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Predicting academic performance of underprepared freshmen with high school GPA, ACT scores, learning styles, psychological type, and learning skills

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Predicting academic performance of underprepared freshmen with high school GPA, ACT scores, learning styles, psychological type, and learning skills
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Thesis (Ph. D.)--University of Florida, 1985.
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Includes bibliographical references (leaves 199-203).
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Typescript.
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i


8606742
Moore, Robert L.
PREDICTING ACADEMIC PERFORMANCE OF UNDEPREPARED FRESHMEN
WITH HIGH SCHOOL GPA, ACT SCORES. LEARNING STYLES,
PSYCHOLOGICAL TYPE, AND LEARNING SKILLS
The University of Florida
Ph.D. 1985
University
Microfilms
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Copyright 1985
by
Moore, Robert L.
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PREDICTING ACADEMIC PERFORMANCE OF UNDERPREPARED
FRESHMEN WITH HIGH SCHOOL GPA, ACT SCORES,
LEARNING STYLES, PSYCHOLOGICAL TYPE,
AND LEARNING SKILLS
BY
R08ERT L. MOORE
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


In Loving Memory
Of Robert H. Moore


ACKNOWLEDGEMENTS
The author wishes to thank the members of his doctoral
committee for their guidance and assistance in developing the
dissertation. Dr. Lee Mullally and Dr. William Hedges were
very supportive and helpful during the writing of the
dissertation, and the long-time friendship of Bill Hedges was
especially comforting. Dr. Mary McCaulley provided both warm
support and critical analysis during the writing stages,
particularly concerning the Myers-Briggs theories and
analyses. Most of all, the author appreciates the guidance
and encouragement from the chairman of the committee, Dr.
Gordon Lawrence. His gentle, yet insistent, support made the
final product possible. The author was honored to have his
mentor. Dr. Katherine Steele, read the final draft and be
present at the defense, and he wishes to have her know she
provided an impetus to finish even though living hundreds of
miles away.
The statistical analyses and computer runs would not
have bean possible without the patient assistance of Rita
Berg and JoLynda Hoggard, and the author is extremely
grateful to both of them. Much of the typing was done by
Evelyn Fuller, and her long hours at the word processor are
very much appreciated. The staff at the Academic Development


Office was understanding of the author's preoccupation during
the writing of the dissertation, and they were constant
sources of ideas and encouragement. The staff of the Career
Planning and Placement Office made the author feel welcome,
and he appreciates the use of the word processor in that
office.
Throughout the long period of the research and writing
of the dissertation, the author has had the comfort and
support of three wonderful daughters. Andrea, Rebecca, and
Rochelle provided more than they realize.
For her unselfish, loving support, which never waivered
even when it should have, the author is grateful to Nancy
Noth. It will take awhile, but the weekends will be repaid.
v


TABLE OF CONTENTS
PAGE
ACKNOWLEDGEMENTS iv
LIST OF TABLES ix
ABSTRACT xiii
CHAPTERS
ONE INTRODUCTION L
The Problem I
Background for the Problem 2
Purpose of the Study II
Assumptions and Delineations
of the Research 14
Definition of Terms 16
Hypotheses 18
.Methodology 19
Data Analysis 20
Summary 21
TWO REVIEW OF THE LITERATURE 22
Introduction 22
Constructs of Learning Style and
Psychological Type 22
Learning Styles and the Learning
Environment 24
Choice of Instruments for the Research 27
Kolb's Learning Style Inventory .... 28
Kolb-McCarthy Learning Styles Inventory 31
VI


TABLE OF CONTENTS
PAGE
Research on the Learning Styles
Inventory 32
Jung's and Myers' Theories
of Psychological Types 41
Myers-Briggs Type Indicator 45
Comparison of the LSI and MBTI .... 64
Summary 65
THREE METHODOLOGY 67
Population 67
DVST 1012, Learning Skills 66
Learning Skills Assessment 71
Asessment of Learning Styles
and Psychological Type 73
Selection of the Population to Study 76
Selection of Independent and Dependent
Variables 76
FOUR DATA ANALYSIS 86
Population 86
Success and Failure Analysis 92
Analyses of Additional Independent
Variables 98
Analyses of Dependent Variables .... 108
FIVE SUMMARY 160
Introduction 160
Discussion 163
Recommendations 185
vi L


TABLE OF CONTENTS
APPENDICES PAGE
A ATTITUDES AND FUNCTIONS BY TYPE 189
B ACCURACY AND RELEVANCE OF STYLE AND TYPE 190
C TITLES OF COURSES CHOSEN FOR ANALYSIS . 196
D MEASURES OF CENTRAL TENDENCY 197
REFERENCES 19 9
BIOGRAPHICAL SKETCH 204
viii


LIST OF TABLES
TABLE PAGE
I-I High-Risk CoursesFine Arts 7
1-2 High-Risk CoursesHumanities 8
1-3 High-Risk CoursesMatura 1 Sciences 9
1-4 High-Risk CoursesSocial Studies 10
2-1 LSI Undergraduate Scores 35
2-2 Distribution of Learning Styles
for Chicago High School Students 37
2-3 Comparison of Learning Style Instruments . 42
2-4 The Sixteen Psychological Types 47
2-5 Distribution of Type for Combined Samples of
11th and 12th Grade High School Students . 49
2-6 Distribution of Preference for Combined Samples
of 11th and 12th Grade High School Students 50
2-7 MBTI Compared with the Alport-Vernon-Lindsey
Study of Values, the Edwards Personality
Preference, and the Personality Research
Inventory 53
2-8 College Students' Perception of Type .... 63
3-1 College Distribution foe Students in the Study 69
3-2 Disciplines, Departments, and Courses Chosen
for Analysis 83
3-3 Order of Entry for Independent Variables . 84
4-1 Age Distribution for Students in the Study 87
4-2 ACT Scores for Students in the Study .... 89
4-3 High School Size and Rank in Class 90
ix


LIST OP TABLES
TABLE PAGE
4-4 Comparison of Self-Reported and Actual HSGPA 91
4-5 Successful and Unsuccessful Attempts
for all Courses 93
4-6 Successful and Unsuccessful Attempts
in the Four Core Disciplines 9 4
4-7 Successful and Unsuccessful Attempts
in Selected Departments 96
4-8 Successful and Unsuccessful Attempts
in Selected Courses 97
4-9 Learning Styles for Students in the Study . 100
4-10 Cumulative Grade Point Averages
for the Four Learning Styles 101
4-11 MBTI TypesMales 102
4-12 MBTI TypesFemales 103
4-13 MBTI TypesTotal Population 104
4-14 Rank Order Comparison of Predicted and Actual
Achievement 107
4-15 Academic Status at the End
of the Freshman Year 110
4-16 Final Parameter Estimates
For the Dependent Variable Academic STATUS 112
4-17 Final Parameter Estimates
For the Dependent Variable CUMGPA 115
4-19 Final Parameter Estimates
For the FINE ARTS Discipline 118
K


LIST OF TABLES
TABLE PAGE
4-19 Final Parameter Estimates
For the HUMANITIES Discipline 119
4-20 Final Parameter Estimates
For the NATURAL SCIENCES Discipline .... 120
4-21 Final Parameter Estimates
For the SOCIAL STUDIES Discipline 121
4-22 Final Parameter Estimates
For the FNAR Department 123
4-23 Final Parameter Estimates
For the COMM Department 124
4-24 Final Parameter Estimates
For the ENGL Department 125
4-25 Final Parameter Estimates
For the HIST Department 126
4-26 Final Parameter Estimates
For the BIOL Department 128
4-27 Final Parameter Estimates
For the GEOL Department 129
4-28 Final Parameter Estimates
For the MATH Department 130
4-29 Final Parameter Estimates
For the PLSC Department 131
4-30 Final Parameter Estimates
For the PSYC Department 133
4-31 Final Parameter Estimates
For the SOCI Department 134
xi


LIST OF TABLES
TABLE PAGE
4-32 Final Parameter Estimates
For the GEOG Department 135
4-33 Final Parameter Estimates cor COMM 1302 . 137
4-34 Final Parameter Estimates for ENGL 1003 . 138
4-35 Final Parameter Estimates for ENGL 1023 . 139
4-36 Final Parameter Estimates for HIST 2003 . 140
4-37 Final Parameter Estimates for BIOL 1004 . 142
4-38 Final Parameter Estimates for GE0L 1114 . 143
4-39 Final Parameter Estimates for MATH 1203 . 144
4-40 Final Parameter Estimates for PLSC 2003 . 145
4-41 Final Parameter Estimates for SOCI 2013 . 147
4-42 Final Parameter Estimates for FNAR 1062 . 148
4-43 Final Parameter Estimates for COMM 1313 . 149
4-44 Final Parameter Estimates for ENGL 1013 . 150
4-45 Final Parameter Estimates for MATH 1033 . 151
4-46 Final Parameter Estimates for PSYC 2003 . L53
4-47 Summary of Regressors for STATUS and CUMGPA 154
4-48 Summary of Regressors for Disciplines and
Departments 155
4-49 Summary of Regressors for Courses 156
4-50 Summary of Independent Variables Found
as Regressors 157
5-1 Reference List of Terms and Definitions 167
B-L Perception of Style and Type L91
B-2 Actual and Predicted Learning Style 192
B-3 Actual and Pradicted Type 194
xii


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
PREDICTIMG ACADEMIC PERFORMANCE OF UNDERPREPARED
FRESHMEN WITH HIGH SCHOOL GPA, ACT SCORES,
LEARNING STYLES, PSYCHOLOGICAL TYPE,
AND LEARNING SKILLS
By
ROBERT L. MOORE
August, 1985
Chairman: Dr. Gordon Lawrence
Major Department: Educational Leadership
The problem examined was how to better predict, for
underprepared college freshmen, academic performance in core
curriculum coursework, freshman-year grade point average, and
the resulting academic status. The Kolb-McCarthy Learning
Style Inventory (LSI), the Myers-Briggs Type Indicator
(MBTI), and a locally-developed Learning Skills Assessment
(LSA) were used to assess 171 students in a learning skills
class. Students' high school grade point averages and ACT
scores were also available. From this group, 128 entering
xi ii


freshmen without prior college experience were identified as
the study population.
There were 31 dependent variables selected for analysis:
academic status and grade point average at the end of the
freshman year; 4 core-curriculum disciplines (Fine Arts,
Humanities, Natural Sciences, and Social Studies); and 11
departments and 14 courses from those disciplines. These
dependent variables were used to determine if predictability
of academic success would be improved when the LSI, MBTI, and
LSA were added to regression equations containing high school
grade point averages and ACT scores.
It was hypothesized that high school grade point
averages and ACT scores were insufficient predictors of
academic success and that the additional independent
variables (LSI, MBTI, and LSA) would significantly improve
predictability. High school grade point averages were found
to be predictive in 39% of the 31 regression equations, and
ACT scores were found to be predictive in 42% of the
equations. The LSI significantly improved 29%, the MBTI 48%,
and the LSA 22% of the equations. Most regressors appeared
in expected directions, but several anomalous results led to
recommendations of replication with a larger sample of
underprepared students and a sample of all entering freshmen.
Of particular note was the lack of predictive power of
reflective observation and abstract conceptualization from
the LSI and sensing and intuition from the MBTI. These
findings were inconsistent with other research on these two
xiv


instruments, suggesting that this group o£ underprepared
students may have differed in important ways from college
students not considered underprepared. Cautious use of the
LSI and MBTI for advising was recommended, but the LSA was
found to be inadequate for prediction.
xv


CHAPTER ONE
INTRODUCTION
The Problem
High school grade point average and standardized
assessment, such as the American College Test (ACT) or the
Scholastic Aptitude Test (SAT), are commonly used to predict
academic success in college, and they are often used as
screening devices when admitting, advising, and placing
students. Yet, even after high school grade point averages
and standardized assessments have been used for prediction,
screening, advising, and placement, many students fail to
achieve academic success during their first year in college.
The early college record for such students is characterized
by very low freshman grade point averages and a resulting
academic standing of probation, suspension, or withdrawal
from college.
Upon closer examination, the lack of success during the
freshman year is often attributable to poor grades in certain
"high-risk" core curriculum courses. If one accepts the
notion that grades of "A," "B," or "C" are considered
successful completion of a course and that grades of D,"
"F," "W" (withdraw), and "I* (incomplete) are considered
unsuccessful completion, then high-risk courses can be
defined as those with a high rate of unsuccessful completion.
1


2
For the purposes of the present research, a course in which
30% or more of all freshman students enrolled receive grades
of "D," "F," "W," or "I" will be considered a high-risk
course. (See Blanc, Debuhr, and Martin, 1983, for a
rationale for using a 30% rate.) Students who are not
prepared to be placed in such high-risk courses, yet who are
advised to take one or more of them during their freshman
year, may suffer low grade point averages and academic
failure.
The question to be investigated by the present research
is: How may advisors and others better predict success or
failure in high-risk core-curriculum coursework, freshman-
year grade point average, and resulting academic status by
examining factors in addition to high school grade point
average and standardized (ACT) assessment?
Background for the Problem
General
If the present national trend of tightening academic
standards and the closing of the "open door" continues,
coupled with a decreasing pool of eligible, traditional-age
college students, colleges and universities will face
increasing problems of maintaining enrollments to meet
financial obligations. Retention of students under such
conditions is becoming increasingly important, and students
who are not prepared to meet higher standards pose a special
problem. Maxwell (1979) has asserted:
(0)nderprepared students will not disappear from college
classrooms, nor can most colleges expect to restrict
admission to the best preparedthere are too few of


3
them. . (I)t is clear that colleges must continue to
to offer comprehensive and intense academic support
services to their students, (p. 25)
Popular national opinion is focusing on basic skills
preparation (or, more accurately, the lack of it). Concern
is also being expressed in the academic community. In a
recent study conducted by the City University of New York
(reported by Nielsen and Polishook, 1984), 85% of the 1,269
institutions responding to a survey of every American college
and university reported that inadequate preparation of their
entering freshmen was a common problem. By contrast, only
three percent of the responding institutions did not perceive
poor academic foundations to be a serious problem. The
responding institutions further reported that basic skill
deficiencies were found in reading (28% of the freshmen
students), writing (31%), and basic mathematics (32%). It is
not surprising that 80% of the reporting institutions,
ranging from open-door, two-year colleges to the most
selective universities, stated that they offer remedial
courses in basic skills.
Academic success in college is a result of many
factors and their interactions, such as, skills preparation
(basic skills, study skills, and thinking skills), personal
and social adjustment, perception of college, attitude and
motivation, personal values, academic standards of the
institution, quality of teaching, learning style preference,
the match between teaching and learning styles, personality


4
type, academic advising and guidance, hours taken, hours
employed, placement in the course sequence, balance between
freedom and responsibility, environmental setting, peer and
familial influence, relationship to faculty, goal and career
orientation, financial support, and extracurricular
activities. Conversely, Maxwell (1979) has categorized
student characteristics which might lead to academic
failure in college: lack of potential, inadequate
conception of the work involved in succeeding, importance of
other activities over study, interference from psychological
problems, failure to assume responsibility for one's own
learning, inhibition of language functions (poor reading,
writing, and speaking skills), lack of understanding of
standards for high-quality performance, selection of
inappropriate major, vagueness about long-term goals, and
selection of wrong college.
An attempt to list success or failure factors is
certain to have omissions, and the problem becomes even more
complicated when the possible interrelationships among the
many factors are considered. However, the underprepared (or
"misprepared," Maxwell, 1979, p. 3) college student will
almost certainly exhibit problems in one or more of the above
factors and/or their interrelationships. While the extent
and problematic nature of these factors will certainly vary
by individual, all are clearly important success or failure
variables and all will not be reflected by students' high
school grade point averages and ACT scores.


5
Oniversity of Arkansas at Fayetteville
To help set the stage for the present research, success
statistics for a selected group of Oniversity of Arkansas
at Fayetteville students were examined by the author. For
the 128 entering freshmen enrolled in a learning skills
course in the fall of 1983, only 73.4% were in good academic
standing by the end of that first term. By the end of their
freshman year, that figure had dropped to 58.6%. The
remaining 41.4% were either on academic probation (14.8%),
had been suspended for one year (6.3%), or had withdrawn from
the Oniversity (20.3%).
A large-scale study (Donnally, 1984) of Oniversity of
Arkansas freshmen has substantiated a high rate of academic
attrition. In 1981, the Oniversity began a six-year -
retention study based on the entering freshman class of that
year. By Fall, 1982, only 66% of that group were still
enrolled. By Fall, 1983, 51% were still enrolled, and by
Fall, 1984, only 44% of the original group were still
enrolled. Thus, over a three-year period, an attrition rate
of 56% had reduced the original 2,628 entering freshman
students to 1,156. Further, in Fall, 1984, after three
complete academic years, only 44% of the remaining 1,156
students were classified as seniors, and seven percent of the
students still enrolled were on academic probation.
A more detailed understanding of freshman attrition is
obtained when one examines success (A, B, or C) in the core-


6
curriculum disciplinesFine Arts, Humanities, Natural
Sciences, and Social Studiesat the University of Arkansas.
Tables 1-1 through 1-4, High-Risk Courses, list 53 core
curriculum courses in the four major disciplines listed above
which posted a success rate of 70% or below for entering
freshmen (N = 2,228) during the 1983-84 academic year at
the University of Arkansas. (Only those courses in which at
least 30 entering freshmen were enrolled were selected.) It
can be seen from the tables that courses in which large
numbers of freshmen students are traditionally enrolled are
also ones which have low (70% or below) rates of success.
The overall success rates for the selected courses in the
four disciplines were found to be 65% for fine arts, 65% for
humanities, 54% for natural sciences, and 61% for social
studies.
The University of Arkansas has traditionally been a non-
selective, open-door institution. Any student with a high
school diploma (or equivalent) has been able to enter the
University regardless of his or her high school grade point
average or ACT scores. A student has been placed on academic
probation only if his or her semester grade point average
dropped below a 1.25 (Colleges of Agriculture and Arts &
Sciences) or 1.50 (Colleges of Business Administration,
Education, and Engineering). However, beginning with the
Fall, 1984 term, higher standards for placing students on
probation were put into effect. All freshmen and sophomores
are to be placed on probation if their semester grade point
average falls below a 1.75, and all juniors and seniors are


Table 1-1
High-Risk CoursesFine Arts
7
Course
Title
N
Success
ARCH
1812
Introduction to Architecture
83
70%
ART
1003
Drawing Fundamentals I
66
68
ART
1313
Drawing Fundamentals II
40
70
FNAR
1022
Theatre Arts
56
68
FNAR
1072
Visual Arts
150
63
LARC
1812
Landscape Architecture
55
55
Totals
450
65%
Notes for Tables 1-1 through 1-4:
Tables 1-1 through 1-4 represent all courses in the four
core-curriculum disciplines for which entering freshmen
enrollment was 30 or more and for which the success rate
was 70% or less.
The first digit in the course number indicates the
level of the course, e.g., 1 = freshman, 2 = sophomore,
etc. The last digit in the course number indicates the
credit hours for the course. Thus, ARCH 1812 is a
freshman-level, two-hour course.
The titles for the courses are from the (Jniversity of
Arkansas' college catalogs.
N indicates the number of entering freshmen enrolled in
each of the courses.
Success Rate indicates the percentage of the entering
freshmen who received grades of A, B, or C in each course.
Percentage figures were rounded to the nearest whole
number, and the total percentage for the success rate is a
weighted average for all the courses listed in the
discipline.


8
Table 1-2
High-Risk
Course
ANTH 2023
ENGL 1003
ENGL 1013
ENGL 1102
GERM 1003
HIST 2003
HIST 2013
JOOR 1023
PHIL 1202
PHIL 2003
PHIL 2203
SPAN 1003
WCIV 1003
WCIV 1013
WLIT 1113
See notes
CoursesHumanities
Title
N
Success
Cultural Anthropology
66
65%
English Grammar
433
56
Freshman Composition
1860
70
Reading Development
78
65
Elementary German
64
67
American History, 1492-
-1877
490
65
American History, 1877
-present
504
62
Intro, to Mass Communications
69
59
Reflective Thinking
30
57
Introduction to Philosophy
182
70
Logic
41
68
Elementary Spanish
84
68
Inst. & Ideas of West.
Man I
369
56
Inst. & Ideas of West.
Man II
169
64
Intro, to World Literature
299
65
Totals
4739
65%
on Table 1-1.


Table 1-3
High-Risk CoursesNatural Sciences
9
Course
Title
N
Succes
ASTR
2003
Survey of the Universe
62
50%
BIOL
1004
General Biology
525
60
BIOL
1024
Biological Concepts
54
61
BOTY
1014
General Botany
157
45
CHEM
1094
Chemistry in the Modern World
48
60
CHEM
1104
General Chemistry I
349
60
CHEM
1104
General Chemistry II
216
59
GEOL
1004
Earth Science for Teachers
57
60
GEOL
1114
General Geology
268
64
MATH
1033
Remedial Math (Algebra)
493
33
MATH
1103
Patterns in Mathematics
106
60
MATH
1203
College Algebra
1102
49
MATH
1213
Plane Trigonometry
220
50
MATH
1285
Precalculus Mathematics
196
65
MATH
2043
Survey of Calculus
176
66
MATH
2053
Finite Mathematics
304
67
MATH
2555
Calculus & Analytic Geometry
387
62
PHYS
1023
Physics and Human Affairs
50
56
PHYS
1044
Physics for Architects I
64
56
PHYS
1054
Physics for Architects II
36
61
PHYS
2053
University Physics
44
59
ZOOL
1004
General Zoology
107
49
ZOOL
2443
Anatomy
36
56
Totals
5057
54%
See notes on Table L-L.


10
Table 1-4
High-Risk CoursesSocial Studies
Course
Title
N
Success Rate
ECON
2013
Principles of Macroeconomics
159
49%
GEOG
1003
Physical Geography
94
44
GEOG
1123
Human Geography
243
63
PLSC
1503
Intro, to Political Science
100
64
PLSC
2003
American National Government
501
67
PLSC
2203
State and Local Government
59
54
PSYC
2003
General Psychology
663
58
SOCI
2013
General Sociology
541
66
SOCI
2033
Social Problems
109
63
Totals
2469
61%
See notes on Table 1-1.


LI
to be placed on probation whenever their semester grade point
average falls below a 2.00, although no student will be
placed on probation if his or her cumulative grade point
average is 2.00 or higher.
Further, beginning with the Fall, 1985 term, students
with less than a 2.00 high school grade point average are not
to be admitted to the University, and two classes of
admission are to be enforced: (1) Students with a high
school grade point average below 2.50 and an ACT
composite score below 18 will be admitted conditionally.
(2) Students with a high school grade point average of 2.50
or above or an ACT composite score of 18 or above will be
admitted unconditionally. Students admitted
conditionally must meet rigid academic requirements by the
end of their freshman year or they will not be allowed to
continue at the University. Entering freshmen will also be
expected to have earned high school credits in four years of
English, two years of mathematics, two years of natural
sciences, and two years of social studies. The high school
requirements will become even more rigorous in 1986 and again
in 1988, and any deficiencies in core-curriculum areas must
be cleared by students during their freshman year in college.
Purpose of the Study
The research was designed to determine if success
predictability (at the five levels explained below) for
underprepared entering freshmen is significantly enhanced by
combining additional selected assessment instruments with
high school grade point average and ACT scores in regression


12
formulas. Three additional assessment tools were examined to
determine if they significantly enhanced academic success
predictability:
1. Students' learning style as measured by the Kolb-
McCarthy Learning Style Inventory (LSI);
2. Students' psychological type as measured by the
Myers-Briggs Type Indicator (MBTI); and
3. Students' reading rate and comprehension, listening
comprehension, notetaking skills, and study habits and
attitudes as measured by the Learning Skills Assessment
(LSA). The LSA is locally developed, and its use in the
present research is to be considered exploratory since
verification of the instrument's validity and reliability had
not been undertaken prior to the research.
The five major levels examined in the regression
equations form a hierarchy ranging from the most general to
the most specific academic outcomes and yield 31 dependent
variables:
1. Academic status at the end of the freshman year;
2. Freshman-year grade point average;
3. Success in the four core-curriculum disciplines
(Fine Arts, Humanities, Natural Sciences, and Social
Studies);
4. Success in 11 selected departments within the core
curriculum disciplines; and
5. Success in 14 selected courses within the
departments.


13
It was expected that the research would show that high
school grade point average and ACT scores are necessary but
insufficient predictors of success at all levels of the
hierarchy, but particularly in the high-risk core courses
required of freshmen. The expected findings, then, should
suggest that additional assessment is necessary to better
advise, place, and remediate students before serious academic
problems begin.
The research was an early stage in the development later
of a process model for freshmen, particularly those admitted
conditionally, which involves the student, his or her
advisor, instructors, and the academic support staff:
The student will, through assessment and feedback,
learn more about his or her capabilities and limitations.
Rather than a passive acceptor of recommendations for college
work, the student will become an active, knowledgeable
partner in the initial advising experience.
The advisor will be able to more accurately place a
student in remedial, regular, or advanced sections of core
coursework. He or she will oe better prepared to guide
students to academic support services when needed and will
better facilitate the crucial freshman year for them.
The instructors will be provided with more precise
individual and group data with which to improve their
instructional methodology. By alerting instructors to
characteristics which signal success or failure, they will be


14
more sensitive to early indications of trouble that help
alert them to the need for appropriate action.
The academic support staff will be better able to
program for the needs of all entering students, not just
those flagged by admissions standards, and a closer
realization of student retention will be achieved.
The University has authorized the establishment of an
Academic Development Office (ADO) to aid conditionally-
admitted students and others in academic difficulty. The
author has been asked to design and direct the ADO, and the
findings of the present research will be used to help design
the assessment, feedback, advising, remediation, and
monitoring components of that office.
Assumptions and Delineations of the Research
At the time the study was initiated, an intact group of
conditionally-admitted and course-deficient students (as
defined by the new admissions standards described above) did
not exist at the University. However, as will be explained
more fully in a later section, a group of students was chosen
which, for the most part, were considered to be underprepared
for college. There was not an intent to choose a
representative sample of the the entire entering freshman
class, since an underlying assumption of the research was
that mispredicting academic success is particularly impactful
on underprepared students. However, while the research and
the findings are specific to the study population and the
University disciplines, departments, and courses under
investigation, the implications of the findings will be


15
useful in other settings. To the extent that other
institutions are under pressure to selectively admit students
and to administer scarce support resources, the findings will
suggest similar attention to early warning signs of possible
academic difficulty, particularly for underprepared students,
and should assist them also in building cost-effective models
of selection, assessment, feedback, advising, placement, and
supportive services. Background and demographic
characteristics of age, sex, high school size, rank in high
school, and the initial college selected, as well as a
description of the research setting, are provided to help
other researchers determine generalizability and the need for
replication.
Academic support programs are typically designed and
implemented following the traditional process/product methods
of assessment, prescription, remediation, advising, and
support because it "seems to work." (See Moore, 1981.) New
models of designing and evaluating developmental programs
need to employ theoretical research to "provide practitioners
with a systematic, predictable method for determining
[program] value and making value decisions" (p. 48). Of
particular concern in the present research are the
theoretical notions of learning styles, psychological type,
and basic and study skills. Specifically, the research will
show how these variables may help better predict academic
success for underprepared students. While the outcome of the
research will not be the actual design of an academic support
program based upon learning style, psychological type, and


L6
basic and study skills, it is assumed that the findings will
aid in the establishment of such design.
Definition of Terms
The following terms are defined for use in the research,
and they will be more fully explained in later sections:
LSI: Kolb-McCarthy Learning Style Inventory
ACCE: Perceiving Dimension
AC: Abstract Conceptualization Scale
CE: Concrete Experience Scale
AERO: Processing Dimension
AE: Active Experimentation Scale
RO: Reflective Observation Scale
Style
I
(Divergers):
CE
and
RO
Style
II
(Assimilators):
AC
and
RO
Style
III
(Convergers) :
AC
and
AE
Style
IV
(Accommodators):
CE
and
AE
MBTI: Myers-Briggs Type Indicator
El Dimension
E: Extraverted attitude
I: Introverted attitude
SN Dimension
S: Sensing function
N: Intuitive function
TF Dimension
T: Thinking function
F: Feeling function


17
JP Dimension
J: Judging attitude
P: Perceiving attitude
MBTI Type: One of 16 possible four-letter
combinations:
ISTJ
ISFJ
INFJ
INTJ
ISTP
ISFP
INFP
INTP
ESTP
ESFP
ENFP
ENTP
ESTJ
ESFJ
ENFJ
ENTJ
Combined Types: Two- or three-letter
combinations
implying
two or more
types,
i.e., EST-
implies
ESTJ and ESTP,
and IN
implies INFJ
, INFP,
INTJ, and
INTP.
LSA: Learning Skills Assessment (locally developed)
RATE: LSA Reading rate
COMP: LSA Comprehension score
READ: LSA Textbook reading score
LISTEN: LSA Listening score
NOTES: LSA Notetaking score
STUDY: LSA Study Skills score
ACT: American College Test
ACTC: ACT Composite
ACTE: ACT English
ACTM: ACT Mathematics
ACTS: ACT Social Sciences subscore
ACTN: ACT Natural Sciences subscore
HSGPA: High school grade point average
STATUS: Academic status at the end of the freshman year


18
CUMGPA: Cumulative grade point average at the end of the
freshman year
The core-curriculum disciplines, departments, and
courses, are operationally defined as they are used in the
research. Chapter Two, Review of the Literature, provides a
detailed description of the LSI and MBTI. Chapter Three,
Methodology, provides an operational definition of the LSA.
Hypotheses
There are five research hypotheses, and they relate the
major independent variables (Learning Style Inventory (LSI),
Myers-Briggs Type Indicator (MBTI), and Learning Skills
Assessment (LSA)) to the dependent variable hierarchy
(STATUS, CUMGPA, and the core-curriculum Disciplines,
Departments, and Courses). The five hypotheses are:
A regression equation which uses high school
grade point average and ACT scores to predict STATUS at the
end of the freshman year will be significantly improved with
the addition of scores from the Learning Styles Inventory,
Myers-Briggs Type Indicator, and Learning Skills Assessment
to the equation.
H2: A regression equation which uses high school
grade point average and ACT scores to predict CUMGPA at the
end of the freshman year will be significantly improved with
the addition of scores from the Learning Styles Inventory,
Myers-Briggs Type Indicator, and Learning Skills Assessment
to the equation.
A regression equation which uses high school
grade point average and ACT scores to predict success in the


19
four selected core-curriculum disciplines will be
significantly improved with the addition of scores from the
Learning Styles Inventory, Myers-Briggs Type Indicator, and
Learning Skills Assessment to the equation.
H^: A regression equation which uses high school
grade point average and ACT scores to predict success in the
11 selected core-curriculum departments will be
significantly improved with the addition of scores from the
Learning Styles Inventory, Myers-Briggs Type Indicator, and
Learning Skills Assessment to the equation.
A regression equation which uses high school
grade point average and ACT scores to predict success in the
14 selected core-curriculum courses will be significantly
improved with the addition of scores from the Learning Styles
Inventory, Myers-Briggs Type Indicator, and Learning Skills
Assessment to the equation.
Methodology
One hundred seventy-two students enrolled in the 10
sections of a learning skills class (DVST 1012) in the Fall,
1983 term at the University of Arkansas, Fayetteville, were
assessed using the Kolb-McCarthy Learning Style Inventory
(LSI), the Myers-Briggs Type Indicator (MBTI), and a
locally-developed Learning Skills Assessment (LSA). The
results of the LSI and MBTI were provided to students by the
investigator in their classroom groups, and the results of
the LSA were provided to students in individual feedback
sessions by their classroom instructors.


20
Osing the University of Arkansas' On-line Administrative
Student Information System (OASIS) and the Statistical
Analysis System (SAS) to determine core-curriculum
enrollments from the population under study, 4 disciplines,
11 departments, and 14 courses were chosen for analysis. To
ensure a sufficient N for the study, only those
disciplines, departments, and courses in which at least 20
enrollments from the study population occurred were chosen.
The selected core-curriculum disciplines, departments and
courses, along with freshman-year grade point average and
resulting academic status, became the focus of the research.
From the group of 172 students who received the initial
assessment, 128 entering freshmen without prior college
experience were selected as the target population for the
research. The three major independent variables (LSI, MBTI,
and LSA) and their subcomponents were introduced into
stepwise regression formulas along with HSGPA and ACT
composite and subscores to test the research hypotheses.
Chapter Three, Methodology, contains the research procedures
in greater detail.
Data Analysis
The data were analyzed using a logistical regression
analysis procedure, LOGIST, run under the Statistical
Analysis System (SAS) at the University of Arkansas Computing
Center. There were 30 independent variables (LSI, MBTI, LSA,
and their subcomponents) and 31 dependent variables (STATUS,
CUMGPA, and 4 core-curriculum disciplines, 11 departments,
and 14 courses). A stepwise regression analysis was


21
performed for each of the 31 dependent variables to determine
which and how many of the 30 independent variables
contributed significantly to the regression model variance.
Since there was a large number of independent variables, and
because the loss of degrees of freedom was a concern, the
independent variables were introduced into the model as
possible regressors in small sections, no more than four new
variables at a time. The variables which remained in the
model as regressors at the end of each run were retained as a
part of the possible regressor pool for the next run. A test
of model "adequacy of fit" (provided by the LOGIST program)
was performed after all the independent regressors were
identified for a particular dependent variable. Chapter
Four, Data Analysis, provides a more detailed description of
the analyses employed.
Summary
Academic success in college is dependent upon many
factors and their interrelationships, and success is not
easily or accurately predicted from high school grade point
averages and ACT scores alone. The present research was
designed to determine if success predictability for
underprepared students can be significantly enhanced by
adding measures of learning style, psychological type, and
learning skills to high school grade point average and ACT
scores in regression formulas. The research will provide the
basis for the later development of a process model to aid in
assessing, remediating, and monitoring entering underprepared
college freshmen.


CHAPTER TWO
REVIEW OF THE LITERATURE
Introduction
The Review of the Literature begins with a brief
overview of the "Constructs of Learning Style and
Psychological Type" and "Learning Styles and the Learning
Environment" to provide theoretical and practical bases for
the section which follows on "Choice of Instruments for the
Research." The remainder of the chapter is devoted to the
theoretical bases for, a description of, the research on, and
a comparison of the Learning Style Inventory (LSI) and the
Myers-Briggs Type Indicator (MBTI). Research data do not
exist on the Learning Skills Assessment (LSA), and that
instrument is described operationally in Chapter Three,
Methodology.
Constructs of Learning Style and Psychological Type
Davies (1981) classified learning styles constructs as
theoretical (from a specific two-dimensional psychological
orientation), response-based (from empirical studies of
learning behavior), and integrated (from a range of sources
including learning theory, developmental theory, observation,
and analysis). He described theoretical constructs of
learning style by citing three examples of bi-polar
psychological theories. In the first of these theories he
cited research on two types of individuals: field-dependent
22


23
(viewing the world in a global, gestalt way) and field-
independent (viewing the world in an analytic, detached way).
A second two-dimensional theoretical approach cited by Davies
involves perceptive learners (those who focus on clues in the
data, examine relationships, and jump from part to part of
the material they are trying to study) and receptive learners
(those who focus on details in a logical order, avoid
judgement by preconceived ideas, and wait to get all the data
before reaching conclusions). Davies' third two-dimensional
theoretical approach involves two ways of choosing between
alternatives: impulsive and reflective.
Davies' second major classification of learning styles
constructs, described as response-based, are empirically-
observed notions of how students learn. As an example of
such studies, he cited research on observations of classroom
learning behaviors and the resulting categories: compliant,
anxious-dependent, discouraged workers, independent heroes,
snipers, attention seekers, and silent types. A second
example of response-based learning styles cited by Davies was
research on Oniversity of Chicago students who were
categorized as authoritarian, anti-authoritarian, or rational
types.
The integrated approaches to constructs of learning
styles, and the final major classification cited by Davies,
are: Hill's Cognitive Style Interest Inventory (symbols of
meaning, cultural determinants, modalities of inference, and
modes of memory), Kolbs Learning Style Inventory (concrete
experience, reflective observation, abstract


24
conceptualization, and active experimentation), and the
Myers-Briggs Type Indicator (extravert-introvert, sensing-
intuitive, thinking-feeling, and judging-perceiving) .
Lawrence (1984b) asserted that "the term 'learning
styles' is used variously and loosely in educational
literature" (p. 7), and he broadly applied the term to
encompass four aspects of psychological makeup:
1. Cognitive style in the sense of preferred or
habitual patterns of mental functioning:
information processing, formation of ideas, and
judgements.
2. Patterns of attitudes and interests that influence
what a person will attend to in a potential learning
situation.
3. A disposition to seek out learning environments
compatible with one's cognitive style, attitudes,
and interests and to avoid environments that are not
congenial.
4. Similarly, a disposition to use certain learning
tools and avoid others, (p. 7)
Learning Styles and the Learning Environment
While many forms of imparting learning have been
identified (such as, independent study, laboratory methods,
mediated instruction, personalized systems of instruction,
traditional lecture methods, seminars, peer tutoring,
computer-assisted instruction, discussion groups, programmed
instruction, discovery learning, etc.), no single method is
"best" because of the individual differences learners
possess. An identification of the preferred ways of
perceiving and processing information, a construct of
learning according to Kolb (1976), then, seems to be an
important first step in the learning process. Students
usually cannot exert much control over the instructional
methodology used in college courses, but helping them to


25
recognize their preferences for perceiving and processing
information will aid in their understanding of why they learn
more in some subjects and with some methods than others.
In an examination of instructional versus learning
styles (using the Canfield Instructional Style Inventory and
the Canfield Learning Style Inventory), Efurd (n.d.) found
that Westark Community College (Arkansas) students in speech,
anatomy, and physiology classes demonstrated the following:
male instructors and male students matched teaching and
learning styles more often than any other pairing; male
students were more competitive than females; male students
preferred working with peers more than female students; male
students preferred contact to be qualitative; females
preferred inanimate contact; male students preferred reading
more than female students; and instructors believed that
changing instructional methods can create positive
differences in learning.
In an interview with Boy Ian (1981), Canfield reported
that research on any one technique of matching teaching and
learning styles is going to be inconclusive as long as a
"homogeny of students" (p. 25) and their attendant individual
styles exist in a particular learning situation. However,
Boylan reported Canfield as saying that students who do
receive preferred treatment tend to perform better in the
classroom, and that matching of teaching to learner styles
does enhance learning. In that same interview, Canfield
asserted that, based upon work done in achievement motivation


26
at some community colleges, it was possible to change
learning styles to achieve academic success.
Based upon observations, interviews, and experimental
studies over a decade, Dunn and Dunn (1979) offered the
opinion that "regardless of their age, ability, socioeconomic
scatus, or achievement level, individuals respond uniquely to
their immediate environment" (p. 239). Citing research on
matching teachers and learners, they reported significant
improvement in both achievement and motivation when matching
occurs. Further, they asserted that students are able to
accurately predict the modality in which they could best
achieve the desired performance. Also, according to Dunn and
Dunn, when students are taught by the method they predicted
was best for them, they score higher on tests, fact
knowledge, attitude, and efficiency of work than students
taught by methods dissonant with their preferences. However,
they further reported that "(m)ost teachers can respond to
differences in students' learning styles. That is preferable
to trying to match students with teachers" (p. 238).
Commenting on Hill's Cognitive Style Mapping, Maxwell
(1979) cited cost, time, instructor incentive and energy,
training difficulties, traditional classroom methods, and
publisher resistance as obstacles to attempts to match
teaching and learning styles. Significantly for the present
research, Davies (1981) asserted that "(i)f the goal is
developmental, where learning to learn and individual
development are essential, then matching may be
inappropriate" (p. 4).


27
Bernice McCarthy, co-author of the Kolb-McCarthy
Learning Styie Inventory, in an interview with Leflar (1982),
reported that in her early research she found that when
students' Learning styles were reinforced during part of the
day the reinforcement carried over into the rest of the day
when styles were not matched. However, McCarthy (1980a)
elsewhere stated: "(A)ny 'matching' operation in a school
necessitates labels, and we already have too many labels in
education now. Do we need more?" (p. 84). Further, grouping
and labeling students with learning styles, and teaching to
those styles, "would be even more stultifying than the old IQ
groupings and trackings" (p. 29).
While there may be disagreement on the advisability of
matching teaching and Learning styles, there is utility in
helping both the instructor and student understand the
Learning process. HilL, Canfieid, Kolb, Dunn, and McCarthy
have all stressed the importance of gaining such an
understanding. (See Boylan, L981; Davies, 1981; Dunn, L981,
1983; Dunn and Dunn, 1979; Kolb, 1976, 1980, 1981, 1984;
Leflar, 1982; McCarthy, 1980a, 1980b; and Mentkowski, 1981.)
Choice of Instruments for the Research
Of the various learning styles constructs described in
the above categorization by Davies, the integrated approach
has appeal because of the sources from which the construct is
developed. The complex notion of learning styles is, in this
researcher's opinion, best derived by integrating learning
theory, theories of human personality and development,
observation in learning settings, and analyses of the


28
interrelationships among these factors. Two of the
integrated approaches cited by Daviesthe Kolb Learning
Style Inventory (LSI) and the Myers-Briggs Type Indicator
(MBTI)were selected for the present research because they
provide the necessary integration, theory, observation, and
interrelationships. (A slightly modified version of the LSI,
the Kolb-McCarthy Learning Style Inventory, was used to
assess students in the study. The Kolb-McCarthy LSI is
described in a later section of this chapter.)
Both the LSI and MBTI are grounded in Jungian theory of
psychological type, the MBTI more faithfully so, and thus
satisfy the need to examine human personality and
development. Both were derived from thousands of
observations in learning settings and thus have empirical
validity. Considerable research on the two instruments has
demonstrated practical applications of Jung's theories of
type and has provided analyses of learning theory and the
integrated construct of learning styles. The following
sections describe the LSI and MBTI, cite relevant research on
the two instruments, and provide comparisons with other
learning styles instruments where appropriate to confirm
validity.
Kolb's Learning Style Inventory
Kolb's Learning Style Inventory (LSI) is an assessment
of a person's preferred modes of perceiving (from concrete
to abstract) and processing (from reflective to active)
information. The underlying theory is


29
a dialectic one, founded on the Jungian . concept of
styles or types . and experiential learning grounded
in the . intellectual origins of Kurt Lewin in the
'40's and the sensitivity and laboratory education work
of the '50's and '60's. [At] the core of the model is a
simple description of the learning cycle, or how
experience is translated into concepts which in turn are
used as guides in the choice of new experience. (Kolb,
1976, p. 2).
Kolb has thus combined personality type (Jung), learning
theory (Lewin), and empirical observation into a unified
construct of learning style.
The determination of preference on each of the two
dimensions (perceiving and processing) results in an
identification of an individual's relative emphasis on four
learning abilitiesConcrete Experience (CE), Reflective
Observation (RO), Abstract Conceptualization (AC), and Active
Experimentation (AE)plus two combination scores that
indicate the extent to which an individual perceives
information abstractly or concretely (ACCE) and the extent to
which an individual processes information actively or
reflectively (AERO).
There are four responses, which the learner is asked to
rank order, to each of nine stem items on the LSI. These
responses correspond to the four end points on the two
dimensions. When the combination scores are computed and
'mapped," an individual learning style emerges. (See Figure
2-1, Kolb's Learning Styles.) These four styles are
described below:
Style I: Preference for CE and RO
Kolb has labeled this type learner the Diverger. He
or she has strength in "imaginative ability," "ability to


30
Concrete Experience (CE)
Accommodator
Diverger
Active
Experimentation
(AE)
IV
I
III
II
Reflective
Observation
(RO)
Converger
Assimilator
Abstract Conceptualization (AC)
Figure 2-1
Kolb's Learning Styles


3L
view concrete experiences from many perspectives," and the
"ability to organize many relationships into a meaningful
'gestalt'" (1976, p. 5).
Style II: Preference for AC and RO
The Assimilator has strengths in "the ability to
create theoretical models," "inductive reasoning," and "the
ability to assimilate disparate observations into an
integrated explanation" (p. 6).
Style III; Preference for AC and AE
The Converger has his or her greatest strength in
"the practical application of ideas" (p. 5).
Style IV: Preference for CE and AE
The Accommodator has strengths in "doing things,
carrying out plans and experiments, and involving himself in
new experiences" (p. 6).
Kolb-McCarthy Learning Styles Inventory
McCarthy (1980a) with David Kolb, Paul Torrance, and
others combined the Kolb Learning Style Inventory and the
Torrance assessment of hemispheric preference into a two-part
assessment she called the 4MAT Survey Battery. Part One of
4MAT is referred to as the Kolb-McCarthy Learning Style
Inventory and is the version used in the present research.
The Kolb-McCarthy LSI is faithful to Kolb's construct of
learning style and modifies the original Kolb LSI only by
putting the response items into a sentence completion form
rather than single-word choices. All research cited below is
based upon the earlier Kolb LSI unless specifically
designated as Kolb-McCarthy or 4MAT.


32
In an interview with Leflar (1982b), McCarthy asserted:
The importance of the 4MAT system is not deciding what
the individual's learning style is, but rather the
purpose is to help the teacher to become more skilled in
[teaching] to all learning styles. Thus the cycle of
learning which Kolb developed is a natural cyclical
progression moving through all four learning styles.
[Teaching "around the circle" lets students "shine some
of the time during their learning, but to] also move
away from their natural preferences some of the time to
acquire new skills and stretch their abilities, (p. 17)
Research on the Learning Styles Inventory
Item Analysis
Kolb (1976) showed in an item analysis of the LSI for
287 managers and management students that none of the
possible 36 choices correlated less than .45 with the
appropriate scale total, and most correlates fell between .50
and .60. Further, choices on a particular scale correlated
negatively with the theoretical opposite (e.g., CE choices
correlated negatively with the AC scale total). Also, no
significant correlations were found between choices and their
theoretically orthogonal scales (e.g., RO choices did not
significantly correlate with the CE or AC scale totals).
These data indicate that the item choices on the four LSI
scales (CE, RO, AC, and AE) have high convergent and
discriminant validity.
Intercorrelation of LSI Scales
Kolb (1976) showed that for a sample of 807 people CE
and AC were negatively correlated (-.57, p < .001), and RO
and AE were also negatively correlated (-.50, p < .001).
Orthogonal correlations were low but significant because of
the large sample size (CE with RO, .13; RO with AC, -.19; AC


33
with AE, -.12; and AE with CE, -.02). All correlations but
AE/CE were significant at p < .001. Because of the
intercorrelation data, Kolb justified the creation of two
combination scores to measure continuous dimensions (ACCE and
AERO). With the ACCE dimension, AC correlated .90 and CE
correlated -.85. With the AERO dimension, AE correlated .85
and RO correlated -.84.
ReliabilityTest-Re test
Kolb (1976) pointed out that since the four basic
learning inodes assessed by the LSI are theoretically
interdependent, any action, including responding to the test,
is determined in varying degrees by all four learning modes.
Responses to the choices indicating preference will be
variable according to the individual's interpretation of the
situation presented. Further, since there are few
theoretically "pure types" (p. 12), reliability will be
dependent upon the extent a person has attained a preferred
style. Retesting will vary to the extent the individual has
approached or moved away from his or her stated preference.
Because of this test-retest problem, Kolb cautioned that the
LSI will be of limited use for assessment and selection of
individuals "without additional detailed knowledge of the
person and his situation" (p. 13). With these cautions in
mind, Kolb applied testretest assessments to four groups who
ranged in discontinuity from three to seven months. The
combined scores showed a high correlation between test-retest
on the continuous scales (ACCE = .91; AERO = .71). The
individual scales showed similarly high test-retest


34
correlations, with the exception o f CE which reached a
correlation of only .48.
ReliabilitySplit-Half
Kolb (1976) used the Spearman-Brown formula between
halves of the LSI for five different groups (total N =
690). Correlations of approximately .80 were consistent
across all five samples for the combination scores, but
somewhat less satisfactory for the individual scales, perhaps
due to the shortness of the scales. From the split-half
studies, Kolb concluded that the continuous scales were
highly reliable indices suitabLe for most research
applications. The greater variability in the individual
scales suggested greater caution.
LSI Population Data and Applications
Table 2-1, LSI Undergraduate Scores, is a summary of
scores for five selected undergraduate populations supplied
to Kolb (1976) by other researchers. All populations in that
summary demonstrated a preference for Style I, Divergers,
with the Lesley female undergraduates showing the strongest
preference for that style.
Kolb (1976), after examining data from a sample of
practicing managers and graduate students in management,
identified a correspondence between LSI styles and
undergraduate academic specialization:
Divergers: History, Political Science, English, and
Psychology.


35
Table 2-1
LSI Undergraduate Scores
School N CE
Kent St.a
135
14.9
MITb
342
14.8
0. Mass.0
284
14.5
Lesley^
66
L6.2
Alvernoe
213
15.3
Combined
1040
14.9
RO
AC
AE
13.8
17.2
16.0
13.6
17.4
15.0
14.7
17.0
15.7
14.4
16.0
15.0
14.7
15.6
15.7
14.2
16.8
15.5
Undergraduate population
^Seniors only
Q
Engineering undergraduates
^Female undergraduates
0
Liberal arts females
Style Preference
(Diverger)
(Diverger)
(Diverger)
(Diverger)
(Diverger)
(Diverger)


36
Assimilators: Economics, Mathematics, Sociology,
Chemistry, and Physics.
Convergers: Nursing and Engineering.
Accommodators: Business.
McCarthy (1980a) administered Kolb's Learning Style
Inventory to 329 Chicago high school students (ages 17-18;
183 females, 146 males) to determine their learning styles
and found that approximately equal percentages of females and
males fell into each of the four quadrants. Her findings are
shown in Table 2-2, Distribution of Learning Styles for
Chicago High School Students. She further reported that at
this age, students tended to favor the Concrete Experience
scale (60% for CE as opposed to 40% for AC) and that students
slightly favored the Reflective Observation scale (57% for RO
as opposed to 43% for AE). McCarthy reported that her
findings on the processing dimension (AERO) conflicted with
Kolb's findings "who has reported a more active orientation
in the age group 16-35 and then a tapering off toward a more
reflective orientation in later years" (p. 81).
In examining the results of combined learning styles
studies over several years, McCarthy (1980b) expressed
concern that schools teach primarily to one style learner,
the Assimilator. Since her data indicated that only
approximately 28-30% of the general population may be
Assimilators, she cautioned that 70% of the students may not
be getting the education best suited to their abilities.


37
Table 2-2
Distribution of Learning Styles for Chicago High School
Students
Females (%)
Styles
Males
(%)
Total
(%)
Divergers
59
(32)
56
(38)
115
(35)
Assimilators
42
(23)
29
(20)
71
(22)
Convergers
35
(19)
24
(16)
59
(18)
Accommoda tors
47
(25)
37
(25)
84
(25)
183
(100)
146
(99)
329
(100)


38
Mentkowski (1981) administered the Kolb LSI to 679 women
who entered a two-year nursing program at Alverno College in
a longitudinal study to determine the effect of the college
experience on learning styles. The women were either
"weekday" students (n = 412, average age = 22) or
"weekend," and thus considered nontraditional, students
(n = 267, average age = 33). Entering women in both
groups were similar in their overall preference for style
(Divergers), but entering weekend women had a significantly
greater preference for CE and AE and a significantly lesser
preference for RO over entering weekday women. Opon
graduation two years later, compared to entering women in
their respective groups, weekend students were significantly
less likely to prefer CE; both groups were less likely to
prefer RO; and both groups were more likely to prefer AC than
their entering counterparts.
Weekend students made an overall shift from Divergers to
Accommodators, while weekday students remained Divergers, but
were not so strong in that style. Since the weekend students
were on the average 11 years older than weekday students, and
significantly higher on the CE scale upon entering college,
Mentkowski concluded that "life experiences" prior to college
for those women did not cause a shift toward AC, but actually
enhanced the preference for CE. Similarly, since weekend
students were significantly higher on the AE scale, she
concluded that life experiences prior to college may have
enhanced the AE preference. College, in contrast to life


39
experiences, according to Mentkowski, does shift the
preference from CE to AC and does promote a more "balanced"
learning style.
In correspondence with this author, Kolb has referred to
one's "adaptive style," and he has developed an instrument,
the Adaptive Style Indicator (ASI), to measure this ability.
(See Kolb, 1980 and 1984 for descriptions of the ASI and its
implications for education.) Apparently, the successful
Alverno students had learned to adapt to a variety of
learning situations, thus a shift to the "more balanced"
style.
Leflar (1982a) reported, after administering McCarthy's
4MAT Battery, that freshmen at the College of the Ozarks
(Arkansas) were significantly, "overwhelmingly," concrete in
their learning preference, indicating they would profit most
from simulations, group discussions, dramatizations, peer
tutoring, and independent explorations. Traditional,
abstract classroom methods of lecturing and assigning
readings were used in the majority of the courses in the
College at the time, and, subsequent to Leflar's findings,
training of faculty in the use of McCarthy's 4Mat system for
advising and teaching has resulted at the faculty's request.
LSI Comparative Studies
Concerned about the construct validity of learning
styles instruments, Ferrell (1983), analyzed four
instruments: the Grasha-Riechmann Learning Style Scales
(SLSS), Kolb's Learning Style Inventory (LSI), Johnson's
Decision Making Inventory (DMI), and the Dunn Learning Style


40
Inventory (DLSI). Subjects tall from Southern Illinois) were
260 high school students and 211 community college students
ranging in age from 17 to 21, with an equal representation of
males and females in both populations. Data obtained from
each of the subjects for the four instruments were separately
factor analyzed. Three factors were obtained from the SLSS
and four from each of the others. For the LSI, 23 (of the
36) items loaded on four single factors and seven items did
not have salient loadings on any factor. Ferrell reported
that only for the Kolb LSI did the revealed factors match the
described learning styles. Items comprising the four factors
extracted matched the four learning preferences as described
by Kolb and "supported Kolb's conceptualization of learning
styles" (p. 36). In the same 1983 study, Ferrell also
examined the four instruments in relation to Keefe's (1979)
conceptualization of learning style (comprised of cognitive,
affective, and physical/physiological behaviors). None of
the instruments were found to completely fit Keefe's
paradigm. The LSI and DMI were cognitive in nature; the SLSS
was comprised of cognitive and affective factors; and the
DLSI reflected the affective and physical/physiological
aspects of learning style. A factor representing a positive
attitude toward learning was found on both the SLSS and the
LSI. Analytical/abstract orientations were found in factors
comprising the LSI and the DMI. In spite of the overlapping
factors across the four instruments, "(they) clearly were not
measuring the same thing" (p. 37). Therefore, Ferrell


41
concluded that "learning styles literature has not
established a single unified conception of learning style"
(p. 39). (See also Lawrence, 1984a, 1984b.)
In an attempt to define measurements and outcomes of
certain learning styles instruments, Dunn and others (1981)
compared the definitions and applications of eight different
learning style instruments, including the LSI. The results
of that comparison are summarized in Table 2-3, Comparison of
Learning Style Instruments. Dunn et al. reported that while
there were overlapping characteristics among the eight
approaches to measuring learning style (structure,
motivation, sociological needs, perceptual modes, and thought
processing), there were important differences, as shown in
Table 2-3. Further, disagreements existed among the
researchers on whether learning styles are inherited or
culturally determined, whether teaching should focus on
strengths exclusively or on both strengths and weaknesses to
build adaptability, and to what extent learning styles are
fixed or change over time.
Jung's and Myers' Theories of Psychological Types
To better understand the Myers-Briggs Type Indicator, it
is important to have an appreciation of Jung's and Myers'
theories of psychological types. Jung developed three
bi-polar psychological orientations. They are: Extraversin
and Introversion, Thinking and Feeling, and Sensing and
Intuiting. (See Campbell, 1971.) A fourth dimension,
Judging and Perceiving, was implicitly derived from Jung's
Theory by Isabel Myers and her mother, Katharine Briggs.


Table 2-3
Comparison
Author
Canfield and
Lafferty
Dunn, Dunn,
and Price
Gregorc
Mill
Hunt
Kolb
Kamirez and
Cat) tenetla
Schineck
of Learning Style Instruments
Instrument
Deflnlt Lon
Appllcatlon
teaming Style
Inveutory
Learning Style
Inveutory
Transact lona 1
Ability
Inventory
Cognitive Style
Interest
lnvontory
Teaclier Assess
ment of Student
Learning Styles
Learning Style
Inventory
Child Hating Form
Inventory of
Learning Process
Style derived from ac
ademic, structural,
and achievement con
ditions, content, mode
and expectstions.
Strengths identified
in environmental, emo
tional, sociological,
and physical dimen
sions.
Mind dualities of con
crete-abstract and
sequential-random are
pairad to determine
meaning,
Meaning reflected by
how qualitative and
theoretical symbols
are handled, influ
enced, and perceived.
Describes most likely
learning conditions
and amount of struc
ture needed.
Describes orientation
on dimensions of con
crete experience, ab
stract conceptualiza
tion, reflective ob
servation, and active
experimentation.
Style determined by
field dependency and
cultural differences.
Measures information
?rocessing ranging
rom shallow and re
iterative to deep and
o 1 ahora 11vo.
Used to develop materials for class
or lndividualsi to understand stu
dent difficulties! and to aid couns
eling. Emphasis on attltdue and ef
fect .
Used to diagnose individual learn
ing characteriatles. Suggests mater
ials to facilitate acli levement.
Emphasis on matching of materials
and methods to preferences. Encour
ages strengthening of non-
preferences.
Identifies major, minor, and negoti
able categories. Serves to develop
Personalized Educational Program
(PEP).
Used to enhance development of con
ceptual level, which ranges from
unsocialized to independent.
Emphasis on awareness of style and
alternative modes. Focus on non
dominant orientations as well as
strengths.
Used to match and mismatch learn
ing and teaching to enhance "bl-
cognitlve ability" and reduce style
preferences.
Used to encourage development of
deep, thoughtful, and olaborative
procesalng.


43
These four dimensions were used to develop scales which form
the Myers-Briggs Type Indicator. (See Myers, 1980.)
Extraversin and Introversion
Myers (1980) summarized the relative interests of the
introvert and the extravert:
The introvert's main interests are in the inner
world of concepts and ideas, while the extravert is
more involved with the outer world of people and things.
Therefore, when circumstances permit, the introvert
concentrates perception and judgement upon ideas, while
the extravert likes to focus them on the outside
environment, (p. 2)
It should be made clear that neither Jung nor his
followers have suggested that persons are exclusively one
extreme or another in the extravert-introvert dimension, nor
any of the other bi-polar dimensions described below. On the
other hand, Jung devoted much of his life to examining
neuroses resulting from the "falsification" of attitude type
(such as parental influence) Such examinaticns are clearly
(and thankfully) beyond the scope of this investigation.
Sensing and Intuiting
In describing the sensing-intuition dimension Myers
(1980) stated:
One form of perception is the familiar process of
sensing, by which we become aware of things directly
through our five senses. The other is the process of
intuition, which is an indirect perception by way of
the unconscious, incorporating ideas or associations
that the unconscious tacks on to perceptions coming from
the outside, (p. 2)
Thinking and Feeling
Myers (1980) described the thinking-feeling dimension as
two distinct and sharply contrasting ways of coming to
conclusions. One way is by the use of thinking, that


44
is, by a logical process, aimed at an impersonal
finding. The other is by feeling, that is, by
appreciationequally reasonable in its
fashionbestowing on things a personal, subjective
value, (p. 3)
Judging and Perceiving
The definitions Myers provided (above) for the sensing-
intuiting and thinking-feeling dimensions are concise
explanations of the perceiving and judging attitudes,
respectively. However, she further stated:
[These attitudes are] a way of life, a method for
dealing with the world around us. . (B)oth cannot be
used at the same moment, [and] most people find one
attitude more comfortable than the other .... This
preference makes the difference between the judging
people, who order their lives, and the perceptive
people who just live them. (pp. 8-9)
Dominant Function
As described above, perception occurs either through the
senses or through intuition, and judgement occurs either
through thinking or through feeling. While all four
functions are distinctive elements of one's deep structure of
psychological type and are all used regularly, one is
considered "dominant and forms the centerpost of the
mental system. It provides psychological consistency, (and)
basic attitudes, values, and interests can be seen as flowing
from the arrangement of preferences of the four functions"
(Lawrence, 1984b, p. 2, emphasis added). (Jung referred to
the function opposite of the dominant function as "inferior,"
and von Franz (1979) has provided a detailed characterization
of the this function.)


45
Schemel and Borbely (1982) graphically discuss the two
preferred attitudes (which must be chosen from El and JP)
and the two preferred functions (which must be chosen
from SN and TF) See Appendix A, Attitudes and Functions by
Type, for a complete listing of all the attitudes and
functions, including dominants and auxiliaries, for each of
the 16 types.
Myers-Briggs Type Indicator
Introduction
The Myers-Briggs Type Indicator (MBTI) has been in use
since first published by the Educational Testing Service in
1962. Its purpose was and is to implement Jung's theory of
psychological type.
Myers (1962) acknowledges her mother, Katharine C.
Briggs, for the original theory of type based upon Jung's
work, but it is Isabel Briggs Myers who is credited with the
authorship of the MBTI. Myers, educated at home after
becoming a "first grade dropout" (Lawrence, 1982, p. 14),
began working on her theories of type during World War II to
"promote human understanding [and] to help people choose
careers which allowed them to use their best abilities" (p.
14). During the next 20 years, by testing thousands of high
school students then tracing their career choices, and by
testing over 5,000 medical students then checking to see if
they had been successful in their chosen careers, Myers
slowly developed the MBTI.
The Educational Testing Service learned of Myers' work
through one of the medical schools used in her research and


46
published the first MBTI (Forra F) in 1962, primarily for
psychologists and other professionals interested in human
behavior- The data for the 1962 publication were from a
large data base collection which terminated in 1957. Twenty
years later, Myers repeated the normative measures to
determine if temporal or cultural changes had eroded the
validity of the Type Indicator and to make some minor
modifications which two decades of experience with the
instrument suggested were desirable. (See Myers, 1977). In
1975, the MBTI (Form G), then published by Consulting
Psychologists Press, was considered ready for redistribution.
Description of the MBTI
The MBTI (Form G) is a 126-item, forced-choice
questionnaire (scaled down from the original 166-item, Form
F) designed as a tool to determine and utilize Jung's
psychological types. The result of an individual assessment
is a determination of one's preference on each of four
dimensions: Extraversin (E) or Introversion (I), Sensing (S)
or Intuition (N), Thinking (T) or Feeling (F), and Judging
(J) or Perceiving (P). Sixteen combinations of type are
possible from the preferences on the four dimensions. These
types are shown in Table 2-4, The Sixteen Psychological
Types.
Since the MBTI focuses on preferences (strengths) and
not weaknesses, the emphasis is on what is unique, yet
normal, about the individual being tested, and not an
emphasis on abnormality, such as is often the case with other
psychological measurements. The non-judgmental nature of the


47
Table 2-4
The Sixteen Psychological Types
ISTJ
ISFJ
INFJ
INTJ
ISTP
ISFP
INFP
INTP
ESTP
ESFP
ENFP
ENTP
ESTJ
ESFJ
ENFJ
ENTJ


48
Type Indicator aids in the understanding of individuals
without the adverse labeling effects.
Distribution of Type
McCaulley (in press) has combined the results of Myers
(1982) samples of 4,933 male and 4,387 female 11th and 12th
grade high school students. These students were largely
college-preparatory and were above average in socio-economic
status. The distribution of types from those samples is
shown in Table 2-5, Distribution of Type for Combined Samples
of 11th and L2th Grade High School Students.
From these data, distributions on the four dimensions
can be computed for students about to enter college. Table
2-6, Distribution of Preferences for Combined Samples of 11th
and 12th Grade High School Students, provides percentage
distributions for males and females for the above samples.
Males and females showed the same overall preferences (though
slightly different percentages) for three of the four
dimensionsEl, SN, and JP. For the TF dimension, a reversal
occurred by sex. Males preferred thinking over feeling 61%
39%; females preferred feeling over thinking two to one.
These data are consistent with Myers (1977) earlier findings.
Reliability
Myers (1962, 1977) and McCaulley and Natter (1980) have
reported high internal consistencies (split-half
correlations) for the MBTI on samples from high school
through college, ranging from .77 to .87 for El, .70 to .87
for SN, .44 to .86 for TF, and .71 to .84 for JP. McCaulley
and Natter (1980) reported that underachieving samples showed


49
Table 2-5
Distribution of Type for Combined Samples of 11th and 12th
Grade High School Students
Type
Males
(n = 4,933)
Females
(n = 4,387)
ISTJ
8.8%
4.9%
istp
6.1
2.0
ISFJ
4.5
9.5
ISFP
5.2
5.7
INFJ
1.6
2.0
INFP
3.5
4.4
INTJ
3.7
1.4
INTP
4.8
2.1
ESTP
8.9
3.9
ESTJ
17.1
12.6
ESFP
7.2
11.8
ESFJ
8.2
20.5
ENFP
6.0
9.4
ENFJ
2.8
4.5
ENTP
6.4
3.2
ENTJ
5.3
2.4


50
Table 2-6
Distribution of Preferences for Combined Samples of 11th
and 12th Grade High School Students
E
r
S
N
T
F
J
P
Males 61.9
(n = 4,933)
38.2
66.0
34.1
61.1
39.0
52.0
48.1
Females 68.3
(n = 4,387)
32.0
70.9
29.4
32.5
67.8
57.8
42.5
Note: Percentages do not equal 100 due to rounding.


51
lower internal consistency correlations, particularly on the
TF dimension.
Reporting on research on test-retest reliability,
McCaulley and Natter (1980) cited Strickler and Ross (1962)
who found in a study of 41 Amherst students reliabilities of
.73 for El, .69 for SN, .48 for TF, and .69 for JP.
McCaulley and Natter (1980) also reported that a study of
Howard University Graduates by Levy, Murphy, and Carlson
(1972) showed a higher test-retest reliability (after a
two-month interval) than the 1962 Strickler-Ross comparison,
and the correlations were slightly higher for females than
for males.
Carskadon (1979b) found most test-retest reliabilities
on Form G of the MBTI to be good to satisfactory. However,
he also reported that test-retest reliability for males on
the TF scale tended to be poor, replicating findings on Form
F of the MBTI. Later, in a replication of the study of
reliability of Form G, Carskadon (1982b) found a puzzling
reversal of the TF reliability between the sexes. Males
showed a .91 test--retest reliability, females showed only
.56, a highly significant difference. Carskadon suggested
further research on the interplay between sex and type and on
how the same type preferences may be manifested differently
for the two sexes.
Myers (1962) spoke to the issue of change in type from
test to retest:
Type development, i.e., the extent to which a person
actually has developed the processes and attitudes which


52
he prefers, enters every equation as an unknown quality.
[Nor is it known how many persons in a sample would be]
answering virtually at random because their type is
insufficiently developed to govern their responses, (p.
19)
Summarizing MBTI reliability, McCaulley (1981) reported
that when changes in type occur on retest, most changes
affect only one preference, and those preferences with low
original endorsement are the most likely to change. (c.f.,
Kolb, 1976. See also Carskadon, 1982a.)
MBTI Validity Studies
McCaulley and Natter (1980) summarized research on
comparison of the MBTI with the Gray-Wheelright Psychological
Types Questionnaire (which determines Jungian types) and with
a battery of 32 tests measuring ability, interest, and
personality variables. The MBTI measured the same dimensions
as the Gray-Wheelright, and the scales from the 32-test
battery significantly correlated with the MBTI in the
predicted directions. Citing earlier work by Myers (1962),
they summarized the comparison of the MBTI with the Alport-
Vernon-Lindsey Study of Values (AVL), Edwards Personal
Preference Scale (EPPS), and the Personality Research
Inventory (PRI). Significant correlations are shown in Table
2-7, and the strongest correlation in each comparison is
underscored.
From all the above findings, McCaulley and Natter con
cluded that there is construct, concurrent, and predictive
validity for the MBTI personality, academic, and behavioral
measures. They further reported that intuitives consistently
score higher on aptitude measures than sensing types. In


Table 2-7
HBTI Compared with the Alpoct-Vernon-Lindsey Study of
Values, the Edwards Personality Preference Scale, and the
Personality Research Inventory
Alport-Vernon-Lindsey Study of Values
Theoretical INTJ
Economic ESTJ
Aesthetic IN-P
Social -SF-
Political EST-
Religious -NF-
Edwards Personality Preference Scale
Intellectual Achievement INT-
Order ISTJ
Exhibition EP
Autonomy -NTP
Affiliation E-F-
Dominance E-T-
Nurturance F-
Change -NTP
Endurance TJ
Personality Research Inventory
Complexity Tolerance -NFP
Impulsiveness EN-P
Talkativeness E
Gregariousness ES
Work Attitude EJ
Artistic -NFP
Liking to use Mind -NT-
Note: Strongest correlations for each type are underscored


54
ability measures, intuitives consistently score higher than
sensing types in English, vocabulary, verbal, and reading
tests.
Educational Applications
McCaulley and Natter (1980) reported that University of
Florida ESTPs ranked first in how fast they read, but low in
comprehension. INTPs, who ranked second in reading speed,
had a high comprehension rate.
In a study reported by Myers (1980), Florida high school
students showed a significant difference between intuitives
and sensing types on mathematics and science. Ns outscored
5s on five out of eight mathematics measures and two out of
three science measures. The primary difference occurred with
problem-solving ability, not computational skills. In
comparing intuitive and sensing types' academic aptitude and
study skills, intuitives scored significantly higher on all
measures (overall grade average, 8th grade study skills, 12th
grade aptitude, and California Test of Mental Maturity).
In contrast, according to Myers (1980), sensing types
significantly outscored intuitives in practical knowledge
applications (such as, electronics and mechanics).
Similarly, thinking types outscored feeling types in
technical, clerical, administrative, electronics, general
mechanics, and motor mechanics. She further asserted that
the most conspicuous consequence of type preference in
educational settings is in the choice between the two kinds
of perceptions: sensing and intuition.
It is therefore understandable that, as most schools are
now run, sensing children have less use for school than


55
intuitive children do (often no use at all), that on the
average they make lower grades and score lower on
intelligence tests (though not enough lower to account
for their grades), and that they far mo'e frequently
drop out. (p. 127)
Substantiating the above claim, Myers (1980) compared the
671 finalists for National Merit Scholarships and found
percentages of 17 and 83 for S and N, respectively. She also
assessed 500 students who did not finish 8th grade and found
dropout rates of 99.6% and 0.4% for S and N, respectively.
McCaulley and Natter (1980) used the MBTI to type
students at the Florida State University Developmental
Research School. Also available were results from a 187-
item "learning activities" questionnaire and selected high
school measurements (grades in school, eighth grade test,
ninth grade test, twelfth grade test, vocational aptitude,
and IQ) From these data they concluded the following:
Extraverts may do better on oral than written tests
and on tests applying knowledge than on tests of concepts and
ideas. While confident and willing to make oral
presentations, they scored lower than introverts on several
academic measures including aptitude, reading, and
mathematics. Introverts may do better on written tests
than on oral tests, and better on tests measuring concepts
and ideas than on tests of practical application. They may
have an advantage in college work where the focus is on
understanding concepts.
Sensing types have a greater interest in the "real
thing" than intuitives, and test scores may underestimate
their true knowledge. At a disadvantage with timed tests,


56
written tests, or tests requiring a knowledge of theory, they
may prefer objective tests which present, rather than ask for
the creation of, choices. They may do well on power,
performance, motor-skill, spatial, or perceptual intelligence
tests, but they may read less and write more poorly than
intuitives. Intuitive types, with their interest in
reading, tend to do well on tests requiring writing on the
meaning of words (comprehension) or symbols (problem
solving). Their perceptual ability serves them well on timed
tests, and they may score higher on academic measures than
sensing types. Intuitives may prefer independent study,
indicate problems with time management, and like spending
time on non-required reading.
Thinking types may have an edge over feeling types in
mathematics and science courses and in courses dealing with
equipment. They indicate a seriousness about education and
learning strategies, and they may score higher than feeling
types in electrical, mechanical, and technical areas.
Feeling types tend to score higher than thinking types on
social awareness and sensitivity and lower on mathematics,
science, and technical skills. They may achieve mastery in
weaker subjects, though, if the goal is value-related,
especially to human relationships.
Judging types may have grades that are likely to be
better than would be predicted on the basis of aptitude
scores. They like scheduling and planning their work, and
they profess an enjoyment for "the work of school," such as,
studying, preparing for exams, making reports, and doing


57
projects. They may score slightly higher than perceptives in
making grades, while scoring lever in all other academic
measures. Perceiving types pick up information through
curiosity, and their aptitude scores may indicate grades
higher than actually received. They tend to procrastinate
and not plan their work. Searching for freedom, they may
daydream. They may score higher on every measure of academic
achievement except grades in school.
In discussing self-concept, McCaulley and Natter (1980)
reported that IP types are likely to turn inward and feel
inadequate, while EJ types focus on the outer world and are
likely to have confidence in managing it. Intuitive types,
who tend to achieve higher academic scores, say they feel
academically superior, as do chinking types. Perceptive
types, who desire spontaneity and freedom, may feel they are
"stuck in a rut" (p. 180). Measures of self-concept, or
confidence, were the best predictors of good grades in the
McCaulley and Natter study. Confident students were not test
anxious, but they were concerned about exams. Such students
had a study plan and were serious about their work. There was
no difference in high predictors of good grades for black and
white students.
McCaulley and Natter (1980) categorized four different
knowledge approaches based upon the interrelationships of
extraversion-introversion and sensing-intuition:
IS: Careful Compilers for whom knowledge is
important to establish truth.


58
ES: Pragmatists for whom knowledge is important for
practical use.
IN: Academics for whom knowledge is important for
its own sake.
EN: Innovators for whom knowledge is important for
innovation.
They further described the interrelationship of sensing-
intuition and thinking-feeling:
-ST-: Practical, matter-of-fact; collects data which
can be verified by the five senses and can be used to make
logical decisions.
-SF-: Sociable, friendly; collects sense data, but
relies upon feeling rather than logic for decision-making.
-NF-: Enthusiastic, insightful; uses possibilities to
judge with personal warmth.
-NT-: Logical, ingenious; uses possibilities to make
logical decisions.
Considerable research, in addition to the major studies
cited above, exists on applications of type theory in
educational settings. The remainder of this section is a
selection of brief research reports to provide a further
foundation for how type theory may help explain students'
success (or lack of it) in the areas chosen for analysis in
the present research.
Contessa (1981) found that eighth graders (an age when
most students waiver between concrete operational and formal
operational stages of cognitive development, according to
Piagetian concepts) demonstrated a significant relationship


59
between sensing and intuition and Level of cognitive
development, with a proportionately greater number of Ns
classified as formal operational thinkers than Ss. He also
reported that formal operational thinkers performed
significantly higher than operational thinkers on a posttest
of the science concept of model building. (Lawrence (1982)
has warned: "Correcting the biases of instruction that harms
ES type children is perhaps the most crucial unrecognized
problem of American Education" (p. 42). It is ironic that ES
teachers may be the most influential in changing students'
attitudes toward school. (See Cohen, 1981.))
Todd and Roberts (1981) found no difference between art
majors and music education majors on the El and TF
dimensions. They reported, however, a significant difference
on the SN and JP dimensions. Two cells, ENFP and INFP, held
58.5% of the art majors, while music majors seemed to be more
randomly distributed among the 16 types, with the greatest
percentage (20) represented by ENFJ. Music majors preferred
sensing (42%) and judging (58%). Art majors preferred
intuition (80%) and perception (74%).
In examining the relationship between type and
performance of practicing speech pathologists on the National
Examination in Speech Pathology, Middleton and Roberts (1981)
found the predominant preference to be ENFJ. The N function
was the best predictor of scores on the exam, accounting for
10.4% of the variance in the sample.
Hoffman, Waters, and Berry (1981) reported a high
dropout rate among EPs (53%) from a computer-assisted program


60
to teach Morse code. The EPs who dropped comprised 38% of
all dropouts from the program compared to an expectancy of
less than 20%.
When offered the opportunity to volunteer for an
innovative, non-structured humanities program at Walt Whitman
High School, Barberousse (c. 1970) found that among the 100
students who volunteered, 6% were STs, 15% were SFs, 19% were
NTs, and 60% were NFs.
Roberts and Butler (1982) found that among 100 upper-
division and graduate students enrolled in a reading program
at Texas Tech University, there was a significant positive
correlation on the SN dimension with vocabulary,
comprehension, and total reading scores. No correlation was
found with reading rate and SN, and no other MBTI dimensions
correlated with any of the reading scores.
Roberts and Butler (1982) found that intuitives
significantly preferred reading as their choice of a medium
of instruction, while sensing types did not. One type, ESFP,
significantly rejected reading as an instructional choice.
ESTJs and INFPs significantly preferred lecturing. To
explain the apparent contradiction of these two types,
Roberts asserted: "ESTJs like to lecture, and INFPs like to
listen to good lectures, so both rated the lecture high as a
medium of instruction" (p. 86). Fourteen of the 16 types
rejected audio as a desired medium of instruction. ISFPs and
ESFPs did not reject audio, nor did they show it as a
preference.


61
To demonstrate difference in one pair of type extremes,
McCauiley (1976) reported that from a sample of 3275
niversity of Florida entering freshmen in 1972, ESFJ types
ranked 16th among all the types on the Florida 12th grade
Placement Test scores, 16th on the SCAT, and 12th among their
class in first-quarter grades. INTP types, in contrast,
ranked first on the 12th grade placement test, first on SCAT
and SAT, and first on first-term grades. Focusing on the SN
dimension, McCauiley reported that sensing types were 78% of
a sample of 135 underprivileged university students; Ns were
22% of that group. By contrast, 18% of 1101 National Merit
finalists were Ss; 82% were Ns. "College," she reported,
"with its demand for complex problem solving, and for working
at an abstract, theoretical, or imaginative level, suits the
interests of the intuitive type" (p. 7).
Many of the above research findings lead to the
conclusion that certain type combinations may be very
important in educational research. In addition to examining
the individual scales and the dichotomous dimensions,
McCauiley (1977) has recommended an examination of certain
groupings of type while conducting research:
Group 1: IJ, IP, EP, and EJ to examine the
perceiving function as dominant (IJ and EP) and the
judging function as dominant (IP and EJ).
Group 2: -ST-, -SF-, -NF-, and -NT- to examine the
combinations of perception (S and N) and judging (T and F) .
Group 3: -S-J (practical, organized), -S-P (practical,
spontaneous), -N-P (innovative, spontaneous), and -N-J
(innovative, organized).


62
Group 4: TJ (analytic, executive), TP (analytic,
adaptable, FP (sympathetic, adaptable), and FJ
(sympathetic, executive).
Group 5: IN (academic), EN (innovative), IS
(realistic), and ES (pragmatic).
Students' Perception of Type
Carskadon (1982a) reported that 129 college students
significantly chose a description of their actual type or a
description of a type in which their weakest preference was
reversed over descriptions which had preferences on El and JP
reversed, descriptions which had preferences on SN and TF
reversed, and descriptions which had all four preferences
reversed. (See Table 2-8, College Students' Perception of
Type.) In the same study, Carskadon determined that students
could accurately predict their preferences: 18% accurately
predicted all four functions; 44% were correct on three
functions; 24% were correct on two functions; 12% were
correct on one function; and only 2% were wrong on all four
functions. Broken down by dimension, students accurately
predicted their El dimension 68% of the time, their SN
dimension 66% of the time, their TF dimension 63% of the
time, and their JP dimension 72% of the time. In a
replication study, Carskadon (1982c) reported that 50% of 118
college students ranked their actual type descriptions as
their first choice. Further, students rated their actual
descriptions as "very true" (27%) or "mostly true" (37%),
while rating the description with all scales reversed as
"partly true" (39%) or "not very true at all (34%). As in


63
Table 2-8
College Students' Perception o£ Type
(N = 129)
Description of Type Percentage Who Ranked It Highest
Actual description 35
Weakest preference reversed 31
E-I and J-P reversed 23
S-N and T-F reversed 7
All scales reversed 4


64
the earlier study, Carskadon found that students were much
more sensitive to reversals on their dominant/auxiliary (SN
and TF) dimensions than they were on their attitude (El and
JP) dimensions.
Comparison of the LSI and MBTI
The MBTI and the LSI variables can be expected to appear
in combinations and patterns in the regression equations
which form the bases of the research hypotheses; it is
instructive, therefore, to examine research which compares
the two instruments. From a comparison of descriptions of
LSI styles and MBTI types, Kolb (1984) predicted the
following relationships:
Divergers are similar to I-F- types.
Assimilators are similar to IN types.
Convergers are similar to E-T- types.
Accommodators are similar to ES types.
In summarizing data from two populations, Kent State
undergraduates and University of Wisconsin M.B.A.s, Kolb
(1984) found significant correlations between the LSI and
MBTI as shown below:
El: Positively correlated with RO; negatively correlated
with AE.
SN: Positively correlated with AC; negatively correlated
with CE and AE.
TF: Positively correlated with CE; negatively correlated
with AC.
JP: No significant correlations.


65
Using data from a study of 220 managers and M.B.A.
students, Kolb reported the following relationships among
MBTI attitudes functions and LSI scales:
E is associated with AE and AC (Converger).
I is associated with AC and RO (Assimilator).
S is associated with AE and CE (Accommodator).
N is associated with AC and RO (Assimilator).
T is associated with AC and AE (Converger).
F is associated with CE and RO (Diverger).
J is associated with AC and AE (Converger).
P is associated with CE and AE (Accommodator).
While Kolb (1984) has indicated that correlations
between group scores on the LSI and MBTI offer some empirical
indication of validity of relationships between the two
instruments, he cautioned that:
(B)oth the LSI and MBTI instruments are based upon
self-analysis and report. Thus we are testing whether
those who take the two tests agree with our predictions
of the similiarity between Jung's concepts and those of
experiential learning theory; we are not testing, except
by inference, their actual behavior, (p. 80)
Summary
Learning Styles research has not resulted in a unified
theory of how individuals learn. However, various constructs
have emerged which help with an understanding of the
individual preferences learners exhibit. The Literature
review above was provided to establish three major learning
style constructs (theoretical, response-based, and
integrated); to show how learning style and an individual's
learning environment are related; to establish a rationale


66
for choosing for the present research two of the integrated
approaches to learning style (the Kolb-McCarthy Learning
Style Inventory and the Myers-Briggs Type Indicator); to
explain the theoretical bases for the LSI and MBTI and cite
validity, reliability, and application research on the two
instruments; and to provide a theoretical comparison of the
LSI and MBTI in order to better understand expected
combinations and patterns of predictor variables from these
two instruments in the regression equations.


CHAPTER THREE
METHODOLOGY
Population
The initial population available for the study was a
group of 188 students enrolled in the 10 sections of DVST
1012, Learning Skills, during the Fall, 1983 term at the
University of Arkansas. (DVST 1012 is a semester-long,
two-hour course offered through the College of Education and
is described in the next section.) Of the 188 students
enrolled in the course, 172 were available for the initial
assessment (described in a later section). The remaining 16
had either dropped the course or were unavailable for
assessment.
From the group of 172 students who received the initial
assessment, 128 were chosen to become a part of the study.
Students were chosen who were new freshmen entering the
University of Arkansas for the first time. Of the 128
students in the study 123 were 17-, 18-, and 19-year olds who
had graduated from high school the previous spring (1983),
but five students had one or more years intervening between
high school and entrance into college. The population is not
to be considered a representative sample of all entering
57


68
freshmen at the University. As explained in the next
section, students enrolled in DVST 1012, Learning Skills are
usually there because of an indication of poor preparation
for college. As will be shown later, however, not all
students in the study were academically underprepared in high
schoolboth the high school grade point average and ACT
scores for some of the students indicated high potential
ability.
There were 75 males (58.6%) and 53 females (41.4%) in
the study, and they represented all of the
undergraduate colleges and schools at the University except
the School of Nursing. (See Table 3-1, College Distribution
for Students in the Study. ) The College of Business
Administration is overrepresented in the population when
compared to the entire entering-freshman population. For the
study population, the College of Business Administration
students represented 42.2% of the total; in the larger
entering-freshman class, approximately one third of the
students had selected Business Administration as a major. It
is instructive to note that the College of Business
Administration consistently reports above average rates of
probation, suspension, dismissal, and withdrawal, yet
underprepared students selected that college at a relatevely
high percentage.
DVST 1012, Learning Skills
DVST 1012, Learning Skills, is one of five developmental
courses offered through the Department of Developmental


Table 3-1
College Distribution for Students in the Study
College
Males Females Total
College of Agriculture & Home Econ.
School of Architecture
Fulbright College of Arts & Sciences 17
College of Business Administration
College of Education
College of Engineering
School of Nursing
4
5
9
6
0
6
17
22
39
33
21
54
5
5
10
10
0
10
0
0
0
75
53
128
Totals


70
Studies (which the author chairs) in the College of Education
at the University of Arkansas. The courses offered are:
DVST 1012, Learning Skills
DVST 1031, Survival Skills
DVST 1041, Human Potential Seminar
DVST 1051, Career Development
DVST 1071, Independent Developmental Studies
All DVST courses are open to all students and are one
credit hour, except DVST 1012, which is a two-hour course.
Except in the College of Agriculture and Home Economics and
in the College of Education, the courses do not meet degree
requirements. However, in all colleges the courses carry
institutional credit, and they are used to compute term and
overall grade point averages. Students are assigned to one
or more of the developmental courses through summer
orientation, academic advising, faculty referral, in-house
remediation, and self-selection. The demand for the courses
is greater than the space available, and attempts are made to
hold space for students with the greatest need.
For the egst part, students in the Learning Skills
course are referred by faculty who advise students at
pre-registration. Students expressing poor preparation in
study skills, habits, and attitudes in high school are the
primary candidates for the course. Freshmen comprise
approximately 75% of the enrollment in the course.
The Learning Skills course provides instruction with
three major goals: study skills knowledge, practice in using
the learned skills, and the study attitudes needed for


71
successful college work. Major topics included in the course
are time management, concentration, memory, reading college
textbooks, listening and notetaking skills, preparing for and
taking exams, and, in general, identifying and practicing
good learning and studying behaviors. A point system is used
for grading and includes attendance, homework assignments,
class quizzes, Learning Lab work, special-topic workshops,
and a final exam.
Students are given a Learning Skills Assessment (LSA) at
the beginning of the term to determine potential problems in
reading, writing, mathematics, listening and notetaking,
spelling, and study skills. As a result of this assessment,
students are given the opportunity to attend the Learning Lab
and/or special-topic workshops as options in addition to
other class requirements.
Learning Skills Assessment
During the first week of classes, 172 of the 188
students enrolled in the ten sections of DVST 1012, Learning
Skills, were assessed as a group to determine potential
problems in basic skills and study skills. The Learning
Skills Assessment (LSA) has eight components and all eight
were administered:
A. Reading rate and comprehension. An untimed
reading selection was presented to the students. They were
asked to record their reading time when they were finished,
and this time was converted to a words-per-minute rate. They
were then asked to answer ten questions to determine their
comprehension of the material.


72
B. Textbook reading. Four untimed reading
selections were presented to the students. They were asked
to answer three questions to determine their understanding of
subject matter, main idea, and supporting detail. The
answers to the 12 questions were then grouped and converted
to percentage figures for each of the three areas tested.
C. Listening skills. A recorded "mini lecture,"
approximately five minutes long, was presented to students
via a recording, and they were instructed to listen and to
not take notes. At the end of the recording, the students
answered five questions on the selection. Correct answers
were converted to a percentage correct.
D. Academic writing. Students were asked to choose
between two possible writing topics, both of which related to
freedom in the New World. Students were then asked to write
at least two paragraphs, and their essays were judged on
awareness of audience, conception of subject, writer image,
overall organization, paragraph construction, sentence
patterns, vocabulary, spelling, and grammar.
E. Notetaking. A sample 'mini iecture,"
approximately seven minutes long, was presented to students
via a recording, and they were asked to take notes. The set
of notes was evaluated to determine if the student was able
to pick out the five main ideas and the ten supporting
details (two for each main idea) in the selection.
F. Spelling. Twenty commonly-misspelled words were
presented to students via a recording. Correct answers were
converted to a percentage correct.


73
G. Mathematics. Six basic mathematics questions
and five basic algebra questions were presented to students
in an untimed test to provide a gross-level assessment of
potential problems in those two areas.
H. Study habits. A 50-item, untimed study habits
questionnaire was administered to students to determine their
strengths and weaknesses in concentration, memory, organizing
time, studying textbooks, listening and notetaking, taking
tests, and motivation.
Data were available for research only for Sections A, 8,
C, E, and H of the LSA, since those sections relate directly
to the goals of the course, and only those five areas were
used in the study. Sections D, F, and G were remediated, to
the extent possible given time and resources available,
outside of class through Learning Lab work and/or special-
topics workshops. (A primary value of the LSA, particularly
for sections not directly related to the course, is the
feedback given to students in individual conference sessions
by the classroom instructors.)
Assessment of Learning Styles and Psychological Type
During the fourth week of classes, 172 of the 138
students enrolled in the ten sections of DVST 1012, Learning
Skills, were assessed to determine their learning styles and
psychological types. The assessments took the first hour of
each two-hour class. When the class met for the second hour
later in the week, feedback and score interpretations were
provided to the class as a whole. The instruments used were
the Kolb-McCarthy Learning Style Inventory (LSI) and the


74
Myers-Briggs Type Indicator (MBTI, Form G). Additionally, a
self-report on the accuracy and relevance of the assessments
was asked of each student. (See Appendix B, Accuracy and
Relevance of Style and Type.) All assessment and feedback
sessions for the LSI and MBTI were provided by the
investigator.
Kolb-McCarthy Learning Style Inventory
The nine-item, forced-choice LSI was administered to
students by the investigator in each of the ten sections
after a brief explanation of the purpose of the assessment
was given and standard instructions were read. Students were
asked to rank order the four completion responses given for
each of the nine stem items, for a total of 36 responses.
The assessment was not timed, but students typically finished
in 15 minutes or less. Students were asked to record their
name, age, sex, date, and section number on the answer sheet.
Anonymity was assured by tel Ling students that names were to
be used only to match against other information and that only
aggregate data were to be reported. The answer sheets were
later hand scored, and individual feedback reports were
prepared.
At the group feedback session (the next class period
later in the week) students were told of the underlying
theory of the LSI, and they each received a graph identifying
their perceiving/processing preferences and the resulting
learning style. The characteristics of each style were
explained to help students better understand themselves in
various learning situations, to stimulate their thinking


75
about a choice of major, and to better understand others.
They also received a handout explaining all four styles.
Myers-Briqqs Type Indicator
The 126-item MBTI (Form G) was administered to students
by the investigator in each of the 10 sections of the course
after a brief explanation of the purpose of the assessment
was given and standard instructions were read. The
assessment was not timed, but students typically finished in
30 minutes or less. Students were asked to complete the
standard Form G answer sheet which asks for their date of
birth, the date of testing, sex, student status (yes or no),
preferred subject, occupation type (if any), and job
satisfaction (if employed). Anonymity was assured. The
answer sheets were later hand scored, and individual feedback
reports were prepared.
At the group feedback session, the underlying theory of
psychological type was explained, and students were given
individual type reports and descriptions of their type as
handouts. Type strengths were emphasized, and students were
advised to think of type as their unique way of interacting
with the world around them.
Self-Report of Accuracy and Relevance
At the feedback sessions, and as the results were being
explained, students were asked to rate the accuracy and
relevance of both the LSI and MBTI. Specifically, students
were asked to:
1. Guess their style and type after hearing a general
description of both but prior to receiving their individual
reports;


76
2. Assess the accuracy of their style and type after
hearing and reading a description of them;
3. State if there was a style or type they would rather
be; and
4. Answer relevance questions about the assessment and
feedback process pertaining to personal insight, application
to college work, application to personal life, understanding
of others, and thinking about career choices. Appendix B,
Accuracy and Relevance of Style and Type, provides a
description of the assessment and the results obtained.
Selection of the Population to Study
The problem statement in Chapter One, Introduction,
concerns the lack of success of entering college freshmen.
Thus only entering freshmen without prior college experience
were selected for analysis from the 172 students who received
the initial assessment. Students were chosen regardless of
their age as long as they met the entering-freshman criteria.
There were 128 students from the larger pool who met that
criteria. All but five of the students had graduated from
high school the previous spring (1983). As stated earlier,
the population was not sampled from the entire entering-
freshman class, and no inference of population representation
was drawn.
Selection of Independent and Dependent Variables
As stated in Chapter One, Introduction, college freshmen
often do not succeed in college even though high school grade
point averages and the results of standardized assessment
indicate they should. Such students demonstrate poor grades


77
in core-curriculum college coursework, low or failing grade
point averages, and a resulting academic status of probation,
suspension, or withdrawal. The selection of independent and
dependent variables was guided by the major research
question: How may advisors and others better predict success
or failure in core-curriculum coursework, freshman-year grade
point average, and resulting academic status by examining
factors in addition to high school grade point average and
standardized (ACT) assessment?
Independent variables
Five major independent variables were chosen for the
study:
High school grade point average (HSGPA)
American College Testing (ACT) scores
Kolb-McCarthy Learning Styles Inventory (LSI)
Myers-Briggs Type Indicator (MBTI)
Learning Skills Assessment (LSA)
The high school grade point averages were computed by
examining high school transcripts for the students.
Transcripts were available for 125 (97.7%) of the 128
students. In computing the HSGPA, all work performed by the
students for which they received a grade was used, since
overall high school grade point average was used at that time
for admissions and prediction purposes at the University.
American College Testing (ACT) scores were available for
116 (90.6%) of the 128 students. ACT scores were expected
for admission to the University when the study was initiated,
but students were not denied admission if the scores were not


78
available. (Beginning in fall, 1985 entering freshmen
without ACT scores will be denied admission.) In one
case, a Scholastic Aptitude Test (SAT) score was provided by
the student, and translated scores were used for ACT English,
Mathematics, and Composite. A translation formula was not
used for the Natural Sciences and Social Studies portions of
the ACT, since the SAT does not test these areas. (See
Langston and Watkins (1976) for an explanation of SAT to ACT
translation.)
Five sections of the LSA relate to goals of the Learning
Skills course (DVST 1012) and were chosen to comprise LSA
independent variables for the regression equations. The
sections chosen were:
A. Reading Rate and Comprehension
B. Textbook Reading
C. Listening Skills
D. Note Taking
E. Study Habits
Section A contains two scores, Reading Rate, in words
per minute, and Comprehension, expressed as a percentage, and
both were used in the analysis. Section B, Textbook Reading,
contains questions in three areas: subject matter, main
idea, and detail. The scores in this section are expressed
as percentages, and the three percentages were averaged into
one to yield a single textbook reading score for the study.
Section C, Listening Skills, has a single percentage score
and was used as is for the study. Section D, Note Taking, is
comprised of five main ideas and two details per idea, and


79
students' scores in this section were combined by multiplying
the number of main ideas they were able to identify times the
number of details identified to yield a single score which
could range from 0 to 50. Section E, Study Habits, is
comprised of 50 true-false questions relating to study habits
and attitudes, and these questions are subdivided into seven
major study skills areas: concentration, memory, organizing
time, studying textbooks, listening and notetaking, taking
tests, and motivation. Students' scores from the seven areas
were added to yield a study skills score which could range
from 0 to 50.
The Kolb-McCarthy Learning Style Inventory (LSI) was
used as an independent variable in the regression equations
by examining each of the scale scores (CE, RO, AC, AE) and
two combination scores (ACCE and AERO). Since the
combination scores are computed by subtraction, the resulting
scores ranged from -24 to *24, depending upon the relative
strength of the scale scores. Negative scores resulted when
CE was larger than AC and/or RO was larger than AE.
Additionally, the two combination scores, when "mapped,"
yield a specific learning style, and style was also examined
as an independent variable in an exploratory analysis of
cumulative grade point average, but not as a part of the
regression equations.
The MBTI yields an identification of psychological type,
e.g., ESTJ, INFP, etc. Raw-point scores are also available
on each of the eight single-letter attitudes or functions (S,
S, T, J, I, N, P, and P), and computed-point scores are


80
availabLe on each o£ the four HBTI dimensions (El, SN, TF,
and JP). The single-letter caw-point scores and the two-
letter computed-point dimension scores were examined as
independent variables in the regression equations. Since
only one unsigned score is available from the MBTI on each of
the computed two-letter dimensions, a method of determining
direction as well as strength was employed. A dimension
score was considered to be negative if the student's
preference on that dimension was found to be E, S, T, or J.
A dimension score was considered to be positive if the
preference on that dimension was found to be I, N, F, or P.
The MBTI types, as well as certain two-letter combinations,
e.g., ES, IN, -NT-, etc., as recommended by McCaulley
(1977), were used in exploratory analyses of cumulative grade
point averages, but not in the regression equations.
Dependent Variables
Five major dependent variables were chosen for the
research consistent with the problem statement and research
question. These variables were considered to be a hierarchy
of academic outcomes, ranging from the most general to the
most specific:
1. Academic status at the end of the freshman year.
2. Cumulative grade point average at the end of the
freshman year.
3. Success or failure in the core-curriculum
disciplines.
4. Success or failure in the core-curriculum
departments.


81
5. Success or failure in the core-curriculum courses.
Academic Status. Students academic status at the
end of the freshman year was used as the dependent variable
in this analysis. Academic status was coded as either "1"
(good standing or returned to good standing) or "0" (placed
on probation, continued on probation, suspended, or
withdrawn) A step-wise regression analysis was run using
LOGIST (developed by Frank E. Harrell, Ouke Dniversity
Medical Center) under the Statistical Analysis System (SAS)
at the University Computing Center.
Cumulative Grade Point Average. The cumulative
grade point average for all work attempted, computed at the
end of the freshman year, was used as a dependent variable in
this analysis. A standard step-wise regression analysis was
run using SAS at the University Computing Center.
Core curriculum. Success or failure in the core
curriculum was determined at three levels: discipline,
department, and course. At the highest level, four core
disciplines were chosen for analysis: Fine Arts, Humanities,
Natural Sciences, and Social Studies. (These disciplines are
the four major groupings of coursework in the Fulbright
College of Arts and Sciences at the University of Arkansas.)
At the next level, 11 departments were chosen from the four
disciplines. Departments were chosen only if 20 or more
enrollments from the study population were in that
department. (In many cases, students enrolled for more than
one course in a given discipline or department.) At the
lowest level, 14 courses were chosen for analysis. Courses


Full Text
UNIVERSITY OF FLORIDA
3 1262 08556 9076
Copyright 1985
by
Robert L. Moore



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