white and 9.726 for
non-white students with a t-statistic of .045. West Campus
reported means of 10.009 for white and 9.775 for non-white
students with a t-statistic of .394. These three hypotheses
also resulted in a fail to reject decision of Hypothesis 6.
Hypothesis 7. There is no significant difference between
white and non-white student population measurements on the
faculty-student interaction variable.
Table 16 contains the results for Hypothesis 7. The
computed t-statistic for total campus was 1.386 with white
student means of 10.015 and non-white means 9.777. This did not
exceed the critical t-statistic at the .05 level. The
conclusion was fail to reject Hypothesis 7. There is no
difference between white and non-white students score on the
faculty-student interaction variable. East Campus, with means
of 10.404 for white students and 9.866 for non-white, North
Campus, with means of 9.999 for white students and 9.438 for
non-white, and West Campus, with means of 9.838 for white
students and 10.063 for non-white students, resulted in computed
t-statistics of 1.973, 1.731, and -.704 respectively. All three
campuses failed to
exceed the critical
t-statistic
for the
.05
level; therefore
failure to reject
Hypothesis
7 was
the
conclusion for each of the three campuses.


11
Hypothesis 11. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the social
system variables.
Hypothesis 12. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
peer-group interaction variable.
Hypothesis 13. There is no significant difference between
students who have taken a human relations type course and
students who have not on student measurements of the
faculty-student interaction variable.
Hypothesis 14. There is no correlation between student semester
hours completed and the social system variable.
Hypothesis 15. There is no correlation between student semester
hours completed and the peer-group interaction variable.
Hypothesis 16. There is no correlation between student semester
hours completed and the facu 11y-student interaction
variable.
Hypothesis 17. There is no correlation between student age and
the social system variable.
Hypothesis 18. There is no correlation between student age and
the peer-group interaction variable.
Hypothesis 19. There is no correlation between student age and
the faculty-student interaction variable.


173
32. Which of the following best explains what the author means
when he speaks of "writing history with a colored pencil".
A. Writing history that makes the deeds of men seem overly
important
B. Writing history that leaves out the suffering of
blacks.
C. Writing history that emphasizes the deeds of only one
group of people.
D. Writing history that includes the entire human race.
33.
In line 20, "sojourn" most nearly means
A. angry speech
B. large meal
C. secret voyage
D. temporary stay
34. According to the author, the black man's contribution to
the culture of the work will be to
A. uphold the worth of men of all races and nations
B. muffle the voices who criticize their homeland
C. protest against the influence of the past
D. teach others the true meaning of oppression
35. The author quotes the proverb "Only a fool points to his
heritage with his left hand" (lines 21-22) in order to
emphasize that the heritage of black people
A. has been neglected by Western man
B. is something they should be proud of
C. is often overemphasized by historians
D. has misled men in the fight for equality
STOP
IF YOU FINISH BEFORE TIME IS UP,
YOU MAY GO BACK AND CHECK YOU WORK


72
the higher the tendency for academic integration (r.360).
Peer-group interaction was positively correlated with
faculty-student interaction (r=.506) and both peer-group
interaction (r=.522) and faculty-student interaction (r=.512)
were correlated with social integration in a positive direction.
North Campus
Eleven of the 78 correlations involving North Campus
students were found to be significant at the .05 level (see Table
4). There was only one statistically significant correlation
involving dropout rate at this level. Students' perceptions of
dropout decisions were positively correlated with actual dropout
decision (r=.324). The remaining 10 correlations are presented in
the order in which they appear in Table 4. Older students tended
to have lower levels of background characteristics (r=-.511) and
females appeared more committed (r=.379) than males. A human
relations type course was more likely to be taken by students
with more accumulated credit hours (r=.340). Those students with
higher peer-group interaction scores (r=-.384) and social
integration scores (r=-.399) were less likely to have taken a
human relations type course. Students with higher academic
integration had higher levels of faculty-student interaction
(r=.482) and social integration (r=.341). Peer-group interaction
was positively related to both faculty-student interaction
(r=.385) and social integration (r=.836). Faculty-student
interaction was also related to social integration in a positive
direction (r=.817).


141
research is to investigate all the possible variables involved in
retaining students and then consider the uniqueness of the
institution and its population in developing more appropriate
retention models and practices. Further research should be
developed that will assist institutions in developing their own
needs assessments in regards to retention and in applying
retention concepts to achieve greater student retention.


63
concerning the total population were obtained from the Office of
the Registrar. The sample consisted of 152 students, East Campus
(25.6 percent), North Campus (25.6 percent), and West Campus
(48.6 percent). There were slight variations in percentages
between the sample and the actual percentage enrollment figures
for the total population of each of the three campuses.
Slightly more than half of the respondents (54.6 percent)
were between the ages of 17 and 21. The remaining age groups and
percentages were, 22-26 (13.2 percent), 27-31 (13.8 percent),
32-36 (5.9 percent), 37-41 (3.9 percent), 42-46 (5.3 percent),
47-51 (1.3 percent), 52-56 (1.3 percent), and 57+ (.7 percent).
The mean age for the sample subjects was 25.1, which approximated
the mean age of the total student population of 26.
The females out-numbered the males slightly better than two
to one, with 67.1 percent of the respondents being female and
32.9 percent being males. These percentages are comparable to
the total population, which contained 61.5 percent females and
38.5 percent males. Each of the three campuses was represented
by percentages that were within 5 percent of the percentages of
their respective total populations.
The white and non-white participants showed the same
proportional trend that was reported for the different sexes.
The sample population of 93.4 percent white and 6.6 percent
non-white was within 2 percent of the total college student
population of 5.4 percent non-white and 94.6 percent white.
Different percentages were reported for each campus, but these