AN TNVESTIGATION OF THE
RELATTONSHIP BETWEEN THREE , ‘
CATEGORIES 0F COLLEGE MAJOR

AND SELECTED MEASURES OF L‘
COGNTTWE STYLE

Dissertation for the Degree of Ph: D.
MECHTGAN STATE UNIVERSITY
TGHN THOMAS DEINES
1974

 

 

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thesis entitled

AN INVESTIGATION OF THE RELATIONSHIP BETWEEN
THREE CATEGORIES OE COLLEGE MAJOR AND SELECTED
MEASURES OF COGNITIVE STYLE

presented by

John Thomas Deines

has been accepted towards fulfillment
of the requirements for

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Thesis Director

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Datel’l’M/tcl. 2 3: [Cf/Li % 5

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ABSTRACT
AN INVESTIGATION OF THE RELATIONSHIP BETWEEN

THREE CATEGORIES OE COLLEGE MAJOR AND SELECTED
MEASURES OF COGNITIVE STYLE

BY

John Thomas Deines

The term cognitive style refers to basic ways in which people
approach learning situations. The purpose of the present investigation
was to determine the relation of cognitive style to college major.

Should students majoring in different subjects be found to differ in
cognitive style, this could influence instructional strategy and provide
more information for counselors dealing with student concerns relative
to choice of major.

The cognitive style constructs selected for use were field-
dependence-independence, reflection-impulsivity, intuition as defined by
Malcolm Westcott, and the Jungian dominant types. American College Test
composite score and grade point average were included for purposes of
comparison. Humanities, social science, and natural science constituted
the college major categories. Two samples of 150 undergraduate students
(divided equally by sex and major) served as subjects for the study.

There were four major hypotheses. The first tested the related
measures simultaneously in their ability to differentiate the categories
of major and the sexes. The second examined the distribution of dominant
Jungian types across the major categories. The third and fourth tested
the related measures simultaneously in their ability to differentiate the
dominant sensors and intuiters and to differentiate dominant thinkers and

feelers. Analysis was via multivariate analysis of variance for testing

John Thomas Deines

the related measures simultaneously and via chi-square for testing the
distribution of dominant Jungian types across the categories of major.
Each measure was also tested via univariate analysis of variance.

No hypothesis in the study was confirmed as stated. However,
in one sample cognitive style was found to differentiate college majors
with field-dependence-independence contributing most to the differentia-
tion. The univariate analyses revealed that natural science majors tended
toward field-independence, were more concerned with accuracy on the meas-
ure of reflection-impulsivity, and tended to require less information to
draw conclusions on the intuition measure. While it was expected that
the strongest differentiation would be between natural science and humani-
ties majors, differences between social science majors and the other two
were more consistent. When the attitudes of extraversion and introver-
sion were combined with the dominant functions, extraverted and intro-
verted sensors were found to tend toward the natural sciences, extraverted
intuiters to tend away from the natural sciences, and extraverted thinkers

were found to tend toward the humanities.

AN INVESTIGATION OF THE RELATIONSHIP BETWEEN
THREE CATEGORIES OE COLLEGE MAJOR AND SELECTED

MEASURES OF COGNITIVE STYLE

BY

John Thomas Deines

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Counseling, Personnel Services
and Educational Psychology

1974

To
Beverly Jane
and

Sara Jane

ii

ACKNOWLEDGMENTS

I wish to recognize and to express my appreciation to the fol-
lowing individuals.

To Dr. Cecil Williams, dissertation director and practicum
supervisor, whose concern led him to take the more difficult
path in helping an introverted feeling type make explicit what
his nature prefers to be left implicit.

To Dr. Norman Kagan, chairman, for his guidance through the
coursework. Participation in one of his Interpersonal Process
Recall (IPR) workshops triggered a period of great growth in my
personal and professional life.

To Dr. Maryellen McSweeney, committee member, for her expertise
and patience in assisting me with the statistical and design
aspects of the present study. I would like to think that it was
her understanding of cognitive style, whether explicit or implic-
it, which made her one of the finest professors under whom I have
had the privilege to learn.

To Dr. Norman Abeles, committee member from the Department of
Psychology, for his support over a period of three and one-half
years and for the suggestions which greatly strengthened the de-
sign of the present study.

To my colleagues, Dr. Donald Bertsch, Dr. Jack Evans, and Dr.
Charles Nicholas, who went out of their way to help a struggling
doctoral candidate.

To my friends, Dave Dreyer, Sara Patten, Jim Ribby, and Cheryl
Moe, for their generous assistance in executing the present study.

To my wife, Beverly, for her total support. She assisted in so

many ways, small and large, for long and arduous hours to make the
present work a reality.

iii

TABLE OF CONTENTS

Chapter
I. ImODmTION O O O O O O O O O O O O O O O O O O O O O 0

Background . . . . . . .

Cognitive StYle Defined s s s s s s s s s s s s s s o
PurpOSCOfCheSCUdYoseosssssssssssso
Benefits of the Study . . . . . . . . . . . . . . . .
Cognitive Styles and College Majors to be Investigated
Secondary Purpose of the Present Study . . . . . . . .
Hypotheses . . . . . . . . . . . . . . . . . . . . . .
SM‘ty O O O O O O O O O O O O I 0 O O O 0 0 O O O 0

II. REVIEW OF RELATED LITERATURE . . . . . . . . . .

Cognitive Style Systems . . . . . . . . . . . . . . .
Cognitive Complexity . . . . . . . . . . . . . . .
Conceptual Systems . . . . . . . . . . . . . . . .
Cognitive Controls . . . . . . . . . . . . . . . .
Ipsative Analysis of Cognitive Functioning . . . .
Sigel's Work on Conceptual Styles . . . . . . . . .

Cognitive Style Systems Utilized in the Present Study
Field-Dependence-Independence . . . . . . . . . . .
RafleCtion‘ImpLIISiVIty s s s s s s s s s s s s s s
Intuition . . . . . . . . . . . . . . . . . . . . .
JungianEunction8.................

Other Research Relating Cognitive Style to Choice of
Major...................o...

c0nc1uaion8 O O O O O O O I O O O O O O O O O O O O C
III. METHODOLOGY AND ANALYSIS . . . . . . . . . . . . . . . .

Design . . .

sample..............‘..........
Procedure . . . . . . . . . . . . . . . . . . . . . .
Instruments . . . . . . . . . . . . . . . . . . . . .
Hypotheses . . . . . . . . . . . . . . . . . . . . . .
Method of Analysis . . . . . . . . . . . . . . . . . .

Summary . . . . . . . . . . . . . . . . .
Iv. RESULTS 0 O O I O O I O O 0 O O O O O O O O O O O O O O

TestonypotheslsI.................
TestOnypOthesisIa.o..............

iv

Page

l"

rar-
ric>¢DG>UIUIh)h'

3—0
N

12
12
13
15
18
18
21
21
27

40

47
56

56

56
58
60
64
75
79
80

82

83
91

Chapter

V.

Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test

of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of
of

Summary

Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis
Hypothesis

Summary . . . . .
Conclusions . . .

Discussion .

Limitations . . .
Implications for Future

REFERENCES .

Appendix

A.

B.

C.

D.

lb
lc
ld
le
lf
ls
lh
Ii
15
2

3

3a
3b
3c
3d
3e
4

4a
4b
4c
4d
4e

SUMMARY AND CONCLUSIONS

we...

0 O I O C O C O I O O O O O O O O O O O O O .
O O I O O C O O O O O O O O O O O O O O O O O
O O O O O O O O O O O I O O O O O O O I O O I

esearch

I O C C O O O O O O O O O O O O O O I O O O O

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, AND AGE FOR SAMPLE 1 WITH

AMERICAN COLLEGE TEST COMPOSITE SCORE . . . . . . . . . .

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, AND AGE FOR SAMPLE 1

WITHOUT AMERICAN COLLEGE TEST COMPOSITE SCORE . . . . . .

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, AND AGE FOR SAMPLE 2 WITH

AMERICAN COLLEGE TEST COMPOSITE SCORE . . . . . . . . . .

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, AND AGE FOR SAMPLE 2

WITHOUT AMERICAN COLLEGE TEST COMPOSITE SCORE . . . . . .

Page

93

94

95

96

98

99
101
102
104
105
105
108
109
111
111
111
112
112
115
115
115
116
116

119
119
121
121
122
123

125

130

134

137

141

Appendix Page

E. MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, WITH AND WITHOUT AMERICAN
COLLEGE TEST COMPOSITE SCORE BETWEEN DOMINANT JUNGIAN
TYPES IN SAMPLE 1 . . . . . . . . . . . . . . . . . . . . 144

F. MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE
MEASURES, GRADE POINT AVERAGE, WITH AND WITHOUT AMERICAN
COLLEGE TEST COMPOSITE SCORE BETWEEN DOMINANT JUNGIAN
TYPES IN SAMPLE 2 O O O C O O O O C O O O O O O O O I O O 147

6. RA" DATA 0 O C O O O C C I O O O I O O C O O O C O I O O O O 150
H. INTERCORRELATION BETWEEN THE FIVE COGNITIVE STYLE MEASURES

AND GRADE POINT AVERAGE WITH AND WITHOUT AMERICAN COLLEGE

TEST COMPOSITE SCORE IN SAMPLE 1 AND SAMPLE 2 . . . . . . 157

I. THE MATCHING FAMILIAR FIGURES TEST (MFF): INSTRUCTIONS,
SCORE SHEET, AND SAMPLE ITEMS . . . . . . . . . . . . . . 162

J. THE WESTCOTT INTUITION TEST (WIT): INSTRUCTIONS, TEST
WITH CLUES UNDEVELOPED, TEST WITH CLUES DEVELOPED . . . . 168

vi

LIST OF TABLES

Table Page

1. Composition of Sample 1 and Sample 2 by Sex and Number in
830!) Major Area and SpCCifiC Major s s s s s s s s s s s s s 62

2. Test of Hypothesis 1: Multivariate Analysis of Variance for
Mean Differences on Five Cognitive Style Measures, Grade
Point Average, and American College Test Composite Score
among Three Groups of College Major and between the Sexes . 8a

3. Test of Hypothesis 1: Step-down F Test for Ability of Five
Cognitive Style Measures, American College Test Composite
Score, and Grade Point Average to Discriminate between
theSexes.........................86

A. Test of Hypothesis 1: Step-down F Test for Ability of Five
Cognitive Style Measures, American College Test Composite
Score, and Grade Point Average to Discriminate among
Three Categories of College Major in Sample 1 . . . . . . . 87

5. Mean Grade Point Average and Mean American College Test
Composite Score between the Sexes . . . . . . . . . . . . . 87

6. Mean Grade Point Average and Mean American College Test
Composite Score among Three Categories of College Major . . 88

7. Analyses of Variance for Differences between the Sexes and
among Three Categories of College Major in Grade Point
Average and American College Test Composite Score . . . . . 90

8. Mean Scores on the Group Embedded Figures Test for Three
Categories of College Major . . . . . . . . . . . . . . . . 91

9. Test of Hypotheses la and lb: Analyses of Variance for
Differences among Three Categories of College Major and
between Sexes on the Group Embedded Figures Test . . . . . . 92

10. Confidence Intervals Based on Tukey Post Hoc Comparisons for
Hypothesis la: Differences among Three Categories of
College Major on the Group Embedded Figures Test . . . . . . 93
ll. Mean Scores on the Group Embedded Figures Test for the Two

sexe 8 O O 0 O 0 O O O I O O O 0 O O O C O O O C O O O O O O 94

vii

Table Page

12. Mean Time Scores (in seconds) on the Matching Familiar
Figures Test for Three Categories of College Major . . . . 94

13. Test of Hypotheses 1c and 1d: Analyses of Variance for
Differences among Three Categories of College Major and
between the Sexes on the Time Score of the Matching
Familiar Figures Test . . . . . . . . . . . . . . . . . . 95

14. Mean Time Scores (in seconds) on the Matching Familiar
Figure. TC.t for the Two SCX98 e e e e e e e e e e e e e e 96

15. Mean Error Scores on the Matching Familiar Figures Test
for Three Categories of College Major . . . . . . . . . . 96

16. Test of Hypotheses 1e and 1f: Analyses of Variance
Differences among Three Categories of College Major and
between the Sexes on the Error Score of the Matching
F.-111‘r Figure. Te.t e e e e e e e e e e e e e e e e e e 97

17. Confidence Intervals Based on Tukey Post Hoc Comparisons for
Hypothesis 1c: Differences among Three Categories of
College Major on the Error Score of the Matching Familiar
Figurcl T..t e e e e e e e e e e e e e e e e e e e e e e e 98

18. Mean Error Scores on the Matching Familiar Figures Test for
th. TWO SQXCB e e e e e e e e e e e e e e e e e e e e e e 99

19. Mean Number Correct Scores on the Westcott Intuition Test
for Three Categories of College Major . . . . . . . . . . 100

20. Test of Hypotheses 1g and 1h: Analyses of Variance for
Differences among Three Categories of College Major and
between the Sexes on the Number Correct Score of the
u..tc0tt IHCULLLOB TQ.‘ e e e e e e e e e e e e e e e e e 101

21. Mean Number Correct Scores on the Hestcott Intuition Test
for the Two Sexes . . . . . . . . . . . . . . . . . . . . 101

22. Mean Clue Use Scores on the Hestcott Intuition Test for
THICC Cttegariel at College “‘10: e e e e e e e e e e e e 102

23. Test of Hypotheses 1i and lj: Analyses of variance for
Differences among Three Categories of College Major and
between the Sexes on the Clue Use Score of the Hestcott
Intuition re't e e e e e e e e e e e e e e e e e e e e e e 103

24. Confidence Intervals Based on Tukey Post Hoc Comparisons
for Hypothesis 1i: Differences among Three Categories of
College Major on the Clue use Score of the Hestcott
Intuition Test in Sample 1 . . . . . . . . . . . . . . . . 104

viii

Table Page

25. Mean Clue Use Scores on the Hestcott Intuition Test for
th. TWO 5.3.8 0 O O O O O O O O O O O O O O O O O O O O O 104

26. Test of HypOthesis 2: Distribution of Dominant Jungian
Functions through Three Categories of College Major . . . 106

27. Extension of the Test of Hypothesis 2: Distribution of
Jungian Types (Attitude with Dominant FUnction) through
Three Categories of College Major for Sample 1 and 2
Calbined.........................107

28. Test of Hypothesis 3: Multivariate Analysis of Variance
for Mean Differences on Five Cognitive Style Measures,
Grade Point Average, and American College Test Composite
Score between Dominant Sensors and Dominant Intuiters . . 108

29. Mean Scores on Five Cognitive Style Measures, Grade Point
Average, and American College Test Composite Score
Obtained by Dominant Sensors and Dominant Intuiters . . . 109

30. Test of Hypotheses 3a, 3b, 3c, 3d, and 3e: Analyses of
Variance for Differences between Dominant Sensors and
Dominant Intuiters on Five Cognitive Style Measures,
American College Test Composite Score, and Grade Point
AVCERSQeeeeeeeeeeeeeeeeeeeeeeeeee110

31. Test of Hypothesis 4: Multivariate Analysis of Variance
for Mean Differences on Five Cognitive Style Measures,
Grade Point Average, and American College Test Composite
Score between Dominant Thinkers and Dominant Peelers . . . 112

32. Mean Scores on Five Cognitive Style Measures, Grade Point
Average, and American College Test Composite Score
Obtained by Dominant Thinkers and Dominant Peelers . . . . 113

33. Test of Hypotheses ha, hb, Ac, 4d, and be: Analyses of
variance for Differences between Dominant Thinkers and
Dominant Peelers on Five Cognitive Style Measures,
American College Test Composite Score, and Grade Point
Am.8.eeeeeeeeeeeeeeeeeeeeeeeee114

3a. Summary of Results on Multivariate Hypotheses and Univariate
Subhypotheses concerning Cognitive Style and Major . . . . 117

A. Means and Standard Deviations for the Five Cognitive Style

Measures, Grade Point Average, and Age for Sample 1 with
American College Test Composite Score

A1 Sample 1 Cell Size by Sex and Major . . . . . . . . . 130
A2 Group Embedded Figures Test . . . . . . . . . . . . . 130
A3 Matching Familiar Figures Time . . . . . . . . . . . . 131

ix

Table Page

A4 Matching Familiar Figures Errors . . . . . . . . . . . 131
AS Hestcott Intuition Test Correct . . . . . . . . . . . 131
A6 Hestcott Intuition Test Clue Use . . . . . . . . . . . 132
A7 American College Test Composite Score . . . . . . . . 132
A8 Grade Point Average . . . . . . . . . . . . . . . . . 132
A9 Age . . . . . . . . . . . . . . . . . . . . . . . . . 133

8. Means and Standard Deviations for the Five Cognitive Style
Measures, Grade Point Average, and Age for Sample 1
Without American College Test Composite Score

Bl Sample 1 Cell Size by Sex and Major . . . . . . . . . 134
32 Group Embedded Figures Test ... . . . . . . . . . . . 134
B3 Matching Familiar Figures Time . . . . . . . . . . . . 135
36 Matching Familiar Figures Errors . . . . . . . . . . 135
BS Hestcott Intuition Test Correct . . . . . . . . . . 135

O O O O O O O O 0 C 136
O O O O O O O O O O 136

86 Westcott Intuition Test Clue Use
B7 Grade Point Average . . . . . .

C. Means and Standard Deviations for the Five Cognitive Style
Measures, Grade Point Average, and Age for Sample 2 with
American College Test Composite Score

Cl ~Sample 2 Cell Size by Sex and Major . . . . . . . . . 137

C2 Group Embedded Figures Test . . . . . . . . . . . . . 137
C3 Matching Familiar Figures Time . . . . . . . . . . . . 138
Ch Matching Familiar Figures Errors . . . . . . . . . . . 138
CS Hestcott Intuition Test Correct . . . . . . . . . . . 138
C6 weatCOtt Intuition TCSt Clue Use a e s e e e e e e e e 139
C7 American College Test Composite Score . . . . . . . . 139
C8 Grade POint Average e e s s e e e s s s e e s e e e s 139

C9 ‘88 s e s s e e s e e e e e e e e e e e e s e e e s e 150
D. Means and Standard Deviations for the Five Cognitive Style

Measures, Grade Point Average,and Age for Sample 2

Without American College Test Composite Score

Dl Sample 2 Cell Size by Sex and Major . . . . . . . . . 141

DZ Group Embedded Figures Test . . . . . . . . . . . . . 141
D3 Matching Familiar Figures Time . . . . . . . . . . . . 142
D“ MatChing FaniliCr Figures Errors s e s e e e e s s e e 142
D5 Hestcott Intuition Test Correct . . . . . . . . . . . 142
D6 Westcott Intuition Test Clue Use . . . . . . . . . . . 143
D7 Grade Point Average . . . . . . . . . . . . . . . . . 143
D8 Age e s e e s s s e e e s e e e s e e e e e e s e e e 143

E. Means and Standard Deviations for the Five Cognitive Style
Measures, Grade Point Average, with and without American
College Test Composite Score between Dominant Jungian
Types in Sample 1

Table

E1

32

Page

Means and Standard Deviations between Dominant
Sensors and Dominant Intuiters . . . . . . . . . . . . 1&5
Means and Standard Deviations between Dominant
Thinkers and Dominant Feelers . . . . . . . . . . . . 146

F. Means and Standard Deviations for the Five Cognitive Style
Measures, Grade Point Average, with and without American
College Test Composite Score between Dominant Jungian
Types in Sample 2

F1

F2

Means and Standard Deviations between Dominant
Sensors and Dominant Intuiters . . . . . . . . . . . . 148
Means and Standard Deviations between Dominant
Thinkers and Dominant Feelers . . . . . . . . . . . . 149

H. Intercorrelation between the Five Cognitive Style Measures
and Grade Point Average with and without American College
Test Composite Score in Sample 1 and Sample 2

H1

82

H3

H4

Intercorrelations for Sample 1 without American College
COIIQBQ 1.3.: cupOU1te Scat. e e s e e e e e e s e e e 158
Intercorrelations for Sample 1 with American College
T..tcup°.it.scor.sseessaseeseeeees159
Intercorrelations for Sample 2 without American
COIIESCT38tcaW.1t. seat. 0 e e s s e s s e e e e s 160
Intercorrelations for Sample 2 with American College
TC'CCQPOOItCscorQeseseesasseessees161

xi

LIST OF FIGURES

Figure Page

I. Mean grade point average for three categories of college
”1“ O O O O 0 C O O O O O 0 O O O O O I O O O O O O O O 88

2. Mean American College Test composite score for three
categories of college major . . . . . . . . . . . . . . . 89

3. Mean scores on the Group Embedded Figures Test for three
C‘tfisarie. 0f 0011.89 “‘10: e e e s s e e e e e e e e e e 92

a. Mean time scores (in seconds) on the Matching Familiar
Figures Test for three categories of college major . . . . 9S

5. Mean error scores on the Matching Familiar Figures Test
for three C‘t.80r1.. 0f COIIQBC .‘jar e e e e e e e e e s 97

6. Mean number correct scores on the Hestcott Intuition Test
for three categories of college major . . . . . . . . . . 100

7. Mean clue use scores on the‘Hestcott Intuition Test for
three categories of college major . . . . . . . . . . . . 103

xii

CHAPTER I

INTRODUCTION

Background

The position that the campus counseling psychologist deals with
the developmental needs of students as opposed to remedial needs has
long been emphasized (Morrill, Ivey, & Getting, 1968: Getting, 1967).
Many universities have reorganized their student services offerings in
a manner such that the divisions frequently are clustered under a title
such as ”Student Development Services." In such organizations, remedial
needs continue to be met by existing units and personnel but the concept
is broadened to include some assistance in the process of living effec-
tively while obtaining a college education. Brown (1971) states

...that student development staffs must have input

into and involvement with the academic dimensions

of the collegiate experience. This could well be

one of their most important functions in the future.

However, it is not likely to be a function that is

going to be handed them freely, nor is it a function

they can usurp. It will be one that they will have

to earn by possessing clearly defined skills and
concepts (p. 48).

Sperry (1973), in a more recent but similar appeal, writes
The need to understand individual differences--
especially learning styles--is emerging as the

number one priority for the teacher and the

counselor (p. 483).

He also reported that researchers, in their efforts to improve

1

instruction, have discovered the importance of the context in which
learning takes place, particularly the interaction between the learner
and his environment-~a book, programmed unit, teacher, or counselor.
An important component of the interaction is the mode by which the
learner learns and how assistance is provided to him.

The goal of the present study is to explore some of the dimen-
sions related to and resulting from the cognitive development of
students--cognitive or learning style. This effort is made to provide
the counseling psychologist with additional understandings for assisting
the student to achieve maximum development during the college years.

The counseling psychologist thus will have more concepts and skills with
which to augment student development both when dealing with the student
directly and when acting as consultant to other university officials

who will in turn deal directly with the student.

Cognitive Style Defined

The term "cognitive style" or "learning style" is not one that
has a precise definition. While most terms in psychology are subject
to interpretation, cognitive style ranks on the lower end of the less-
precise-to-more-precise-definition continuum.

That consensus as to a precise and exact definition is lacking
is due in part to a lack of a single unifying theory which underlies
the phenomenon, though the work of proponents of a specific system may
be theory inspired, e.g”.the cognitive controls of the Menninger group
are rooted in psychoanalytic theory. Kagan and Hogan (1970) say that
the research on cognitive styles and controls has been conducted within

a broad theoretical base while Spitler (1971) says that cognitive styles

are more empirical observations of researchers than deductions from a
theoretical system. Ziegler (1963) criticizes the work of Hitkin, one
of the foremost researchers in this area, on the grounds that it has no
theory to which his work can be linked.

From a systematic review of the literature, there seem to be
three groups of studies to which the label ”cognitive style” has been
attached. The first most obvious group (Category I) includes those stud-
ies which employ measures labeled as estimates or dimensions of cognitive
style. In this category belong the work of Hitkin (Hitkin, Dyk, Faterson,
Goodenough, & Karp, 1962: Hitkin, Lewis, Hergzman, Machover, Meissner, &
Hapner, 1956) on fie1d-dependence-independence, the work of Hagan
(Hagan, Rosman, Day, Albert, a Philips, 1964) on conceptual tempo, the
work by a group of researchers (Gardner, Holzman, Klein, Linton, s Spence,
1959) at the Menninger Foundation on cognitive controls, the work of
Dieri (Bieri, Atkins, Drier, Leaman, Miller, a Tripoldi, 1966) on cogni-
tive complexity, and the work of Droverman (1960a, 1960b) on ipsative
analysis of cognitive functioning.

The second classification (Category II) includes those phenomena
which operationally use instrumentation similar to the cognitive style
researchers referred to above but which do not employ the actual term
”cognitive style.” Some of these researchers published their work be-
fore the ”cognitive style" label became popular. Such is the case with
the work of Thurstone (1966) and Mooney (1956) in their research on the
various aspects of closure. Other researchers chose not to use the
term. Such is the case with the work of Hestcott (1968b). The view of
the present author, which will be presented in Chapter III, is that

Hestcott's operational definition of intuition is in fact an operational

definition of cognitive style. Fengel (1971) used the Hestcott measure
and referred to it as a measure of ”cognitive-affective style.“ The
present author is unable to explain why the term ”affective” was added.
No other source has equated cognition with effect, nor does Pengel ex-
plain herself on this point.

The third classification (Category III) includes as measures of
cognitive style some phenomena more readily identified as personality
variables. Messick (1972) says that cognitive styles are frequently
implicated in personality and social functioning. As an example of
this, Johansson (1971) refers to Holland's (1966) six personality types
as cognitive styles. Cohen, Johnson, and Hanson (1971) define cognitive
style as basic level of intentionality. Snyder (1966) used the Sensa-
tion and Intuition scores of the Myers-Briggs Type Indicator (Myers,
1962) to assess students' cognitive ”horizons.” Similarly, Child (19651
in a study of esthetic judgment in college students, employed the Myers-
Driggs Type Indicator as a measure of cognitive style along with mea-
sures of the cognitive controls of the Menninger group, field-dependence,
and others.

With this categorisation in mind, it might be well to review
some definitions of cognitive style. De Ceeco (1968) uses this
definition:

Learning styles are personal ways in which

individuals process information in the course

of learning new concepts and principles (p. 75).

He also points out in common with others that these modes of processing
are considered to be relatively free of content and to cut across dif-

forest types of information.

Kagan and Kogan (1970) say cognitive style is an approach to
cognition and cognitive processes and then define those terms as follows:

...cognition stands for those hypothetical psycho-

logical processes invoked to explain overt verbal

and metor behavior as well as certain physiological

reactions. Cognitive process is a superordinate

term, subsuming the more familiar titles of imagery,

perception, free association, thought, mediation,

proliferation of hypotheses, reasoning, reflection

and problem solving (p. 1275). 1

Child (1965) operationally defines cognitive style by saying

People differ greatly one from another in their

orientation toward various aspects of experience

and the label cognitive style has come to be

applied to such variations (p. 483).

As has been stated, it is the aim of the present study to pro-
vide the counseling psychologist with information which can be utilized
primarily in an instructional setting. With this end in mind, De Cecco's
definition seems most appropriate for the present study since it ex-

presses specifically what the other two imply.

Purpose of the Study

The purpose of this study is to investigate the relationship of
cognitive style to college major in the belief that knowledge of cogni-
tive style will facilitate the role of the counseling psychologist as

consultant to students and faculty.

Benefits of the Study

 

Vocational theorists, among others, have pointed out that dif-
ferent characteristics are required for success in different occupations

(Super, 1953: Holland, 1966). Choice of major is closely related to

choice of occupation in that choice of major frequently leads to choice
of occupation and in that a similar process is involved in choice of
either. An understanding of the relation of cognitive style to college
major can provide the counseling psychologist with an additional tool
for assisting students in their search for the best major for them. The
input of one more characteristic relevant to the choice of major can in-
crease the accuracy of prediction formulae.

Brown (1971) has emphasized that it is important for the student
personnel worker to become more involved in the academic dimensions of
the collegiate experience, e.g. , as consultant to faculty. Knowledge
that cognitive style is related to college major can be used to assist
faculty in grasping its implications for instruction. That is, if
faculty are aware that a significant nuber of their students utilize
a particular learning style, this information can be put to use in their
instructional strategy.

Messick (1972) elaborates on the applicability of cognitive
style for instruction by suggesting that measures of cognitive style
could provide a more effective characterisation of the student than
achievement measures alone. In this regard he says,

These stylistic characteristics should have relevance,

although direct research evidence is admittedly very

scanty, not only for the course of individual learn-

ing in various subject matter areas, but also for the

nature of teacher-pupil interactions and of social

behavior in the classroom, the family, and the peer

stone (9- 110).

Other possibilities outlined by Messick include using cognitive style
as the basis for placement of students in classes, either bomogenously

or in special mixes, and matching students to faculty.

Mode of instruction can also be geared to cognitive style. For
instance, at least in science, instruction via an inductive method of
teaching (i.e., having the student discover the principles to be learned)
or through a more direct approach (i.e., one in which principles are
specified) can be related to cognitive style. The field-independent
(Hitkin et al., 1962; Witkin et al., 1954) and possibly reflective
students (Kagan et al., 1964) may well learn more efficiently with the
inductive approach, while field-dependent and impulsive students may
learn more efficiently with the more direct approach.

Messick tempers all his proposals by saying that more empirical
evidence concerning cognitive styles is needed. It is the aim of the
present research to further knowledge in this area by focusing on the
relation of cognitive style to college major.

Awareness of the range and variation of clients' cognitive
styles can be beneficial to the counseling psychologist in dealing
directly with students, individually, in groups, and in outreach pro-
grams. Carkhuff (1969) says that, while a great deal of emphasis has
been placed on the style which counselors bring to sessions with clients,
it is equally important to consider the client's style. A very important
component of ”style" is cognitive style.

Knowledge of client style including cognitive style can be
utilized in one of two ways. Either the counselor can gear his style to
the client's style or he can refer the client to another counselor whose
style is more in harmony with that of the client.

In summary, a knowledge of cognitive style provides a very use-
ful conceptual system from which the counseling psychologist can draw

in his role as consultant to faculty and administration for student

development, or in providing services to students directly through in-
dividual, group, or outreach programs. Also since nearly all concep-

tual systems make some assumptions about cognitive style (although many
are not very explicit) in a university setting where the cognitive do-
main is so emphasized, it seems especially important that such concep-

tualizing be made explicit.

Cognitive Styles and College ngors to be Investigated

Four cognitive styles were selected for use in this study.
They are field-dependence-independence (Hitkin et al., 1962; Witkin et
al., 1954), reflection-impulsivity (Kagan et al., 1964), intuition
(Westcott, l968bL and the four Jungian (Jung, 1971) functions of sensa-
tion, intuition, thinking, and feeling.

Sperry (1973) noted that there were three cognitive styles
which had received most attention and were therefore regarded as most
important--learning modality, learning tempo, and learning differentia-
tion. This statement provided the rationale for inclusion of learning
tempo (reflection-impulsivity) and learning differentiation (field-
dependence-independence). Learning modality refers to the sense through
which the student best learns. Since it seemed to have minimal rele-
vance for higher education, it was not included in the present study.

The Jungian functions were included in the study because they
were of particular interest to the present author, and provide a way
of relating cognitive "style" into a broader theoretical framework.
The instrument which currently is most widely used to assess Jungian
typology, the Myers-Briggs Type Indicator (MBTI) (Myers, 1962) enjoys wide

popularity in colleges and universities throughout the country, and

research has been conducted with it relevant to choice of occupation
and college major. The four functions are very similar to cognitive
controls and styles (Child, 1965).

The choice of intuition as a measure for this study was made
for two reasons. First, Westcott's (lafinfl measure for intuition yielded
scores for success in solving, in an inductive manner, abstraction prob-
lems and the amount of information demanded in seeking that solution.
The variation in performance on the task seems to provide most useful
information in keeping with the purposes of the study outlined above.
Second, the present author hoped to provide more data on the relation
of Westcott's measure to the Jungian notion of intuition.

College major will be categorized in the present study as majors
in the humanities, social sciences, and natural sciences. The inspira-
tion for this classification is found in the work of Goldschmid (1967)
who successfully was able to predict college major (humanities to
natural science dimension) on the basis of personality tests. While
Goldschmid used the humanities to natural science dimension, he felt

that the social sciences should be included in future studies.

Secondary Purpose of the Present Study

A secondary purpose of the present study proposes to correlate
the four Jungian functions to measures of cognitive style. It builds
in part on the work of Stanfiel (1966). He tested the hypothesis that
field-independence was related to the two Jungian attitudes of extra-
version-introversion. In two of three studies, he found support for
that hypothesis but found no relation between the Jungian functions and

field-dependence-independence. However, he did not take into account

10

Jung's concept of dominance of function, which says that one of the

four functions is more important and more fully developed than the

other three.

The present author hypothesizes that a relationship will be

found between dominant Jungian function and the cognitive styles which

are the subject of the present study.

Hypotheses

 

From the discussion above it is now possible to state the

hypotheses in the present study.

1.

3.

4.

S.

6.

9.

Students in different categories of college major will
differ among themselves and between sexes on the dimension
of field-dependence-independence.

Students in different categories of college major will
differ among themselves and between sexes on the dimension
of reflection-impulsivity.

Students in different categories of college major will
differ among themselves and between sexes on the dimension
of intuition.

The proportion of subjects divided on the basis of dominant
Jungian function will differ by category of college major.

Differences will exist in performance on the dimension of
field-dependence-independence between dominant Jungian
sensors and intuiters.

Differences will exist in performance on the dimension of
fie1d-dependence-independence between dominant Jungian
feelers and thinkers.

Differences will exist in performance on the dimension of
reflection-impulsivity between dominant Jungian sensors
and intuiters.

Differences will exist in performance on the dimension of
reflection-impulsivity between dominant Jungian feelers
‘nd thinkers s

Differences will exist in performance on the dimension of
less to more intuition between dominant Jungian sensors
and intuiters.

ll

10. Differences will exist in performance on the dimension of
less to more intuition between dominant Jungian thinkers
and feelers.

Summary

In this chapter, the position was advanced that the role of the
campus counseling psychologist may expand to that of consultant to faculty
on academic dimensions of the collegiate experience. It was proposed that
examining the relationship of cognitive style to college major would pro-
vide the counseling psychologist with useful information in fulfilling
that role and also in fulfilling his current role of assisting in student
decision making.

The problems associated with defining cognitive style were dis-
cussed and the definition of personal ways people approach learning
situations was adopted. Four conceptualizations of cognitive style--
all applicable to learning situations--were chosen for investigation
in the present study: field-dependence-independence, reflection-
impulsivity, intuition, and dominant Jungian typology. Secondarily,
an investigation of differential performance on field-dependence-
independence, reflection-impulsivity, and intuition among the dominant

Jungian functions was proposed.

ll

10. Differences will exist in performance on the dimension of
less to more intuition between dominant Jungian thinkers
and feelers.

Summary

In this chapter, the position was advanced that the role of the
campus counseling psychologist may expand to that of consultant to faculty
on academic dimensions of the collegiate experience. It was proposed that
examining the relationship of cognitive style to college major would pro-
vide the counseling psychologist with useful information in fulfilling
that role and also in fulfilling his current role of assisting in student
decision making.

The problems associated with defining cognitive style were dis-
cussed and the definition of personal ways people approach learning
situations was adopted. Four conceptualizations of cognitive style--
all applicable to learning situations-~were chosen for investigation
in the present study: field-dependence-independence, reflection-
impulsivity, intuition, and dominant Jungian typology. Secondarily,
an investigation of differential performance on field-dependence-
independence, reflection-impulsivity, and intuition among the dominant

Jungian functions was proposed.

CHAPTER II

REVIEH OF RELATED LITERATURE

The plan of this chapter is to present first a brief descrip-
tion of selected cognitive style systems which, though of theoretical
interest, were not utilized in the present study. It portrays the
process through which a neophyte student of cognitive style might
proceed and which the present author used in arriving at the concepts
utilised in the present study. Second, an overview of the cognitive
style measures used in the present study will be presented along with
research relevant to their relation to college major. Third, a review
of those studies which relate other measures of cognitive style to
college major will be presented. Finally, the implications of the

findings for the present study will be discussed.

Eggnitive style System;

mum Complexity

sieri (Bieri, 1971: nieri et al., 1966) is among those scholars
who view cognitive style as a mental set with which individuals construe
their environment. Bieri's work has focused on how highly differentiated

or complex those mental functions are and has been limited to the social

12

13

domain. His definition of cognitive complexity is

...the capacity to construe social behavior in a

multidimensional way. A more cognitively complex

person has available a more differentiated system

of dimensions for perceiving others' behavior than

does a less cognitively complex individual (Bieri

et al., 1966, p. 185).

The construct is evaluated by having a subject list ten people
with whom he is familiar. For these ten people he is to make ten ratings
of each such as "outgoing,” ”calm," ”cheerful," etc., on a Likert-type
scale from one to six. Those individuals who rate their subjects much
in the same manner, e.g., use mostly S's or 6's, are said to be cogni-
tively simple because they do not use much differentiation in their
rating, while those who use more of the range are said to be cognitively
complex.

The work of Bieri was not chosen for the present study because

it focused on a domain not as directly applicable to the learning envi-

ronment as the selected measures.

Conceptual Systems

bieri's system represents an approach which is specific in con-
ceptualization and application. 0n the other hand, the conceptual sys-
tens approach of Harvey, Hunt, and Schroder (1961) adopts a more perva-
sive view of cognitive functioning. The following statement by Schroder
(1971) would lead one to conclude that he equates cognitive functioning
withhpersonality.

'...personality is viewed as the style a person uses
in processing information about a given domain of

stimuli, e.g., interpersonal, political, or religious
.tm11 (Po 260) e

16

The earlier position of Harvey 23.21. (1961) does not eliminate psycho-
physical and functional determinants, but their position is still in
marked contrast to Bieri's. The Harvey gt 31. system concerns itself

not only with differentiation but also with hierarchic integration

which is considered a characteristic in the highest system of functioning.

The systems are four in number and the basis for differentiating
them is a concreteness-abstractness dimension with System I being charac-
terized by concreteness and System IV being characterised by abstractness.
While the description of characteristics of the four types is couched in
esoteric language, the following is a brief summation of them.

Each system is centered on a specific attribute which is said to
be characteristic of that system. When a specific system is operative
in an individual, events which are in harmony with it are said to be
bolstered and those which are not are said to be neutralized.

The central attribute in System I functioning is adherence to an
external standard and is said to be characterized by the following be-
haviors: forming standards quickly, rigidity, and overgeneralised sub-
mission to authority. The central attribute in System 11 functioning
is imposition of control and is said to be chsracterised by the following
behaviors: Aggression against the source of the control, flight from a
situation in which strong control is perceived, and taking an opposite
stance to the source of control.

The central attribute in System 111 functioning is mutuality
and friendship and is said to be characterised by the following behaviors:
self-evaluation based on others' opinions rather than one's own, sub-
mission to influence in an overgeneralized fashion, and seeking support

of others. System I and III functioning are said to be related and

14

The earlier position of Harvey 35 a}, (1961) does not eliminate psycho-
physical and functional determinants, but their position is still in
marked contrast to Bieri‘s. The Harvey‘s; 3;. system concerns itself

not only with differentiation but also with hierarchic integration

which is considered a characteristic in the highest system of functioning.

The systems are four in number and the basis for differentiating
them is a concreteness-abstractness dimension with System I being charac-
terized by concreteness and System IV being characterized by abstractness.
While the description of characteristics of the four types is couched in
esoteric language, the following is a brief summation of them.

Each system is centered on a specific attribute which is said to
be characteristic of that system. When a specific system is operative
in an individual, events which are in harmony with it are said to be
bolstered and those which are not are said to be neutralized.

The central attribute in System I functioning is adherence to an
external standard and is said to be characterized by the following be-
haviors: forming standards quickly, rigidity, and overgeneralized sub-
mission to authority. The central attribute in System II functioning
is imposition of control and is said to be characterised by the following
behaviors: Aggression against the source of the control, flight from a
situation in which strong control is perceived, and taking an opposite
stance to the source of control.

The central attribute in System 111 functioning is mutuality
and friendship and is said to be characterised by the following behaviors:
self-evaluation based on others' opinions rather than one's own, sub-
mission to influence in an overgeneralized fashion, and seeking support

of others. System I and III functioning are said to be related and

15

System III functioning resembles the functioning of field-dependents in
Witkin's system. The central attribute in System IV functioning is
autonomy and is said to be characterized by the following behaviors:
less susceptibility to social pressure, more ability to see self nega-
tively and take corrective action, and more exploratory behavior.

Assessment in the conceptual systems approach is done with a
sentence completion instrument which uses "This I believe" as its stem.
Reactions are solicited on such areas as friendship, guilt, religion,
and people.

While the conceptual systems approach in theory sees cognition
as all pervasive, its application is primarily to the realm of social
behavior. Also there seems to be a good measure of overlap between
functioning in the three systems, and their method of assessment seems
not to tap system specific functioning directly. For these reasons the
present author chose not to deal extensively with the conceptual systems

approach.

Cognitive Controls

The system Gardner, Holzman, Klein, Linton, and Spence (1959)
have‘developed is referred to as cognitive controls. In common with
the conceptual systems approach, this system attempts to explain a wide
range of human behavior, but utilizes several concepts as opposed to
one in achieving that end. Also the two systems differ in theoretical
origin. The conceptual systems approach, as well as that of Bieri,
derives its basic premises from Lewin's ideas on differentiation while
proponents of cognitive controls look to the neo-Freudians for their

inspiration. They postulate the controls as mediating links between

16

drives and situational requirements and have identified the following
six cognitive controls. The combination of them in an individual con-
stitutes his cognitive style.

1) Leveling-sharpening refers to a characteristic of individuals
to relate previous stimuli to present perceptions. The person who tends
to see present stimuli as relevant to past perceptions is referred to as
a leveler: the person who tends to see past perceptions as not relevant
to present perceptions is termed a sharpener. The test usually used to
assess this characteristic is the Schematizing Test developed by Holling-
worth. It is a test in which the subject views a series of square figures
of varying size, both in a presentation ordered by size and one in which
the squares are presented in random fashion.

2) Scanning refers to the number of times a subject looks at a
standard and a comparison object in a size estimation task. ~0ne test of
scanning requires the subject to adjust a disc of light to the size of
a disc in his hand. There are several discs which vary according to
color and weight. The other test requires the subject to estimate size
in circles which have been constructed to present optical illusions.

3) Field articulation is the same concept identified by Witkin
as field-dcpendence-independence. Gardner includes Thurstone's Con-
cealed Figures Test as a measure of this variable.

A) The constricted-flexible control principle governs the manner
in which a person handles conflicting or intrusive cues. The test used
is modeled on Stroop's Color Word Test in which interference is created
by requiring the subject to identify the color of the word "blue" when
it is printed in red. Those whose performance on the test is relatively
poor are referred to as constricted, and those who are relatively suc-

cessful are referred to as flexible.

17

S) Equivalence range concerns itself with the manner in which
an individual categorizes objects into broad or narrow categories or
ranges. The characteristic is measured by the Object Sorting Test, the
Photo Sorting Test, and two Thematic Apperception Test (TAT) cards.

The first two tests require the subject to sort objects and photos into
groups and then indicate the reasons he formed the groups he identified.
0n the TAT, subject's responses are scored on the conceptual distance
the stories moved from physical features in the TAT cards.

6) Tolerance for unrealistic experiences refers to the ability
of an individual to perceive something he knows to be unreal and accept
it as such. Many individuals perceive an unrealistic experience and
try to make it fit into the mold of previous perceptions. Optical illu-
sions provide the means of assessing this characteristic. One is a
situation in which two still photographs of a horse are progressively
manipulated so that they give the appearance that the horse is moving.
Subjects are assessed on this dimension by how long it takes them to
recognize that what they are seeing is an optical illusion.

Research utilizing cognitive control principles more frequently
deals with topics of relevance to mental health than to instructional
practice. This, coupled with the fact that Chung (1967) had utilized
four of the control principles in a study similar to the present study,
led the present author to utilize only the concept of field-dependence-
independence which had its origins independent of cognitive control

research.

18
Ipsative Analysis of Cognitive Functioning

The work of Broverman (1960a, 1960b) stands alone among cogni-
tive style researchers, not in conceptualization of specific styles
but in a unique method of assessing an individual's cognitive style.
Instead of using inter-individual differences to characterize an in-
dividual on a cognitive style dimension, relative intra-individual
differences are used. That is, the subject is given a battery of cog-
nitive style measures and then scores relative to the mean score of all
the tests are used to categorize the subject on a cognitive style dimen-
sion. Factor analysis of a number of cognitive style measures analyzed
using the intra-individual approach yielded a dimension Broverman refers
to as strong or weak automatization. Kagan and Kogan (1970) point out
that the measure strongly resembles Witkin's field-dependence-independence
but that Broverman's method of analysis makes comparison difficult.

It did not seem that Broverman's system was so rewarding that
there would be sufficient gain from leaving the mainstream of cognitive
style research to warrant such a move. It was for this reason that

Broverman's system was not utilized in the present study.

Sigel's Work on Conceptual Styles

Of the four systems described thus far, Sigel's work is the
most directly applicable to instructional settings. His work started
with an interest in the manner in which children organize phenomena in
the world around them. Originally (Sigel, 1953), he dichotomized that
mode of organization into perceptual or conceptual. The child who used

the perceptual mode formed concepts on the basis of sense data. The

19

developmentally more advanced child used the conceptual mode and con-
sciously imposed an organization on the material into deliberately
conceived categories.

Kagan, Moss, and Sigel (1963) refined Sigel's (1953) formulation
to include three categories~-relational, inferential-categorical, and
analytic-descriptive. A conceptual category is said to be relational
when the subject groups at least two objects on the basis of a perceived
relationship. For instance, he may identify in a picture two adults and
a child as family, or in a picture a horse and a wagon as a unit because
they "go together."

A conceptual category is said to be inferential-categorical
when the subject groups objects and each object is an individual instance
of the general category. That grouping is an inferred characteristic of
what he perceives. For instance, in a picture of a cow and a horse, the
two are identified as animals: a picture of a bed and a cradle are iden-
tified asthings to sleep in.

A conceptual category is said to be analytic-descriptive when
the subject groups one part of the stimulus field common to at least
two objects in it. His conclusion is based on his analysis of what he
perceives. For instance, if in a picture of three people two had no
shoes, he would say that two people had no shoes. Sigel, Jarman, and
Hanesian (1967) renamed the analytic-descriptive category analytic part-
whole to which the term descriptive-global was contrasted. A conceptual
category was said to be descriptive-global when the subject groups at
least two entire parts of the stimulus field. For instance, in a pic-
ture of three people in which two are uniformed and one not uniformed,

the subject may identify the uniformed people as such.

20

Sigel's instrument is the Conceptual Styles in Categorizing
Behavior Task (SCST). In it three line drawings are presented to the
subject who is asked to tell what is common in the drawings. They are
so constructed that any of the conceptual categories can be identified.
The conceptual categories which the subject identifies determine his
style. Those subjects who use more analytic concepts are said to be
more advanced.

The work of Sigel and his associates serves as a transition
between the systems just discussed and some systems used in the present
study. Kagan £5 31. (1964) used the Conceptual Styles Test (CST) in
the first of their series of studies. As Kagan's work progressed, he
found that those who formed analytic concepts were more reflective,
that is, they took longer to make a response. This began his work on
reflection-impulsivity, utilized in the present study. Also Kagan
ggngl. (1963) say they believe that there is a relation of the tendency
to form analytic concepts to what Witkin terms field-independence.

To acquaint the reader with specific systems to which the
label "cognitive style" has been attached, five systems have been
briefly described. While they all deal with the manner in which
people construe the world they perceive, the difference among them
seems to be the area of application. The systems of Bieri, and Harvey
.ggigl. have their application primarily in the world of social inter-
actions, the work of Gardner g£_§l, to mental health applications,
and the work of Sigel to educational instruction, the focus of the
present work. Broverman's work presents a unique way of assessing

an individual's cognitive style.

21

In the next section the cognitive styles chosen for the present
study will be discussed. First, an overview of each style will be
presented to acquaint the reader with the system. Following this
discussion, research linking that system to college major will be

reviewed.

Cognitive Style Systems Utilized in the Present Study

 

Field-Dependence-Independence

 

Overview Nitkin's work (Witkin et al., 1962; Witkin et al., 1954)
started nearly thirty years ago with an interest in perception. A
subject was placed in a perceptually embedding context, for instance,
in a tilted room which contained a chair which could also be tilted.
The subject was to orient himself upright.

Originally Witkin termed his construct "perceptual field-
dependence-independence." As research evidence built, he found that
intellectual as well as perceptual functioning was involved and so the
term "global-analytical" was applied. Further research which uncovered
dimensions of personality functioning such as body concept led to the
term "global vs. articulated" functioning. The current conceptualiza-
tion is that of "psychological differentiation." While the Witkin
terms have a specific historical significance, they are used inter-
changeably in the literature and that practice will be continued in
the present review.

Differentiation, a concept also utilized in biology, is related
to the degree of complexity of an organism. In psychology it is found

in the theory of Lewin and underlies other cognitive style systems as

22

well as Witkin's. Under this concept, that organism is considered to
be less developed which is less complex. When the concept is applied
to human growth, the infant is seen as less differentiated from his
environment than the older youth who experiences his body as separate
from the environment and develops a sense of identity.

Witkin's theory postulates that the level of a person's develop-
ment is equal to the level of his differentiation. Level of differen-
tiation is assessed by using one of three measures. The first is the
Body Adjustment Test (BAT) in which the subject is placed in a tilted
chair in a tilted room and adjusts his chair until he perceives he is
in an upright position. The second is the Rod and Frame Test (RFT).
In this test the subject is placed in a totally darkened room with a
luminous frame which encloses a luminous rod. Both the rod and the
frame are adjustable. The experimenter varies the tilt of the frame
and the rod, and the subject then adjusts the rod to what he believes
is the upright position.

The third measure is the Embedded Figures Test (EFT). In this
test the subject is to identify a geometric figure which has been em-
bedded in a maze of geometric designs.

Kagan and Kogan (1970) have reviewed the literature on field-
dependence-independence extensively. They conclude that in Hestern
cultures the EFT, EFT, and BAT all measure the same phenomena. There
is evidence that in Nigerian culture these may not be valid measures
and, therefore, possibly also in other non-Western cultures. The
position of a person on the continuum from field-dependence to field-
independence is relatively stable over time, although as children

develop, they become progressively more field-independent. Evidence

23

that geriatric groups are more field-dependent suggests that perhaps
there is a peaking of this characteristic in mid years and then a
decline, the peak possibly occurring in the late thirties (Witkin,
Oltman, Raskin, & Karp, l97l).

Perhaps the area of greatest controversy concerning the work of
the Witkin group centers on the relation of analytic vs. global function-
ing to general intelligence and verbal ability. Witkin gt 21. (1962)
point to research which links performance on the three measures of field-
dependence-independence and performance on a cluster isolated through
factor analysis--the object assembly, picture completion, and block
design portions of the Weschler Intelligence Scale for Children (WISC).
These three WISC subtests are believed to measure the ability to over-
come an embedding context as do the measures of field-dependence-
independence. Since there were two other verbally oriented clusters of
WISC subtests isolated which did not require the ability to overcome an
embedding context, Witkin's group concludes that verbal ability is not
relevant to the dimension of psychological differentiation.

Ziegler (1963) has contended that the Witkin group, in arriving
at this conclusion, has ignored research which suggests that there may
be a link (a general intelligence factor) between verbal ability and
analytic-global functioning. Indeed, Kagan and Regan (1970) cite stud-
ies which have found significant correlations between verbal ability and
analytic-global functioning. They conclude that the relationship between
verbal ability and analytic-global functioning is not substantial since
only a few researchers have found it, and there is more evidence to the
contrary.

Analytic-global functioning has been related to other concepts

involving perception. Such is the case with speed of closure and

24

flexibility of closure identified through factor analysis by Thurstone
(1944). witkin 35 21° (1962) discusses the relationship at length and
points to research which strongly links overcoming an embedding context
to flexibility of closure but not speed of closure. The work of Mooney
(1954) on closure seems to involve both speed and flexibility of closure
and it, therefore, is related in part to Witkin's work.

Witkin 35 21. (1962) comments on the apparent duplication of
effort.

In a period of extensive research on cognitive styles

it is not surprising that there should be overlap or

even identity among the cognitive styles established

by different investigators. There is clearly a need

for studies aimed at codifying these cognitive styles

(p. 80).

To the best of the present author's knowledge, no one has seriously
undertaken what Witkin has recommended.

There is evidence that field-independent individuals produce
more sophisticated line drawings of human figures than field-dependent
persons. witkin makes the inference from these data that field-
independent persons have a more differentiated body concept.

The personality variable of activity-passivity has been posited
by the Witkin group as relating to field-dependence-independence. In
only one study, which investigated posture of ten year old boys, did
the hypothesized relationship receive confirmation. Also there has been
evidence (using projective tests) to show that field-independent sub-
jects used more specialized defenses such as isolation and intellectual-
ization as opposed to repression and denial used by field-dependent sub-
jects. Field-dependent subjects also have more uncontrolled aggression.

Socially, field-dependents have been found to exhibit more

other directed (passive-dependent) behaviors while field-independents

have been found to be less influenced by their social environments.

25

Witkin cites strong correlational evidence that field-dependent
mothers foster field-dependence in their sons, but other research in
this area has been confusing as to the influence of parents in fostering
the analytic-global function in their children.

Except in four to eight year old groups and geriatric popula-
tions, males have been found to be significantly more field-independent
than females, though the difference is relatively small. However, in
some college papulations, males and females have scored the same. The
determinants of this observed difference have yet to be discovered with
certainty, but cultural influences as well as spatial ability seem to
be involved.

Further evidence for the validity of the global vs. articulated
dimension has been collected in cross-cultural studies. Temne tribes
in Sierra Leone, Africa, and Canadian Eskimos were subjects. The Temne
have strict child-rearing practices while the Eskimos allow their women
and children more autonomy. Also, the Eskimos live in a bleak and barren
environment which requires a greater degree of field articulation. Since
field-independence is associated with more moderate child-rearing prac-
tices, as well as greater need for field articulation, one would expect
the Eskimos to be more field-independent than the Temne. Research
evidence supports this.

Some of Hitkin's earlier statements imply that it was more
desirable to be field-independent. Kagan and Kogan (1970) challenge
this notion saying that in today's climate the need may well be as
great for those who are socially more accommodating (field-dependents)
as for those who are able to resist the influence of others (field-
independents). Witkin ggflgl. (1971) have clarified their position

which is now in basic harmony with that of Kagan and Kogan.

26

Field-dependence-independence is perhaps the most thoroughly
researched of all the cognitive style systems. In this section it has
been shown that the dimension has been effective in differentiating a
wide range of phenomena from an individual's perception of his body
image to differentiating cultures from one another. Against this back-
ground of research evidence, the argument of Ziegler (1963) that the
dimension lacks a foothold in an established theory and may be no more
than a factor of general intelligence seems pale. 0f the dimensions
chosen for the present study, field-dependence-independence has been
shown to be the most successful in differentiating college majors.

That evidence is presented in the next section.

Research Relevant to Field-Dependence-Independence agg;§ollege Major
De Russy and Futch (1971) investigated the relation of field-dependence-
independence to a humanities or natural science orientation. They ad-
ministered the Embedded Figures Test to thirty-two subjects~-eight males
and eight females in the natural sciences, eight males and eight females
in the humanities. They found males were significantly more field-
independent than females and that science students were significantly
more field-independent than humanities students. There were no inter-
action effects. The authors hypothesized that training in geometry
might explain why science students were more field-independent.

Chung (1966), in a study to be reported in more detail later
in this chapter, found that a group measure of field-dependence-
independence discriminated science from humanities majors much in the

manner as in the De Russy and Futch (1971) study.

27

Barrett and Thornton (1967) tested the hypothesis that engineers
were more field-independent than the general population. They adminis-
tered the Rod and Frame Test to forty-six male engineers and technicians
employed by a midwest aerospace firm and to eleven non-engineering male
students. The engineers and technicians were more field-independent
than either the eleven college students or Witkin's standardization
sample. There was no significant difference between Hitkin's standard-

ization sample and the college students.

Reflection-Impulsivity

 

Overview The dimension of reflection-impulsivity is concerned with
the length of time subjects reflect on the solution to a problem where
the solution is not absolutely clear. As has been pointed out, its
development was an outgrowth of the work of Jenna Kagan (Kagan, et al.,
1963; Kagan et al., l96h) on the analytic attitude in children. Most
subsequent research has focused on children.

Since most of the research has focused on children, it might
be questioned why it is being used with an adult population. The
rationale for its use is that the variation which is found in children
is also found in adults (Burgbacher, 1973: Gatewood, 1972). Specifi-
cally in reference to the present study, it is also reasonable to be-
lieve that science majors who are oriented to quantitative precision
would tend toward a more reflective attitude than social science and
humanities majors who'are oriented to a more verbal and less quantita-
tively oriented methodology.

Reflection-impulsivity is usually measured using the Hatching

Familiar Figures Test (MFF), a test in which the subject is presented

28

a standard line drawing and eight variants. He is to identify the vari-
ant which duplicates the standard. Performance is measured by time to
first response and errors made before identifying the correct variant.

The research on this dimension is much less extensive than that
on the dimension of field-dependence-independence. This is particularly
true in the area of personality variables such as self-concept, etc.
Kagan and Regan (1970) cite the following research relevant to the
dimension. 7

1) Even for young children the dimension of reflection-
impulsivity has been found to be reliable. In three studies the lowest
test-retest correlation for the response time score was .31 (over 2%
years) and the highest .70 (over ten weeks).

2) Subjects have been found to be impulsive or reflective on
other tasks from similar perceptual tasks to an interview situation. In
the interview situation, the time a subject took to respond to a question
of a general nature was recorded and correlated with response time on the
HEP. The Pearson product moment correlation was .31.

3) Reflective children have been found to recall words in a
serial recall list better than impulsive children under conditions of
both low and high anxiety.

h) Reflective first grade children are better able to recognize
spoken words than impulsive children. These same children served as
subjects in a study one year later and the reflective children made
fewer errors in reading a paragraph of English prose than did the imp
pulsive children. Reflective children made fewer errors on tasks of
inductive reasoning (e.g., responding to a question such as what barks,

has fur, and walks on four legs?) than did impulsive children.

29

5) Reflective children made more eye movements in the first six
seconds when they compared a standard with a variant than impulsive chil-
dren. When the standard and variants were put behind frosted glass and
it was necessary for each child to remove the glass, reflective children
removed more of the glasses and examined the variants more carefully.

6) The characteristic of reflection-impulsivity can be modified.
Four short-term experimental studies are cited in which the characteristic
was modified in some way (e.g., in time to first response, but not errors)
through direct training or modeling. In a fifth study, first grade
teachers and students were categorized as reflective or impulsive thinkers
at the beginning of the school year and at the end. Students did change
in the direction of the tempo of their teachers. Therefore, evidence
thus far presented has suggested that the characteristic of reflection-
impulsivity is relatively stable over time and tasks but is somewhat
modifiable if there is an intent to modify.

Only one study, Gatewood's (1972), has investigated the relation
of reflective or impulsive individuals to choice of college major, and

it is reviewed in the following section.

Research Relevant to Reflection-Iggulsivitz and College Major Gate-

wood (1972) investigated the relationship of two measures of cognitive
style to grade point average, academic aptitude, and college major. The
cognitive style measures were the HF? and Sigel's Conceptual Styles in
Categorizing Behavior Task (SCST). The measure of academic aptitude was
the American College Test (ACT), and college major was categorized as
either ”arts” or "sciences.” No criterion was reported, however, for

making this categorization, and only 391 of the subjects in the study

30

were classified as either arts or science majors for purposes of in-
vestigating hypotheses relating to science and arts students. Subjects
for the study were 129 junior college sophomore males who were paid
volunteers.

None of the seven hypotheses tested in the Gatewood study were
substantiated by the data. The present author feels that failure to
uphold hypotheses of relationship of cognitive style to college major
was more due to the age of the population and the fact that not all
subjects could be used to test the hypotheses. Gatewood cites data
which show that only 501 of junior college students matriculate at four
year institutions and that they tend to declare a given major more on
the basis of prestige than ability. Furthermore, because not all sub-
jects could be classified as analytic vs. non-analytic or impulsive vs.
reflective, the number used for the statistical tests for these hypo-

theses was smaller than that used for the other tests.

Intuition

Overview Hestcott's (1968b) work on intuition started with the simple
observation that some people get the point more quickly than others.
This seemingly obvious statement triggered questions such as, Do people
in fact get the point more quickly? If so, to what degree do they vary?
what are the implications of this variation?

A study of the psychology of intuition has its roots in philoso-
phy. The classical position on intuition is that it is an avenue by
which knowledge gained is characterized by non-sensory attainment of

knowledge, the knowledge being non-empirical and non-verifiable. The

 

31

knowledge need not come as the result of prior intellectual endeavor,
but it frequently does.

Hestcott points out that there are basically two opposing views
concerning intuition. They differ on the scope of the knowledge attained
in this manner. The pure intuitionists hold that the knowledge gained
through intuition is that of ultimates, while those of the positivistic
school hold that the knowledge is more limited and immediately useful.
An example of the former is that God is to be glorified and of the
latter is that events have causes.

westcott reports three views on intuition in psychology. The
first view he terms the Verstehenist (or global understanding) position.
This position holds that intuition is the step from inference to under-
standing. It is akin to what is referred to among psychotherapists as
clinical as opposed to empirical understandings. The clinician suddenly
achieves ”insight" into the dynamics of the client, though he may not be
able to trace in a one-two-three fashion just how he came to the conclu-
sion. The non-intuitively-oriented empiricist, on the other hand, de-
mands hard data to form a conclusion.

The second position (Jung, 1971) on intuition deals not so much
with it as a form of mystical knowledge but as personality trait found
in all people. Jung refers to intuition as perception by the unconscious
as opposed to perception through the senses. Through the intuitive pro-
cess Jung believes the intuiter perceives the generalities and implica-
tions while a sensing oriented person perceives the physical properties
of the object or event. For instance, an intuiter may be likened to an
abstract artist who is portraying the implications of his subject while

the sensor would portray a replica of the physical properties of his

32

subject. Jung has, therefore, taken the mystery out of classical intui-
tion by saying that it is just as much a function of human behavior as
is perception by the senses. He feels that the reason people are not
more aware of the function is that it is suppressed through societal
pressure. His reasoning is that a person who has a constitutional pre-
disposition toward intuition and develops it will likely be regarded as
a dreamer and, therefore, a social outcast.

Jung's position links the Verstehenist position with the third
position which can be termed the inference position. Hestcott reports
that those who aspire to the inference position hold that intuition is
a special case of inference. It differs from the Verstehenist position
in that knowledge is gained through definite sensory channels and cogni-
tive manipulations but that some parts of the process--a specific manip-
ulation or mediating link-~may be obscure.

It is the latter position which Hestcott holds and upon which
his work has been based. When Westcott points to the research dealing
with the inference view of intuition, he points to that body of research
which others could readily term cognitive style. He says the research
is

...catalogued under the headings of learning,

perception, concept attainment, problem-solving,

and so on, all occurring under less than optimum

conditions. we are also directed to a literature

not yet so large, but rapidly growing, which is

concerned with personality and attitude differences

in the acquisition of knowledge...(Hestcott, 1968b,

p. 189).

From this, it can be concluded that Hestcott treats intuition as cogni-

tive style which focuses on the amount of information an individual

needs to solve a "cognitive riddle.”

33

Westcott believes that one application of his work on intuition
is in instructional practice in situations where information is lacking
or apparently lacking. Such is the case with language instruction.
Some students must extract the rules through a mental osmosis process,
an intuitive process, while others learn best through ”active” teaching
of the rules. In graduate education the apprentice system is often ad-
vocated. It is a system in which the pupils learn informally, at the
feet of the master so to speak, and it seems geared to an intuitive
thinker while non-intuitives may gain more from a more formal approach.
Hestcott's overall contention is that cognitive style should influence
instructional practice, and at every level-nursery school through
graduate school.

Hestcott's (1968b) operational definition of intuition is

...the event which occurs when an individual

reaches a conclusion on the basis of less

explicit information than is ordinarily re-

quired to reach that conclusion (p. 100).

The instrument (Westcott Intuition Test, HIT) which he uses to
measure the concept consists of a series of verbal and numerical ab-
straction problems with five clues to the solution of the problem. The
clues are so arranged that the subject uncovers them one at a time and
.in sequence. The subject is to use as few clues as possible. The correct
response is that which is consensually valid when all the clues are known.
The dependent variables are clue use, number correct, and efficiency or
the ratio of the number correct to clue use. The efficiency score is
rarely used.

Hestcott has produced considerable research on characteristics

associated with differential performance on the "IT. Subjects for his

34

study were several groups of college students which he terms samples.
The samples he used for a specific study varied from study to study.

His first studies were correlational in nature comparing measures
of academic achievement and aptitude with HIT scores. His major finding
concerning academic aptitude was that the clue use score was negatively
related to both the verbal and numerical scores of the Scholastic
Aptitude Test (SAT), that the number correct score is positively related
to both academic aptitude and achievement, and the efficiency score is
related to SAT Mathematical Scores. Since the correlation coefficients
between HIT and the aptitude scores were generally of a low magnitude
and there were virtually no significant coefficients when course grades
were compared with HIT scores, Hestcott's overall conclusion is that
neither academic achievement nor aptitude are much related to intuitive
thinking. This finding coincides with the findings of other cognitive
style researchers who posit that cognitive style is for the most part
independent of intelligence.

After failing to find significance using correlational techniques
with personality measures of impulse expression, and flexibility (adapted
from the Vassar College Attitude Inventory), and manifest anxiety (Taylor
Manifest Anxiety Scale), Hestcott turned to using subjects whose perfor-
mance was extreme on the measures of clue use and number correct. Ex-
treme was defined as any score which was plus or minus one standard
deviation from the mean on the two measures. (Sometimes the criterion
was a .75 s.d.) Sometimes extreme scorers on clue use and number correct
were studied, but more often four quadrants were established for those
who were extreme on the two measures combined. Thus those low on clue

use and high on number correct were termed ”intuitive thinkers)” those

35

high on clue use and high on number correct were termed ”careful suc-
cessesz” those low on clue use and low on number correct were ”wild
guessersg” and those high on clue use and low on number correct were
”careful failures.” There were from six to seven percent in each of
the groups selected from the subjects used in the correlational studies
cited previously.

One study cited by Hestcott involved ratings by faculty members
of extreme performers on the efficiency score. An overall rating of
quality of performance failed to produce significant differences in the
two groups. EXtreme performers in the four categories mentioned above
were rated on items concerning ”quality of thinking," "grasp of concepts;'
”conscientiousness,” and ”involvement.“ Again there were no significant
differences.

Next a series of studies were undertaken to discover personality
correlates of the extreme scorers. The Allport-Vernon-Lindzey Study of
values yielded essentially identical profiles for the four groups.

Use of other instruments yielded more positive results. However,
the manner in which significant results were found was in many cases less
than straightforward, and to report in detail the methodology and results
in the present study would unnecessarily belabor the point. Instead the
methodology will be reported for one study and brief mention will be made
of the instrumentation used in other studies and Hestcott's overall con-
clusions. flestcott acknowledges that other methods of data analysis
serve to generate hypotheses rather than come to definitive conclusions
about personality traits of extreme scorers on the HIT.

One instrument which Hestcott used was the California Psychological

Inventory (CPI). There were no significant differences among the four

36

groups on the scales established by the CPI authors. At this point
Hestcott selected individual test items which discriminated one group
from the other three, or which discriminated high number correct from
low number correct groups and high clue use from low clue use groups.
Subjects from this study were three samples of the college students
mentioned above. Items were said to discriminate if they did so in any
of the three samples, and in fact there were few items which discrimi-
nated in more than one sample. So if item 58 discriminated intuitive
thinkers from the other three groups in the second sample but not the
first and third samples, it was put in the pool of items which discrim-
inated intuitive thinkers from the other three groups. Those items
which were found to discriminate were then grouped on the basis of
psychological coherence. Descriptions of the four groups were devel-
oped from this information.

Other instruments which were used were the Allport-Vernon-
Lindsey Study of Values, the instrument previously described which
measured impulse expression, flexibility, and manifest anxiety responses
to a six question open-ended interview situatiom,and an adjective check
list of indeterminate origin.

Using the methodology and instrumentation mentioned above,
Westcott arrived at the following conclusions concerning extreme per-
formers. He concluded discussion of characteristics of the intuitive
thinkers in the following manner:

This is a coherent picture of self-determining

persons, willing to deal with the world on its

own terms and unwilling to be swayed by social

pressures. Their goals and their aspirations

are high, but are often quite different from

what most people seem to want (Westcott, 1968b,
p. 143).

37

The wild guessers are described as socially complex and involved,
but their involvement seems clouded with cynicism, rigidity, and bull-
headedness. They seem not to have a firm grasp on reality or to organize
or consolidate their efforts toward achieving a goal.

The careful successes, Hestcott (1968b) describes as

...conservative, cautious, somewhat repressive

people who function well in situations where

expectations are well established and well met

(p. 147).

The careful failures are described as conservative, authority-
oriented individuals who seemingly adopt the conservative stance in a

desperate effort to attain stability in a world which they little under-

stand and are unable to control.

Research Relevant to Westcott's Conception of Intuition to College Major
The present author could find no studies relating Hestcott's measure of
intuition to college major. However, westcott (1968a) did compare scores
on the HIT to scores on the Strong Vocational Interest Blank.

The selection of vocation and college major is thought to be
closely parallel, though not identical in all cases. However, a person
aspiring to be a mathematician is very likely to major in mathematics.
That selection of college major and vocation is closely parallel also
seems to be the view of Holland (1966) who reports characterizing univer-
sity environments by major as one method for categorizing vocational en-
vironments. It is for this reason that the present author will report
research relating cognitive style to vocational choice when research

relating cognitive style to choice of major is unavailable.

38

Westcott's (1968a) subjects were ninety-five college female
seniors. They were administered the NIT as freshmen and as seniors.

He then formed two samples from this group--those who were extreme
performers on the HIT either as freshmen or as seniors. There was
considerable overlap in these groups. The entire sample was adminis-
tered the 1945 edition of the Strong Vocational Interest Blank for
Men (SVIB-M) .

As in previous studies, correlational analysis using the entire
group failed to produce significant coefficients.

Two other methods were used to analyze the data. In each
method thirty-two of the original ninety-five subjects were divided into
the four groups--intuitive thinker, careful success, wild guesser, or
careful failure. In the first method each subject was assigned a rank
from one to four on each individual scale of the SVIB-M, depending on
the closeness of her interest pattern to that of each occupational pro-
file. The individual scores were averaged by group on each individual
scale and were compared to the mean score for the other three groups via
t test. Thus on the physician scale the rank of intuitive thinkers
might differ from that of the other three groups. It appears that this
procedure required multiple t tests on the same population and was
therefore inappropriate.

The second procedure took the group rank of the subjects in
each of the four groups on each occupation in one of the SVIB-M occur
pational clusters. Thus on the physician scale the intuitive thinkers
might rank four indicating their interests were the most similar.of the
four groups to those of physicians, wild guessers might rank two, etc.

This procedure was followed for each occupation in the cluster. Then

39

the ranks for each group were added and rank chi-square analysis was
performed. The procedure was repeated for each occupational cluster.

From this analysis Hestcott draws the following conclusions.
The intuitive thinkers show more interest in diverse occupations.

They share the interests of abstract scientists and those who perform
manual labor. They have least interest in business and social service.

The wild guessers dislike the vocation of music teacher and
salesman and are interested in a cluster of mathematical subjects.
They are most interested in the professional service occupations.

The careful successes prefer the vocation of music teacher and
librarian and the school subjects of geometry and civics. They have
interest in practical manual vocations and are interested in business
and social service occupations.

The careful failures produced the fewest findings. They show
interest in the vocation of clergyman and have the least interest in the
vocation of politician. They share more interests with people in the
professional services and least with people in business.

Overall, Hestcott (1968a) concludes

The significance of the particular preferences and

dislikes which distinguish the groups is not en-

tirely clear, of course, but those described above

are quite congruent with the earlier descriptions

offered (9. 19).

In view of the fact that Westcott had to use somewhat extreme
measures to find correlates of intuitive thinking and that he admits
that the fruits of his efforts are more suggestions than definitive

results, it is incumbent upon the present author to justify use of this

particular measure for further study.

40

Originally a comparison of the theoretical and operational
definitions of intuition by Jung, Myers (1962) (as expressed by the
Myers-Briggs Type Indicator), and Hestcott was of interest to the
present author. However, Nestcott (1968a) reported essentially nega-
tive correlations between intuition as measured by the HIT and the
Myers-Briggs Type Indicator (MBTI). However, when_the present author con-
sidered Westcott's work more fully, the cognitive style implications
became more apparent and more important. As has been mentioned above,
Hestcott's comments concerning the importance of the manner in which
information is presented at all levels of instruction provided suf-
ficient cause in the mind of the present author for further investi-

gation.

Jungian Functions

Overview In the discussion in the previous section, Jung's thoughts
on intuition were presented. In this section his ideas on psychologi-
cal types will be discussed-that part of his work in which his thinking
on intuition was first presented. In a new collection of his works
(Jung, l97l). Jung explains the rationale for classifying people by
psychological type. He said he developed his theory of type

...to provide an explanatory basis and theoretical

framework for the boundless diversity that has

hitherto prevailed in the formation of psychologi-

cal concepts (p. 555).
He points out that type has been a concern with which even the ancients
have dealt. He says his formulation is grounded in a purely psychic

foundation whereas other formulations have been built upon a foundation

in physiology.

41

Jung wrote that he developed his particular system empirically,
that is, in trying to explain the diversity of behavior in his patients,
he discovered that they had characteristic orientations to their environ-
ments. Some were oriented to the world outside themselves (extraverts),
some more to the forces within (introverts). However, he discovered
that there remained much diversity to be explained in the behavior of
extraverts and introverts. The explanation lay in the fact that indi-
viduals differed in their use of functions which he identified as
thinking, feeling, sensation, and intuition. He argued that while the
names of the functions might be changed and that other formulations
might be developed, his four were the most practical. Research by Cook
(1970) and Gorlow, Simonson, and Krauss (1973) has given empirical
support to the existence of a typology as posited by Jung.

The function tells which of four tools the person typically
uses in experiencing his world. Some prefer to rely most on data from
the senses, and are, therefore, said to be sensation oriented. Hhat
they perceive by the five senses becomes the basis for their actions.
Others prefer to use intuition. While they perceive with their senses,
they do not focus on the object itself, but rather on its implications
and possibilities. Since these two functions are perceptive functions,
Jung refers to them as irrational, that is, not concerned with judgment.
The judging or rational functions are thinking and feeling. Those who
are disposed to use thinking need a rational basis in drawing conclu-
sions, and those disposed to feeling make judgments on the basis of
what is valued at an emotional level.

Jung (1971) characterizes the interrelation of the functions

in this manner:

42

Sensation establishes what is actually present,

thinking enables us to recognize its meaning,

feeling tells us its value, and intuition points

to possibilities as to whence it came and whither

it is going in a given situation (p. 540).

The spice and variety of individual differences is due, in
Jung's view, to a differential weighting, so to speak, of the functions
in a given individual. That function which is most predominant and most
used is referred to as the dominant function. The function which is
second in time is referred to as the auxiliary function. If the dominant
function is perceptive (i.e., sensing or intuition), then the auxiliary
must be judgmental (i.e., thinking or feeling). The other functions may
come into play in a given instance but generally they are less developed
and more in the unconscious, particularly that function which is opposite
the dominant. For instance, if thinking is dominant, then feeling is
most undeveloped, and the auxiliary must be either sensing or intuition.

The Jungian formulation thus established a system by which an
individual's characteristic orientation to the world about him can be
discerned. Jung (1971) seemed to establish a linkage between the per-
sonality types and cognitive style by the statement:

It (introversion) is therefore oriented by the factor

in perception and cognition which responds to the

sense stimulus in accordance with the individual's

subjective disposition (p. 374).
That part of the statement,'that introversion is oriented by a factor in
perception and cognition3'provides a basis for linking the personality
types to cognitive style.

Myers (1962) also indicates that the Jungian type can be con-
sidered cognitive style.

Preference type is the product of the person's con-

scious orientation to life, his habitual, purposeful

ways of using his mind,chosen because they seem to
him good and interesting and trustworthy (p. 74).

43

Sundberg's (1965) statement clearly indicates he views the MBTI
as a measure of cognitive style.

Purely as a potential research procedure for

getting at individual differences in cognitive

preferences, it would seem the Indicator would

merit a great deal of attention from cognitive

theorists (p. 325).
It is precisely for the purpose of "getting at individual differences in
cognitive preferences" that the MBTI has been employed in the present
study.

It is on similar bases that Child (1965) made the statement that

the Jungian typology could be included in the category cognitive style.

The present author has reached the same conclusion.

Research Relevant to Jungian Typolggy and Choice of Major Myers (1962)
and Reynolds and Hope (1970) point to research which suggests that choice
of major is relevant to Jungian typology and the intent of this section
is to review those studies. Most studies are reported by Myers based on
findings arrived at through the use of the MBTI.

The MBTI has four scales-three reflecting the Jungian dimensions
[extraversion-introversion (E-I), sensing-intuition (8-H), and thinking-
feeling (T-Ffl and a fourth called judging-perceiving (J-P) which is
used to identify the dominant life style attitude (the extraverted pro-
cess). If a subject chooses more items related to needing conclusions
rather than to observing phenomena, he is identified as J on the J-P
dimension, and it is taken to mean that one of the judging functions
(either T or P) will be the manner in which that individual interacts

with the world. In the case of extraverts,that dominant function will be

44

displayed prominently to the world as it is used to facilitate inter-
action with the environment. However, introverts are said to display
their auxiliary in their everyday life and show their dominant only

when the pressures of life compel it. Therefore, an introvert who is

a judging type will have as his dominant one of the perceptive functions,
either S or N.

Myers reports results, not in Jungian terminology (e.g., intro-
verted feeling type), but by using the initial of the preference on
each of the four scales. In this manner an introverted sensing type
is reported as ISTJ or ISFJ, an extraverted sensing type as ESTP or
ESFP, an introverted intuitive type as INFJ or INTJ, an extraverted
intuitive type as ENFP or ENTP, an introverted thinking type as ISTP
or INTP, an extraverted thinking type as ESTJ or ENTJ, an introverted
feeling type as ISFP or INFP, and an extraverted feeling type as ESFJ
or ENFJ.

Most research reported in this section is based on Myers (1962).
A critical examination of her sources is beyond the scope of the pre-
sent work and would be a difficult task. While she reports the sources
of her data, much of it is in technical reports or unpublished material.
Also the sources of some of her own analyses are cross-referenced in a
complicated manner.

Myers reports correlational data comparing MBTI scales with
SVIB-M scales. The manner of presentation was to say that certain
SVIB-M occupational groups attracted a particular MBII type or combina-
tion of types. Thus SVIB-M groups I and II (professional and technical-
scientific, nomenclature used by Myers) were said to attract IN-- types.

This means that MBTI scores on the I-2 scale and on the S-N scale

45

correlated highly with most SVIB-M scores in groups I and II, in the
direction of I and N, but there were no significant correlations between
those groups and the T-F and J-P scales. In the same manner groups III,
VII, VIII, IX, and XI (production manager, CPA, business detail and
administration, business contact and president of manufacturing firm)
were said to attract EST] and "partial“ ESTJ types. Groups VI and x
(musician, verbal or linguistic) were said to attract -N-P types and

and group V (uplift) was said to attract ENF- types.

Also listed are the individual SVIB-M occupations which cor-
related highest (range .20 to .55) with each MBTI dimension. E cor-
related highest with the sales manager scale; I, with the mathematician
scale; S, with the banker scale: N, with the psychologist scale; T,
with the purchasing agent scale; F, with the minister scale; J, with
the accountant scale; P, with the artist scale.

The report of another series of studies was that among creative
occupations, i.e., architects, research scientists, writers, and
matheticians, the writers tended to be ~NF- and mathematicians -NT-.
All four occupations were N.

Myers also reports data which show that the composition of
student bodies in different colleges and professional schools differs
by type. The relative frequencies of the sixteen types of college prep
high school students were compared with the relative frequencies of
students at liberal arts, engineering, science, business, and medical
schools. 0n the basis of this comparison, the following conclusions
were drawn.

For liberal arts students the characteristics identified as

being predominant were -NF- and -IN- against EST-; for science students,

46

IN-- against ES--; for engineering students, -N-J against -S-P and ES--;
for business students, -ST- and ES-- against IN--; for medical students,
--F- and IN-- against ESTJ. These findings do not have immediate use-
fulness for the present study since the primary thrust of the findings
is that business types can be clearly differentiated from science types.
Business was excluded as a dimension in the present study for reasons
to be cited later. However, the findings are significant for the pres-
ent study in that they do show that Jungian typology as operationalized
by the MBTI is a useful tool for assessing differential characteristics
of college majors.

Another comparison, one step closer in relevance to the present
study, is of the effects of combining the perceptive and judging func-
tions,i.e., the occupational choice or choice of major a person who is
an -ST- combination is apt to make as opposed to one whose preference
is -NT-. The data were derived by investigating the percentages of the
combinations among various occupational and/or student groups. The

table is presented here as Myers (1962, p. 64) presented it.

Function

choice ST SF NF NT
Production Sales Research Research
Construction Service Teaching Science
Accounting Customer Preaching Invention
Business relations Counselling Securities
Economics Welfare work Writing analyst
Law Nursing Psychology Management
Surgery Gen. practice Psychiatry Cardiology
Etc. Etc. Etc. Etc.

Reynolds and Hope (1970) investigated the hypotheses that there
would be a greater proportion of science students classified INTP on
the MBTI than in the general population and that students with those

preferences would score higher on science achievement and aptitude tests,

47

in grade point average, and on academic aptitude tests. The population
for this study was 326 secondary school students in required general
science and biology classes representing students in general and 58
advanced science students representing science students. The authors
concluded that science students did move in the direction of INTP when
compared to students in general, but the support was marginal in that
the results were in the predicted direction but not always statistically
significant. The latter hypothesis concerning higher achievement and
aptitude scores by science students was for the most part not supported.

Further considerations of the MBTI are contained in the instru-
mentation section of Chapter III.

In this section four conceptualizations of cognitive style chosen
for the present study have been surveyed and research having relevance to
their relation to college major has been reviewed. The research with the
dimension of field-dependence-independence was the most direct, followed
by the research on Jungian typology via the MBTI. Reflection-impulsivity
was discussed as an important concept for instructional settings though
research relative to college major is all but non-existent. Westcott's
conceptualization of intuition was seen as important to instructional
settings because it had implications for the manner in which information
is presented in instructional settings. It is the least well researched,

possibly because findings via the HIT have been scanty.

Other Research Relating Cognitive Style to Choice of Major

The third major section of this chapter, as outlined in the

introduction, deals with a review of studies which in.some manner have

48

linked a cognitive style with college major, with the exception of the
study to be presented next.

Campbell (1967) through multivariate procedures analyzed eight
predictor variables derived from the Scholastic Aptitude Tests (SAT) and
the Milwaukee Academic Interest Inventory as to their effectiveness for
predicting college major. Of interest for the present study are the
findings that a science vs. non-science dimension (as well as a helping
people vs. commercial-business interest) was identified and that all
variables discriminated among the groups of interest.

Brubaker (1972), conceptualizing creativity and critical thinking
as two dimensions of dissimilar cognitive styles, investigated the rela-
tionship of these variables and Scholastic Aptitude Test scores to the
educational-vocational areas of agriculture, biological science, business,
education, humanities, physical science, and social science. Subjects for
the study were 1,233 entering freshmen at the University of Delaware.
Findings of relevance to the present study were that students in the
different areas did differ among themselves, and from a control group
of undecided students, on the SAT scores and critical thinking measure,
but only females differed among themselves and from a control group of
undecided students on the measure of creativity. The undeclared students
differed from the other students in combinations of the dependent
variables.

Osipow (1969) studied the relationship between cognitive style,
selected college majors directlyrelated to occupational choice, and pro-
files on Holland's Vocational Preference Inventory (VPI). Osipow's basic
hypothesis was that people tend to organize their perceptual experiences

in distinctive and significant ways, which results in differential

49

behaviors-~including those in the occupational realm. He used four
measures of cognitive style-FWord Similarity, the Object Sort (cf. the
discussion on cognitive controls earlier in this chapter), a measure

of rejecting vs. accepting response set, and Thurstone's Closure Flexi-
bility Test as a measure of field-dependence-independence.

Female students majoring in nursing, home economics, dental
hygiene, and special education, and male students majoring in pharmacy
and fisheries technology served as subjects in the Osipow study. The
four groups of female majors could be differentiated on the Object Sort,
two of the three measures of rejecting vs. accepting response set, and
field-dependence-independence,and on five of eleven VPI scales. The two
groups of male majors could be differentiated on word similarity, one
of the three measures of rejecting vs. accepting response set, and on
three of eleven VPI scales.

It was also hypothesized that those who scored at the extremes
on one measure of cognitive style would be significantly different on
other cognitive style measures and VPI scales. This hypothesis was
upheld in five out of a possible twenty cases for the cognitive style
measures and in eleven of a possible 55 cases for the VPI. It should
also be mentioned that the questionable practice of using multiple t
tests was used in obtaining these results.

Other hypotheses were investigated concerning the VPI scales.
Their results are not reported here because they have marginal relevance
to the present study. Overall, Osipow concluded that his study lends
support to the general hypothesis that students preparing for different

occupations vary in cognitive style.

50

Hudson (1967) conducted a series of studies of British school
boys. The British system is such that at age fifteen a student is cate-
gorized as either an arts or a science student. In his search to find
intellectual ability correlates of the arts-science dimension, Hudson
discovered that a "style-of-reasoning" dimension which he terms convergent-
divergent thinking discriminated science from arts students remarkably
well. (It might be added that he had already developed a composite of
ability test profiles which also discriminated well.) In conjunction
with an intelligence test, he used two tests, one a Use of Objects Test
in which a student is to name as many uses as he can of an object (e.g.,
barrel), and another in which the student gives as many meanings of a
word as he can. Convergent students tend to score well on an IQ test
(termed A. H. S), to give fewer definitions and uses, and to be in the
sciences. Divergent students do relatively poorly on the IQ test, give
more definitions and uses, and tend toward the arts.

Mackay and Cameron (1968) replicated Hudson's findings in a
Scottish university where the decision to specialize in the arts or
sciences is not made as soon. Their sample came from an introductory
psychology class in which a cross section of students enrolled. The
same tests administered in Hudson's study were used. The battery did
not differentiate students when non-specializing students were in the
sample, but when they were eliminated from the sample so that there
were only arts specialists and science specialists in the sample, then
the results strongly confirmed Hudson's findings.

Hervey (1967) investigated the relationship between cognitive
style as measured by Sigel's SCST (also used by Gatewood, 1972) and

performance in two school related tasks. When six of the seven hypotheses

51

relating to that investigation were not confirmed, and the seventh was
not able to be analyzed statistically, she refocused the study and in-
vestigated the influence of cognitive style on the choice of major and
grade point average. Categories for choice of major were basically the
same as for the present study. They were literature and communications,
natural sciences, and social sciences. The sampling of specific majors
in the general categories differed little from those in the present
study except that history was included as a social science by Hervey

and as a humanity in the present study.

Hervey concluded after examining the data via analysis of vari-
ance and chi-square that there was indeed a relationship between those
majoring in the sciences and the inferential-categorical mode of con-
cept formation. She also compared unidentified "entrance test subscores
(pp. 51-52)" to the three modes of concept formation and found a rela-
tionship between "numerical" aptitude and the inferential-categorical
mode. Science majors had significantly higher grade point averages and
higher "information" and ”numerical" aptitude scores.

In a similar study, Williams (1971) devised a Cognitive Prefer-
ence Test (CPT) which yielded preference scores for l)facts or terms,
2) fundamental principles or generalizations, and 3) practical applica-
tion in each of three areas--natural sciences, social sciences, and
mathematics. Subjects were 231 community college and university fresh-
men and sophomores.

Of significance for the present study are findings that 1) no
difference in CPT scores were found between the sexes, 2) differences
were found between subjects majoring in different fields, 3) CPT scores

were unrelated to academic aptitude test results, and 4) surprisingly

52

CPT scores were unrelated to scores on unnamed "traditional psychological
tests of cognitive styles."

Chung (1966) investigated the relationship among four measures
of cognitive style, major in college, vocational preference, and
vocational commitment.

The measures and instrumentation for cognitive style were:
field-dependence-independence as measured by a group test very similar
to the Group Embedded Figures Test used in the present study; a test
of leveling-sharpening developed by Gardner; constricted-flexible style
as measured by the Stroop Color Word Test; and equivalence range as
measured by Clayton and Jackson's Object Sorting Test.

Vocational preference was assessed by scores on the Kuder
Preference Record. College majors used in the study were identified
on the basis of the investigator's judgment as to what would maximize
differences between areas and minimize differences within areas. The
groups he selected were social science, natural science, humanities,
engineering, elementary teaching, music, social service, and library
science majors.

Vocational commitment was established by evaluating two responses
on Chung's Personal Data Blank. Subjects for the study were 141 junior,
senior, and graduate level paid volunteers from three schools in the
Nashville, Tennessee, area. There were seventy-one female and seventy
male subjects ranging in age from 19 to 39 (2522.8).

Of particular interest for the present study was that scores of
those majoring in different areas were differentiated on the various
cognitive style measures. However, the pattern was mixed, i.e., the

pattern of scores of those majoring in different areas clustered

53

differently on the different measures of cognitive style. The statis-
tical tool was multiple discriminant analysis. On the measure of
field-dependence-independence, engineering and natural science students
had the most field-independent scores, while social service, elementary
teaching, library science, and humanities clustered toward the field-
dependent end. Social science and music majors stood between the two
groups; they were significantly different from the former but not the
latter.

On the constricted-flexible dimension, library science and social
service were toward constricted style while elementary teaching and
social science were toward the flexible dimension. On the leveling-
sharpening dimension, natural science and library science majors were
the strongest sharpeners while music and the humanities were the strong-
est levelers. The equivalence range dimension was found to be an inef-
fectual dimension for differentiating college major.

The analyses of Kuder Preference Record types indicating voca-
tional commitment yielded negative results.

Field (1954) administered five personality measures, a perceptual
task, an attitude scale, and seven measures of identification with the
father figure to subjects majoring in physical sciences and social sci-
ences. Of significance for the present study was the finding that the
physical science majors scored more toward sharpening on the leveling-

sharpening measure than did the social science majors.

54

Conclusions

 

A careful review of the literature has led the present author to
the following conclusions.

I. There is substantial evidence that cognitive style, although
defined in many diverse ways, is related to college major.

2. The most promising dimension for differentiating humanities
from natural science students is Witkin's field-dependence-independence.
However, there has been no study using many subjects, both male and fe-
male, and incorporating a social science dimension. The present study
intends to provide the next step in exploring this dimension.

3. While Westcott's measure of intuition has not been demon-
strated to be an effective measure in differentiating college majors,
some research has alluded to the possibility of such a finding. However,
as has been pointed out, the primary reason Westcott's work is included
in the present study is that it has implications for instructional prac-
tice-~that while some students seem to prefer an inductive, "discovery"
approach to learning, others prefer a more structured presentation ap-
proach. As has also been pointed out, the intent of the present study
is to investigate whether these differences are systematic by college
major.

4. The nature of Gatewood's study leaves inconclusive the
relation between reflection-impulsivity and college major. However,
as with intuitive thinking the dimension has implications for instruc-
tional practice. As it was pointed out in Chapter I, should it be found
that students in different major groups vary systematically on the
dimension of reflection-impulsivity,either instructional practice could

be geared to that difference or attempts be made to alter the characteristic.

55

Therefore further investigation seems warranted.

S. Jungian typology as indicated by the MBTI has been shown to
be effective in differentiating college majors. An impressive array of
evidence has been presented using various combinations of MBTI scale
types, but there has been no test of the concept of the dominant func-

tion and college major. The present study proposes to meet that need.

CHAPTER III

METHODOLOGY AND ANALYSIS

In this chapter the design of the present study, a description
of the sample, procedures used in gathering data, the measures selected
for evaluating the concepts, testable hypotheses, and the method for

analyzing the data will be presented.

Design

The present study was descriptive in nature. Its primary purpose
was to investigate whether students cast into three categories of college
major would differ on dimensions of cognitive style and to determine
which measure best differentiated categories of college major when several
related measures of cognitive style were used. This basic hypothesis was
investigated using two techniques. On all measures which yielded con-
tinuous scores-field-dependence-independence, reflection-impulsivity,
and intuition-mean differences and vectors were tested. 0n the measure
which identified dominant Jungian function and yielded discrete data, the
relative percentages of subjects exhibiting particular dominant functions
in each major category were compared.

The technique investigating mean differences included comparison
not only of mean differences among the three major categories--humanities,
social science, and natural science--but also between the sexes. The

56

57

dimension of sex was added for three reasons. First, most investigators
have reported finding small but statistically significant differences be-
tween the sexes on field-dependence-independence. It seemed appropriate
to investigate the phenomenon further. Second, it made the present study
more complete. Studies most similar to the present study either controlled
for sex differences by eliminating one sex (Hervey, 1967; Gatewood, 1972)
or did not control for sex differences at all (Chung, 1966). Third, add-
ing sex as a dimension made possible testing for interaction effects be-
tween sex and major, i.e., whether differentiation on cognitive style
dimensions might be strongest in a combination of the two. It must be
added, however, that the present author found no reason to hypothesize
interaction effects and therefore no hypotheses were formulated con-
cerning them.

Grade point average (GPA) and American College Test Composite
(ACT-C) score were collected from university records and included in the
analysis. They were included as comparison measures since the review of
the literature discussed the relationship between academic aptitude and
achievement and cognitive style. Such an addition made the present study
a more thorough investigation.

Two samples were drawn and teSted, the second sample replicating
the first.

The technique for analyzing the relation of Jungian dominant types
to college major, as has been pointed out, was to compare the relative
percentages of subjects exhibiting a dominant Jungian function in each
category. Thus the data were cast into a 4 X 3 table. The sample size

prohibited separating subjects by sex and it was also impossible in this

58

design to make comparisons with GPA and ACT-C. However, the replication
was performed for this analysis.

The secondary purpose of the present study was to compare subjects
identified as dominant sensors with dominant intuiters and subjects iden-
tified as dominant thinkers with dominant feelers on measures of field-
dependence-independence, reflection-impulsivity, and intuition. The same
design was followed for this part of the present study as was followed
for comparing majors on the cognitive style dimensions yielding continuous
scores, except that sex could not be included as an independent variable.
The scarcity of subjects identified as dominant sensors and dominant

thinkers rendered the sample size too small.

Sample

Each sample in the present study was comprised of ISO volunteer
subjects, so divided that there were 25 males and 25 females in each of
three categories of college major--humanities, social science, and natu-
ral science. The majority of subjects were upperclassmen.

Roughly one-sixth of the students solicited volunteered as sub-
jects except in one case in the first testing and two cases in the second
in which the professor made class time available for testing. Only a few
in those instances chose not to participate.

Sample 1 consisted of undergraduate students present on the cam-
pus of Central Michigan University (CMU) during the spring term mini-
session of 1973 and the first three weeks of the regular 1973 summer
session. The subjects were tested from May 15 to June 1, 1973, and June
18 to July 9, 1973. They ranged in age from 17 to 55 years with the mean

age being 22.2 and the standard deviation 4.3 years. The mean grade

59

point average for the sample was 2.90 (s.d. ! .53). Since the average of
all grade point averages for students at the end of the winter term 1973
was 2.74, this sample had on the average slightly higher academic achieve-
ment than the student body as a whole. The mean ACT-C score for 88 of

the students for whom the score was available in this sample was 23.1
(s.d. I 4.0) while the median of mean ACT-C scores for freshmen admitted
from the 1969-1970 to 1972-1973 academic years was 21.0. While it is
apparent that the mean ACT-C score for Sample 1 was higher than the median
of mean ACT-C scores for incoming freshmen and that the mean CPA for this
sample was higher than that of the student body as a whole, the question
remains whether the sample was higher than a random sample of their peers
on these measures or whether the fact that most of the sample was upper-
classmen accounted for the difference.

In Sample 1, 29 females in the humanities were enlisted since the
experimenter experienced difficulty in soliciting male subjects. When it
was realized that sufficient male subjects would participate, four females
in that category were randomly removed from the data analysis. One sub-
ject in this sample had to be excluded because he would not answer all
MBTI items, so another volunteer was solicited.

Sample 2 consisted of undergraduate students present on the campus
the first three weeks of the fall 1973 semester. They were tested from
August 27 to September 14, 1973. They ranged in age from 17 to 33 years
with the mean age being 20.7 and the standard deviation 2.2 years. The
mean GPA for this group was 2.91 (s.d. - .48) and the mean ACT-C score
for 117 of the students for whom the score was available in this sample

was 22.8 (s.d. - 4.1).

60

From the data presented, it can be seen that the two samples
were quite similar in academic achievement and aptitude and that the mean
age of Sample 2 subjects was 1.5 years less than that of Sample 1 subjects.
The mean differences were analyzed by means of the t test. Differences
were not significant on GPA and ACT-C, but the age difference was sig-
ficant (B 8 3.004, p 41.001). It can be concluded that on CPA and ACT-C
the samples were drawn from the same population, but on age it appears
they were not.

‘e

Procedure

Specific majors were classified humanities, social science, or
natural science using the ranking system devised by Goldschmid (1967).
He used the constant sum method for developing two scales of the same
55 majors. One scale was anchored on philosophy and the other on physics.
Groups of counselors, faculty, and upper-level students rated the sub-
jects on each scale in relation to an anchor subject. On the science
scale, physics was the anchor subject and therefore was given 100 science
points and O humanities points. On the humanities scale, philosophy was
given 100 humanities points and 0 science points. The result was two
scales of SS majors ranked on their relation to science or humanities
in descending order. One scale was reversed so that there were not two
scales, each headed by natural science subjects. Both scales were
divided into thirds so that the top third contained mostly natural
sciences, the middle third contained mostly social sciences, and the
bottom third contained mostly humanities. Those subjects which were

included in the same third were immediately chosen as appropriate for

61

the present study. Those majors which were in different thirds were
chosen using the best judgment of the present author consistent with
commonly accepted classifications.

Some majors were specifically excluded from the present study.
Goldschmid (1967) concluded that certain majors seemed not relevant to
the arts vs. science dimension, namely business, home economics, and
librarianship. Likewise, they were not included in the present study.
Education as a major fell in the humanities category. However, though
CMU has a strong tradition of teacher education, no one majors in educa-
tion as such. There are a few curricula which have, in effect, a major
in education such as special education, physical education, and indus-
trial education. Since the major is a combination of education and
other subject areas, e.g., psychology on the special education curricu-
lum, these majors were also excluded from the present study.

The criterion for determining a student's major was self-report.
If a student was a double major, then he was asked which was his prefer-
ence if he had to choose between the two. While the soliciting was done
for the most part in upper-level classes because more upper-level students
know their majors, freshmen or sophomores who could say they were majoring
in a specific area were accepted for the study.

Table 1 contains a list of the majors accepted in the present
study and the number of male and female subjects in each testing by
subject area.

The present author or one of his assistants asked professors for
ten minutes of class time to solicit subjects from the professor's
classes. No professor refused the request. Potential subjects were in-

formed of the nature of the study, time required, the general nature of

62

TABLE 1

Composition of Sample 1 and Sample 2
by Sex and Number in Each Major Area and Specific Major

Sample 1 F Sample 2

 

Majors T Male Female Male Female
Humanities
Speech 6 6 6 9
Music 2 l 2 1
English 8 3 7 4
Journalism 3 4 3
Religion 1
Foreign Language 2 6 2
Philosophy 1
Art 2 4 2 4
History 4 2 3 2
Total 25 25 25 25

 

Natural Science

 

Mathematics 4 10 6 3
Biology 12 12 17 21
Chemistry 5 l 2 1
Earth Science 1 2
Geology 1
Physics 1
Civil Engineering 1

Total ' 25 25 25 25

Social Science

Psychology 13 13 14 14
Sociology 7 11 3 8
Political Science 4 l 4
Economics 2 1
Social Science 1 _2 1
Health Education 1

Total 25 25 25 25

 

 

 

63

the tests to be administered, and that, since the design of the study
required two samples of 150 subjects each, the experimenter was unable
to pay his subjects. Subjects were also told that they could receive an
interpretation of the test results at the end of the term or testing
period.

A small number of students were solicited in other ways, e.g.,
students known personally by the present author or his assistants. Sub-
jects were solicited until each of the six categories of 25 subjects was
filled.

A few subjects, particularly those who were tested in a class
session, did not keep an appointment to complete the testing. In those
cases, subjects were solicited to fill in the number of required subjects
for each category.

Subjects were scheduled for testing at a specific time to main-
tain an orderly atmosphere for testing. Since there were only two exam-
iners for the individually administered MFF and the administration time
for the whole battery was quite lengthy, the order of administration of
[the tests varied so that the subjects were occupied most of the time.

The four tests administered were the Group Embedded Figures Test (GEFT),
the WIT, the MFF, and the MBTI. Maximum utilization of the subject's

time was accomplished by breaking up the administration of the untimed
MBTI, usually with administration of the MFF. For instance, if subjects

A, B, C, and D were tested at the same time, they all would be administered
the two timed tests (GEFT and WIT), and then subjects A and B would start
the MBTI and subjects C and D would be given the MFF. When subjects C

and D completed the MFF, then subjects A and B would be interrupted to

take the MFF while subjects C and D were given the MBTI. There is no

64

reason to believe that the data were distorted using this system since
the MBTI is untimed and the nature of the items is such that responses
are not likely to change with an interruption of short duration. Also,
the interruptions were random so that no systematic differences were
introduced.

The present author was assisted in test administration for
Sample 1 and Sample 2 by two people, both with graduate degrees and known
to be reliable and accurate. One was paid; the other volunteered. In
addition, for Sample 2, two reliable psychology students, one graduate
and the other a senior, were paid to assist in test administration since
the time required to solicit subjects for the first study far exceeded
the expectations of the present author. The role of the two psychology
assistants in Sample 2 was relatively minor and their primary function

was to fill gaps which would expedite the testing.

Instruments

 

This section contains the instrumentation used in the present

study, rationale for its use, and reliability and validity information.

Group Embedded Figures Test The Group Embedded Figures Test (Witkin
et al., 1971) was chosen for the present study as the measure of field-
dependence-independence because evidence presented in the manual suggests
it is a reliable and valid measure of the construct, and it offered the
advantage of relative speed and ease of administration.

The test presents the subject with eighteen geometrically complex
figures. Within each figure is a more simple figure, which the subject

is asked to identify by outlining it with a pencil in the complex figure.

65

The test is divided into three timed sections, one two-minute practice
section, and two five-minute test sections. The score is the number of
simple figures correctly identified. Subjects are classified field-
independent if they score above the mean of their group and as field-
dependent if they score below it.

The manual reports preliminary norms based on undergraduate men
and women at an eastern liberal arts college. For men, it reports a mean
of 12.0 and a s.d. of 4.1 based on 155 cases; for women, it reports a
mean of 10.8 and a s.d. of 4.2 based on 242 cases. The grand mean for
397 cases is 11.3. The data from the two samples collected for the
present study yielded mean and s.d. scores of 12.3 and 4.6 respectively
for Sample 1 and 13.0 and 4.0 respectively for Sample 2. The scores from
the present study seem acceptably close to those from the preliminary
norm group. It was found that no sex difference existed in the present
study though the difference reported in the manual is significant at the
.005 level of significance.

A reliability estimate of .80 is reported for a sample of 80
males and 97 females. The correlation was based on number identified
in the first section of nine problems, as. opposed to the nine problems
in the second section, and corrected by using the Spearman-Brown prob
phecy formula.

Since the GEFT, as well as the WIT, were administered using time
limits, the question of the propriety of the split-half method of comput-
ing reliability coefficients is raised. Were the tests purely speed
tests, there would be no question that the method was totally inappro-
priate. However, Magnusson (1967) speaks of tests which do not depend

on pure speed but which have time limits. In such situations he says

66

the effect is to diminish the magnitude of the reliability coefficient.
0n the other hand, Cronbach (1960), speaking in the context of tests of
general ability, makes the comment that short speed tests may be more
reliable than tests with very few items. Clearly the GEFT and WIT fall
in the former category.

The criterion for assessing the effect of a time limit on per-
formance is whether most subjects finished all the items they could in
the required time. It was the observation of the present author that
most subjects taking the GEFT were not pressed for time. ‘Therefore, it
seems that the effect on reliability was more severe for the WIT than for
the GEFT since Westcott shortened the ten item test used in the present
study to eight items because some subjects were pressed for time (M.
Westcott, personal communication, May 17, 1973). The situation is
somewhat alleviated for the WIT since Westcott does report test-retest
coefficients. In both cases, however, caution seems warranted in inter-
preting the split-half coefficients.

The manual cites three cases of concurrent validity for the GEFT.
Correlations of -.82 for 73 males and -.63 for 68 females with scores on
the EFT are reported. Correlations of -.39 were reported for 55 males
and -.34 for 68 females with the Portable Rod and Frame Test (PRFT), and
of .71 and .55 for the same number of males and females respectively on
the ABC scale which measures degree of body articulation. (The negative
correlations are in the expected direction because of the nature of the
EFT and PRFT scores.) Degree of body articulation, as discussed in Chap-
ter II, was found to be an indicator of degree of field-dependence-

independence.

67

Witkin 33 31. (1971) conclude
The combined evidence suggests that the GEFT may

prove to be a useful substitute for the EFT when
individual testing is impractical (p. 29).

The Matchinngamiliar Figures Test As reported in Chapter II, the
Matching Familiar Figures Test (MFF) presents the subject with a standard
line drawing and eight variants. One line drawing is an ocean liner. In
the variants the shape of the prow is altered, the height of the smoke-
stacks, the position of the anchor, or the tilt of the smokestacks. The
subject is to select the line drawing which is the exact duplicate of the
standard. The time he takes to make the first selection as well as the
number of the selections he makes before identifying the correct one are
recorded as scores.

The time score is the most important index of a reflective or
an impulsive attitude in an individual. Impulsive subjects score below
the mean response time of their group and reflective subjects score above
it. Most impulsive subjects' error scores are above the mean and most
reflective subjects' error scores are below it. However, the correlation
is not perfect. Kagan and Kogan (1970) report correlations between the
scales which range from -.40 to -.65. In the present study the correlation
in Sample 1 was -.59 and in Sample 2 was -.60. (See Appendix H.)

There appear to be no published norms for the test, and inquiries
on the part of the present author and another investigator to the test
author produced no data. Gatewood (1972) reports that for her 129 junior
college subjects the median of mean response times was 45.58 seconds. In

the present study, the median of all response times was 50.75 seconds in

68

Sample 1 and 46.08 in Sample 2. The median error score in Gatewood's
study was 7.5. In the present study the median error score for Sample 1
was 6.4 and in Sample 2 was 6.3.

Burgbacher (1973) administered the MFF in two sections, by sepa-
rating the odd and even items, to 40 male junior, senior, and graduate
students (the majority were graduate students) whose median age was 24.8.
The median age for Sample 1 in the present study was 21.7 and for Sample
2, 21.0. Burgbacher divided the test to facilitate the pre-post test
design used in his study. On one half of the MFF, the mean error score
for Burgbacher's sample was 4.3 and on the other half was 3.4. The mean
error score for Sample 1 in the present study was 8.6 and for Sample 2,
8.5. The mean time score on one half of the MFF for Burgbacher's sample
was 337.2 seconds and on the second half was 346.4 seconds. The mean
time score for all items was 630.9 seconds in Sample 1 and 593.7 seconds
in Sample 2 in the present study.

The descriptive data presented by the present author, Gatewood,
and Burgbacher are fairly consistent when the mean scores for each half
of the MFF in Burgbacher's study are combined. Burgbacher's combined
error scores are slightly lower and time scores are slightly longer which
could be explained by the fact that his older and mostly graduate student
population could be expected to be more reflective in their test taking
behavior. Thus it is contended that the three samples do not differ in
kind and could serve as a norm group.

In Chapter II, it was reported that the dimension of reflection-
impulsivity was found to be a reliable one. Kagan and Kogan (1970) cite
specific research which points to the reliability of the MFF. One hundred

and four third and fourth grade boys and girls were administered one form

69

of the MFF and then another form one year later. The correlation for the
response time score between administrations averaged .62. One hundred
and two children were administered the same form of the MFF a year apart.
The correlation for the response time score was .48 for boys and .52 for
girls. After 2% years, the correlation was .31. Kagan and Kogan do not
report coefficients for the error scores.

Burgbacher (l973) cites evidence for the reliability of the MFF.
As was reported previously, he divided the test items into two groups
according to an odd-even split, so that he could use half of the items
for a pre- and half for a post-test. He had, in effect, parallel forms
of the same test. The correlation between the two forms was .76 for the
time score. The correlation between the two forms on the error score was
.55. These correlations seem quite acceptable as evidence for the relia-
bility of the MFF especially in view of the fact that the tests were
shortened and no correction formula was applied and came from a very
similar population on the same campus.

One source of validity for the MFF is face validity, i.e., Kagan
g£_2l. (1964) have proposed a dimension which they believe is an impor-
tant factor in information processing. They have termed this dimension
reflection-impulsivity. Clearly the MFF measures how rapidly and accu—
rately a subject responds to the task. The research reported in Chapter
II concerning the generality of the dimension across tasks provides a

form of concurrent validity.

The Westcott Intuition Test As was pointed out in Chapter II, the
Westcott Intuition Test (WIT) requires the subject to solve an abstraction

problem using as few of five clues to its solution as possible. The

70

correct solution is that which consensual validation dictates when all
five clues are known.

The format of Westcott's original test was two masonite boards
which had twenty rows of five oblong slots cut through both boards. The
clues were typed on a piece of paper attached to the back of the bottom
of the two boards so that they showed through the 100 holes. A piece of
aluminum foil was inserted between the two boards which served to cover
up the clues. The subject uncovered the clues by inserting a stylus in
the slots and tearing away the foil.

The present author contracted with a person a duplicate the
board he had received from Westcott and after six weeks of frustration
that person gave up the task. Fortunately, another process was found to
produce the test. This was a latent image spirit duplication process
whereby the clues were invisible until they were developed with a special
pen which the subject brushed across the clues which were outlined by
visible boxes.

The WIT has been shortened three times to»make its administration
more convenient. The original test was twenty items; the second, ten:
and the third, eight. The present author was supplied with the ten item
version and learned of the eight item version only in a data sheet (M.
Westcott, personal communication, May 17, 1973) containing information
on the ten and eight item tests. By this time data collection was under-
way and it was too late to change to the eight item.version.

The data sheet provided normative data for the ten and eight item
versions. The population was 49 social agency employees (mean age, 35.6
years) recruited from all levels. However, of those volunteering, 41

had at least a bachelor's degree. There were 37 females and 12 males.

71

Westcott reports that as many as 101 of the protocols in this sample had
to be eliminated because of failure to comprehend instructions, as opposed
to 22 to 52 in his college populations. In the present study, no subject
who finished all tests misunderstood directions. Perhaps this was due to
careful monitoring by the present author or his assistants and to adminis-
tration of the WIT in small groups.

For his sample on the ten item scale Westcott reported the mean
clue use score was 33.9 (s.d. I 6.5), as opposed to 32.3 (s.d. I 6.7) in
Sample 1 and 31.8 (s.d. I 6.0) in Sample 2 of the present study. For
Westcott's sample the mean number correct was 4.3 (s.d. I 2.0) as opposed
to 4.2 (s.d. I 2.0) for Sample 1 and 4.5 (s.d. I 2.1) for Sample 2. It
can be seen by these data that the measures of central tendency and dis-
persion are very stable, even though Westcott's group was much older.

There is no reliability information supplied for the ten item
version of the WIT. However, Westcott (1968b) does provide extensive
reliability information for the twenty item version. Subjects were 900
female and 197 male college students in eleven samples of data collected
over a period of nine years. There was no noticeable difference in
descriptive statistics between male and female samples. For all but 70
in the entire population tested, split-half correlations corrected for
test length were available. For the number correct score, correlations
ranged between .36 and .72 with the median correlation being .48. For
the clue use score, coefficients ranged from .70 to .91 with the median
being .82. For two of the samples (NI95), both split-half reliabilities
were computed. For the number correct score, the split-half reliability
was .80 and the three year test-retest reliability was .50. For number

correct the split-half reliability was .70 and the three year test-retest

72

reliability was .66. The split-half reliability coefficients are pos-
sibly higher than for the form presently employed: first, because the
number of items in the form used for the present study is half those in
the original form; second, as has been discussed in the section on the
GEFT, because the time limit on the present form of the WIT places it in
the category of a speed test. It is unclear at what point Westcott intro-
duced the time limit. While split-half reliability is not appropriate

for speed tests, some mitigating circumstances were cited which show that
the attenuation of the coefficient may not be as great as if the test

were a pure test of speed.

The number correct and clue use scores have been found to be
uncorrelated. Westcott (1968b) reports correlations from eleven samples
ranging from -.24 to +.24. 0f the eleven, only three were significant.
In the present study the correlation between the two scales was -.01 in
Sample 1 and .03 in Sample 2. (See Appendix H.)

Validity for this test is again face validity. Westcott has so

operationalized the definition that the WIT measures it.

_The Myers-Briggs Type Indicator The Myers-Briggs Type Indicator (MBTI)
is a 166 item forced-choice self-report inventory. Ninety-five of the
items are scored on the four dimensions mentioned previously: extra-
version-introversion (E-I), sensing-intuition (S-N), thinking-feeling
(T-F), and judging-perceiving (J-P). A subject is classified as E or I,
for instance, on the basis of the difference in "E“ items and "I" items
marked on the score sheet. A scoring system has been devised to elimi-
nate the problem of equal scores on one dimension. The difference scores

are doubled and one point is added in the direction of the least

73

predominant type in the population. Therefore, a subject might be
classified as E 01 or N 11. A system of continuous scores can be
developed using this system by adding or subtracting the score from 100.
Thus on a continuous scale the "E 01" would become 99 and the "N 11"
would become 111. It is on the basis of the continuous scores that the
first reliability coefficients are reported.

The manual (Myers, 1962) cites split-half coefficients of the
four scales for 200 college males and females in the .80's with the
median being .835. They are slightly lower for younger samples. The
manual also cites data based on tetrachoric correlation coefficients
since the user is more interested in the reliability of the test in
categorizing subjects into dichotomies than in continuous scores. These
coefficients corrected for test length ranged from .74 to .90 for the
college populations cited with the median again at .835.

Concurrent validity is established through correlation with the
scales of the Gray-Wheelwright, another less well-known instrument used
to assess Jungian typology. Although its reliability is lower than the
MBTI, its E-I, S-N, and T-F scales correlate .79, .58, and .60 with cor-
responding scales on the MBTI. The Gray-Wheelwright has no J-P scale.

The other type of validity reported is construct validity in
which scales from other tests which are believed to correlate with Jungian
constructs are examined. Data derived from the SVIB have already been
reported in Chapter II, and the methodology for comparison on that test
is the same as was employed for comparison with the following tests.
These tests which are reported as having parts complementing the Jungian
constructs are the Allport-Vernon-Lindzey Study of Values (AVL), the

Edwards Personal Preference Schedule (EPPS), and the Personality Research

74

Inventory (PR1). Faculty ratings and findings relative to the MBTI and
job stability are reported as further evidence of construct validity.

Scores on MBTI scales were correlated with scales on other tests
thought to be measuring at least partial MBTI constructs. In this manner,
the AVL Theoretical scale was found to correlate with the INTJ scales of
the MBTI. Scales on other tests which correlated highest with a single
MBTI scale were also examined. In this manner, a significant correlation
of .12 was discovered between the AVL Economic and the J scale on the
MBTI and a correlation of .51 between Nurturance on the EPPS and the F
scale on the MBTI. The myriad of evidence presented for construct valid-
ity is impressive.

The primary criticisms of the MBTI (Mendelsohn, 1965) are that
the scales which are claimed to measure dichotomously, in fact, have dis-
tributions more normal than bimodal and that the scales do not accurately
measure the Jungian concepts. While the criticism regarding the bimodal
distribution at this point seems valid, still the MBTI is the best instru-
ment yet devised for assessment of Jungian typology. Therefore, caution
seems to be warranted for interpretation of scores near the dividing line
between attitudes, functions, and on the J-P scale.

Mention is also made by Sundberg (1965) of the problems in test
taking attitude on the part of subjects. The experience of the present
author has been that subjects often complain of the ambiguity of the
items. To this criticism, it might be mentioned that Stanfiel (1966)
developed item weights to correct for motivational and social desirability
factors in the results, but that the weights did not appreciably change
them. Many items of which subjects complain are those which are not

scored. Also intuiters are in the majority in college populations,and

75

their characteristic orientation of seeing possibilities leads them to

complain of myriad possibilities suggested by the items.

Hypotheses

The hypotheses of the present study will now be stated in test-

able form. The major hypotheses are stated in their null form. The sub-

hypotheses will be stated in the alternate form.

Hypothesis 1 HO

There will be no differences with respect to average
performance on five cognitive style variables, grade
point average, and American College Test composite
score in the degree each contributes to the differen-
tiation among three categories of college major and
between the sexes.

Differences will exist in the degree of field-
dependence-independence as measured by group mean
scores on the Group Embedded Figures Test among human-
ities, social science, and natural science majors with
natural science majors scoring highest (dost field-
independent) followed by social science, then humanities
majors.
Symbolically: M1 < M2 < M3
Legend: M1 I Humanities
M2 I Social Science
M3 I Natural Science
Differences will exist in the degree of field-
dependence-independence as measured by group mean scores
on the Group Embedded Figures Test between males and
females with males being higher (more field-independent).
Symbolically: M1 > M2
Legend: M1 I Males

M2 I Females

C

8

76

Differences will exist in reflection-impulsivity as
measured by the group mean time score on the Matching
Familiar Figures Test among humanities, social science,
and natural science majors with natural science majors
scoring longer times (more reflective) followed by
social science, then humanities majors.

Symbolically: M1 < M2 < M3

Differences will exist in reflection-impulsivity as
measured by the group mean time score on the Matching
Familiar Figures Test between males and females.

Symbolicallyc M1 f M2

Differences will exist in reflection-impulsivity as
measured by the group mean error score on the Matching
Familiar Figures Test among humanities, social science,
and natural science majors with natural science majors
scoring fewer errors (more reflective) followed by
social science, then humanities majors.

Symbolically: M1 > M2? “3

Differences will exist in reflection-impulsivity as
measured by the group mean error score of the Matching
Familiar Figures Test between males and females.

Symbolically: M1 f M2

Differences will exist in the degree of intuitive
thinking as measured by the group mean number correct
score on the Westcott Intuition Test among humanities,
social science, and natural science majors.

SYDDOIlCClIyI ”1 f H2 ’ “3

Differences will exist in the degree of intuitive
thinking as measured by the group mean number correct
score on the Westcott Intuition Test between males and
females.

Symbolically: M1 f M2

Differences will exist in the degree of intuitive
thinking as measured by the group mean clue use score
on the Westcott Intuition Test among humanities, social
science, and natural science majors with natural science
majors scoring highest (least intuitive) followed by
social science, then humanities majors.

Symbolicallys M1 < M2 < M3

Hypothesis 2

Hypothesis 3

Hlj

Ho

77

Differences will exist in the degree of intuitive
thinking as measured by the group mean clue use score
on the Westcott Intuition Test between males and
females.

Symbolically: M1 f M2

Differences will exist among humanities, social science
and natural science majors as to the distribution in
those major categories of dominant sensors, dominant
intuiters, dominant thinkers, and dominant feelers as
identified by the Myers-Briggs Type Indicator.

There will be no differences with respect to average
performance on five cognitive style variables, grade
point average, and American College Test composite
score in the degree each contributes to the differen-
tiation between dominant sensors and dominant intui-
ters as identified by the Myers-Briggs Type Indicator.

Differences will exist in the degree of field-
dependence-independence as measured by group mean
scores on the Group Embedded Figures Test between
dominant sensors and dominant intuiters as identified
by the Myers-Briggs Type Indicator.

Symbolically: M1 f M2
Legend: M1 I Sensors
M2 I Intuiters

Differences will exist in reflection-impulsivity as
measured by the group mean time score of the Matching
Familiar Figures Test between dominant sensors and
dominant intuiters as identified by the Myers-Briggs
Type Indicator.

Symbolicallys M1 I M2

Differences will exist in reflection-impulsivity as
measured by the group mean error score of the Matching
Familiar Figures Test between dominant sensors and
dominant intuiters as identified by the Myers-Briggs
Type IndiC‘tor e

Symbolically: M1 f M2

Differences will exist in the degree of intuitive
thinking as measured by the group mean clue use score
of the Westcott Intuition Test between dominant sensors
and dominant intuiters as identified by the Myers-
Briggs Type Indicator.

Symbolically: M1 f M2

H3e

Hypothesis 4 Ho

b

78

Differences will exist in the degree of intuitive
thinking as measured by the group mean number correct
score of the Westcott Intuition Test between dominant
sensors and dominant intuiters as identified by the
Myers-Briggs Type Indicator.

Symbolicallyc M1 f M2

There will be no differences with respect to average
performance on five cognitive style variables, grade
point average, and American College Test composite
score in the degree each contributes to the differen-
tiation between dominant thinkers and dominant feelers
as identified by the Myers-Briggs Type Indicator.

Differences will exist in the degree of field-dependence-
independence as measured by group mean scores on the
Group Embedded Figures Test between dominant thinkers

and dominant feelers as identified by the Myers-Briggs
Type Indicator.

Symbolicallys M1 f M2
Legends M1 I Thinkers
M2 I Feelers

Differences will exist in reflection-impulsivity as
measured by the group mean time score on the Matching
Familiar Figures Test between dominant thinkers and
dominant feelers as identified by the Myers-Briggs
Type Indicator.

Symbolically: M1 f M2

Differences will exist in reflection-impulsivity as
measured by the group mean error score on the Matching
Familiar Figures Test between dominant thinkers and
dominant feelers as identified by the Myers-Briggs
Type Indicator.

~Symbolica11y: M1 f M2

Differences will exist in the degree of intuitive
thinking as measured by the group mean clue use score

of the Westcott Intuition Test between dominant thinkers
and dominant feelers as identified by the Myers-Briggs
Type Indicator.

Symbolically: M1 f M2

79

"4e Differences will exist in the degree of intuitive
thinking as measured by the group mean number correct
score on the Westcott Intuition Test between dominant
thinkers and dominant feelers as identified by the
Myers-Briggs Type Indicator.

Symbolically: M1 f M2

Method of Analysis

Multivariate analysis of variance (MANOVA) met the design re-
quirements of the present study for the test of Hypotheses 1, 3, and 4.
MANOVA provided the means by which the five related measures-IGEFT, MFF
time, MFF errors, WIT correct, and WIT clues-~could be tested simul-
taneously for the ability to discriminate among three categories of
major and between the sexes or between dominant types.

In interpreting the MANOVA test, first, the P value for interac-
tion effects was examined for significance at the assigned level. For
the present study, the significance level was set at .05. If a signifi-
cant interaction effect was found, it was interpreted as outlined below
and further examination ceased. If no significant interaction effect
was found, significant main effects by sex and major or by type were
interpreted as outlined below.

When a significant interaction effect or main effect was found,
the step-down F test was performed. ‘The five cognitive style meas-
ures, ACT-C, and GPA were ranked according to priority of interest.
Following the same rationale, separate alpha levels were set for each
measure. (The specifics of the ranking are outlined in Chapter IV.)
Starting with the variable of least interest, the p value for each vari-
able was compared with its alpha criterion. The examination stopped

with the first measure which met the criterion. That measure was seen

80

as the most important contributor to the differentiation in the signifi-
cant interaction or in the main effects of major or sex (H1) or type
("3, H4).

The tests via MANOVA were followed by tests of the subhypotheses
via two-way analyses of variance (ANOVA). These tests investigated the
power of each of the five dependent variables taken separately to dis-
criminate among the categories of college major and between the sexes.
Those subhypotheses of H3 and “4 were tested via one-way ANOVA since the
scores of dominant sensors and dominant intuiters, and dominant thinkers
and dominant feelers were not crossed by the two sexes. The significance
level for these tests was that assigned for the step-down F tests in the
multivariate analysis.

The statistical procedure chosen for evaluating Hz was chi-square
since assessment using Jungian typology involves placing subjects in dis-
crete categories. In this test the three categories of college major were
crossed with the four dominant functions. A significance level of .05 was
chosen for the test.

These tests were performed at the Michigan State University

Computer Center using the program written by Jeremy D. Finn.

Summar

In this chapter the methodology and instrumentation used in the
present study were discussed. One hypothesis investigating the relation-
ship of five cognitive style measures to each other in differentiating
three categories of college major and the sexes was presented. Another
hypothesis investigating the proportion of dominant Jungian types across

the three categories of major was proposed, and hypotheses relating

81

cognitive style variables to dominant type were presented. Two samples
of 150 students were tested, the second sample serving as a replication.
ACT-C and GPA were added for purposes of comparison with the five cogni-
tive style variables.

The method of soliciting subjects and carrying out the testing
was outlined. The strengths and weaknesses of the instruments were dis-
cussed. MANOVA, ANOVA, and chi-square were chosen as statistical tools.

In Chapter IV, the results will be presented.

CHAPTER IV
RESULTS

In this chapter the results of the statistical tests of the
hypotheses derived in Chapter III will be presented. The results of
tests of the major hypotheses via MANOVA will be followed by univariate
tests of the subhypotheses. Since the review of the literature provided
no basis for anticipating interaction effects, and the present author
did not have reason to believe they would exist for other reasons, no
hypotheses were formulated predicting interactions nor were any found.

The mean scores actually tested in each univariate analysis will
be included in tables and graphic representations for clarity of presen-
tation.. These mean scores are combinations of mean cell scores, which
with their standard deviations are presented in Appendices A, B, C, .
and D.

The tables reporting the results of the multivariate tests will
report them twice for each sampleI-with and without the ACT-C, which was
not available for all subjects. The purpose of dual presentation is to
examine the effect, if any, reducing the sample size to include ACT-C
might have on the overall F statistic and the step-down F test.

The dependent variables on the step-down F test were ranked to
gain maximum benefit from the test according to the priority of interest
in the dependent variables (Bock 6 Haggard, 1968). The GEFT was placed

82

83

first, since for both sex and major the literature suggests it would be
the most discriminating of the cognitive style variables. The MFF meas-
ures were placed next because the literature suggested that they offered
more promise of ability to discriminate majors than did the WIT. The
alpha level for the GEFT and the MFF was set at .05.

The WIT measures were judged to be of less crucial interest,
since the review of the literature had shown that their power to dis-
criminate groups was considerably diminished when scores from an entire
sample were used. If the measures did discriminate, safeguards against
it being a chance occurrence dictated the choice of an alpha level of .01.

The comparison measures, ACT-C and GPA, were of least crucial
interest. The review of the literature suggested that measures of cog-
nitive style were relatively independent of academic ability and mention
of the relation of college major to GPA is rarely made. These considera-
tions led to the choice of an .001 alpha level.

The tables reporting the results of the univariate hypotheses
will be presented for the full sample size of 150. The alpha level for

each univariate hypothesis will be that chosen for the step-down F test.

Test of Hypothesis 1

Ho There will be no differences with respect to average per-
formance on five cognitive style variables, grade point
average, and American College Test composite score in the
degree each contributes to the differentiation among three
categories of college major and between the sexes.

Table 2 presents the MANOVA table for Hypothesis 1. From Table
2 it can be seen that in Samples 1 and 2 the main effect by sex was

significant and in Sample 1 the main effect by major was significant.

Test of Hypothesis ls

84

TABLE 2

Multivariate Analysis of Variance for

Mean Differences on Five Cognitive Style Measures, Grade Point
Average, and American College Test Composite Score among Three
Groups of College Major and between the Sexes

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample 1
without ACT-C 4 With ACT-C
Source . df F df F
Major . 121278 2.9426*** 4 161152 2.3195**
Sex 6/139 3.5204** ¢ 7176 2.5541*
Interaction . 121278 1.5373 14/152 .4848
Sample 2
without ACT-C‘ with ACT-C
Source df 8 df F
Major . 12/278 1.7010 161210 1.2540
Sex 6/l39 2.6264"r 7/105 2.6401“?
Interaction lZ/278 .4352 . 14/210 .7583
* p 41.05
** pi<I.Ol

*** p 4.001

85

Table 3 reports the results of the step-down F tests for the main effect
by sex in Samples 1 and 2. From Table 3 it can be seen that in Sample 1
without ACT-C, GPA met the alpha criterion and that in Sample 2 without
ACT-C, GEFT met the alpha criterion. Since the findings were not upheld
in both samples, however, the results are inconclusive.

Also inconclusive is the effect of the reduced sample size and
addition of the ACT-C on the step-down F test. The difference in some
step-down F's is minimal but on others seems quite large, e.g., on the
GEFT. With addition of ACT-C and reduction in sample size in Sample 2,
the p value for GEFT was significant.

Table 4 reports the results of the step-down F tests for the main
effect by major in Sample 1. It can be seen that only the alpha level
for the GEFT met the alpha criterion. It can therefore be concluded that
in Sample 1 the GEFT was the measure which was most efficient in dif-
ferentiating the three groups of college major.

For the sake of completeness, data from the one-way ANOVA's are
presented. Table 5 presents the means for the one-way tests of signifi-
cance by sex for GPA and ACT-C. Table 6 presents the means for the one-
way tests of significance by major on the same measures. Figures 1 and
2 are graphic representations of these means and the individual cell
means by sex and major. Table 7 presents the one-way ANOVA tests for
these measures. From Table 7 it can be seen that only the main effect

by sex for GPA was significant in Sample 1.

86

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87

TABLE 4

Test of Hypothesis 1: Step-down F Test for Ability of Five
Cognitive Style Measures, American College Test Composite
Score,and Grade Point Average to Discriminate among Three

Categories of College Major in Sample 1

 

 

 

 

Without ACT-C ‘ With ACT-C "

Step- P less Step- P less Alpha
Measure down F than . down F than criterion
GEFT ‘ 7.8407 .0006* 4.9051 .0098* .05
MFF time . 1.1485 .3201 ‘ 1.8354 .1662 . .05
Mff error 1.0776 .3432 1.1936 .3085 .05
WIT correct . 1.9175 .1508 3.8003 .0266 .01
WIT clues 2.9705 .0211 ‘ 2.3053 .1065 ’ .01
ACT-C 1.5581 .2171 .001
CPA 1.6013 .2054 .4418 .6446 .001

 

 

 

 

 

* Significant at specified alpha criterion.

TABLE 5

Mean Grade Point Average and Mean American College Test
Composite Score between the Sexes

 

 

 

 

Grade Point American College Test
. Average Composite Score
Males Females . Males Females
Sample 1 . 2.75 3.05 .. 23.10 (N I 42) 23.11 (N I 46)

 

Sample 2 .' 2.78 3.03 . 22.98 (N . 54) 22.59 (N - 63)

 

 

 

88

TABLE 6

Mean Grade Point Average and Mean American College Test
Composite Score among Three Categories of College Major

 

 

Grade Point Average

 

 

 

 

 

 

 

 

 

 

 

 

 

 

i Humanities > Social Science Natural Science
Sample 1 b 2.78 u 2.87 3.05
Sample 2 . 2.91 2.95 2.86
American College Test Composite Score
Sample 1 4 21.88 (N826) . 22.03 (N-30) . 25.09 (N-32)
Sample 2 . 23.18 (N840) . 21.70 (N333) . 23.20 (N844)
3. 3 A" -AMa1es
Or-OFemales
g H Both
“.3 l
u - ,--o ........
3 o——"' a
m
c . _______
'8 A‘ " Ax \
o. ‘tt
3 2.7 \A
m
35
2.5 if - - , c -
Humanities Social Natural Humanities Social Natural
Science Science Science Science
Sample 1 Sample 2

Figure 1. Mean grade point average for three categories of

college major.

89

   

 

 

26 4 A-‘A Males
o--o Females
e—-e Both
25 4
0
24
8
o
D
3 23
v!
Q
o
o.
8 22
c2
21
20 , - c - 4
Humanities Social Natural Humanities Social Natural
Science Science Science Science
Sample 1 Sample 2

Figure 2. Mean American College Test composite score for three
categories of college major.

90

TABLE 7

Analyses of Variance for Differences between the Sexes

and among Three Categories of College Major in Grade Point Average
and American College Test Composite Score

 

 

Grade Point Average

 

 

Sample 1 Sample 2
Source df MS P df MS F
Major 2 .9138 3.5997 2 .0925 .4204
Sex 1 3.5205 13.8689* 44 1 2.2546 10.2521
Interaction 4 2 .2919 1.1501 2 .0644 .2928
Within cells 4 144 .253843 44 144 .219918

 

 

 

 

American College Test Composite Score

 

 

Sample 1 (N-88) Sample 2'2fi=1173""'
Source 4 df MS F fijdf MS F
Major 2 100.1553 6.8136 44 2 26.2889 1.5357
Sex 1 .0040 .0003 1 4.5179 .2639
Interaction 4 2 14.2093 .9667 2 15.7231 .9184
Within cells 4 82 14.699344 “ 111 17.119147

 

 

 

 

91

Test of Hypothesis la
“la Differences will exist in the degree of field-dependence-
independence as measured by group mean scores on the Group
Embedded Figures Test among humanities, social science, and
natural science majors with natural science majors scoring
highest (most field-independent) followed by social science,
then humanities majors.

Table 8 presents the mean GEFT scores obtained by the three groups
of college major and Figure 3 is a graphic representation of these mean
scores and the individual cell mean scores by sex and major. Table 9
presents the ANOVA table for Hypotheses la and lb.

Although the specified alpha levels were achieved for both .
samples on the main effect by major and the null hypothesis was rejected,
the alternate could not be accepted. The results were only partially in

the predicted direction.

TABLE 8

Mean Scores on the Group Embedded Figures Test
for Three Categories of College Major

 

 

Humanities 4 Social Science 4 Natural Science

 

Sample 1 4 11.3 11.2 14.3

Sample 2 4 13.8 4 11.7 13.6

 

 

 

 

Tukey post hoc comparisons were performed as shown in Table 10.
The results indicate that differences exist between natural science
majors and both humanities and social science majors in Sample 1 and
between social science and both humanities and natural science majors
in Sample 2. Therefore, in both samples, a difference between social

science and natural science majors was upheld in the predicted direction,

92

   

 

 

15 4 Ar-AMales
o-"o Females
e——~Both
‘5 l4 4
g
0 13 4
H
8
E 12
ll
10 ‘ ‘ . ¢ 4v v :
Humanities Social Natural Humanities Social Natural
Science Science Science Science
Sample 1 Sample 2

Figure 3. Mean scores on the Group Embedded Figures Test for
three categories of college major.

TABLE 9

Test of Hypotheses la and lb: Analyses of Variance for
Differences among Three Categories of College Major and
between Sexes on the Group Embedded Figures Test

 

 

 

 

 

—— Sample 1 Sample 2
Source df MS —iFT MS F
Major 2 157.1267 7.8407** 4 63.2267 4.0598*
Sex 1 : 1.5 .0749 20.1667 1.2949
Interaction 4 2 6.14 .3064 7.7867 .5000
Within cells 4 144 4 20.04 4 15.573889

 

 

 

 

 

** p<.01

93

natural science majors being more field-independent. However, humanities
majors scored higher than social science majors in both.samp1es and

significantly so in the second sample contrary to prediction.

TABLE 10

Confidence Intervals Based on Tukey Post Hoc Comparisons
for Hypothesis la: Differences among Three Categories of
College Major on the Group Embedded Figures Test

 

 

 

 

 

 

Sample 1 Sample 2
diff;’- Confidence d’ er- on ence
ence q interval ence q ginterval

 

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‘88“ i4. ' '3-0 t 2-11 (' o89- -5-11>* -1.9 t 1.87 (- .03. -3.77)*

 

 

 

* p <1.05

Test of Hypothesis 1b

 

Hlb Differences will exist in the degree of field-dependence-
independence as measured by group mean scores on the Group
Embedded Figures Test between males and females with males
being higher (more field-dependent).

Table 11 presents the mean GEFT scores obtained by the two sexes
and Table 9 presents the F values indicating no differences were found
between the sexes. It should be noted, however, that the differences
observed between males and females are in the predicted direction, the

males' scores being higher.

94

TABLE 11

Mean Scores on the Group Embedded Figures
Test for the Two Sexes

 

 

 

4 Males 4 Females
Sample 1 4 12.4 o 12.2
5.391. 2 ll 13.4 {T 12o?

 

 

 

Test of Hypothesis lc

ch Differences will exist in reflection-impulsivity as measured
by the group mean time score on the Matching Familiar Figures
Test among humanities, social science, and natural science
majors with natural science majors scoring longer times
(more reflective) followed by social science, than humanities

majors.
Table 12 presents the mean MFF time scores in seconds for the
three categories of college major and Figure 4 is a graphic representa-
tion of these mean scores and the individual cell mean scores by sex and

major. Table 13 presents the ANOVA tables for the test of the hypothesis.

TABLE 12

Mean Time Scores (in seconds) on the Matching Familiar Figures
Test for Three Categories of College Major

 

 

Humanities A Social Science 4 Natural Science

 

38-910 1 1 581s 36 632s 7‘ 1 678a 68

Sample 2 4 563.99 J 569.47 647.57

 

 

 

 

Though the differences were in the predicted direction in both

samples, in neither sample were they significant.

9S

   

 

 

A 800 4 Af'flMales
.3 o--oFemales
8 o——eBoth .4
5: 700 4
O
m
up.
" 600 .
5
500 1, .1 - -- -
Humanities Social Natural Humanities Social Natural
Science Science Science Science
Sample 1 Sample 2

Figure 4. Mean time scores (in seconds) on the Matching Familiar
Figures Test for three categories of college major.

TABLE 13

Test of Hypotheses 1c and 1d: Analyses of Variance for
Differences among Three Categories of College Major and between
the Sexes on the Time Score of the Matching Familiar Figures Test

 

 

 

 

Sample 1 Sample 2
Source df 4 MS F 4 MS F
Major 4 2 ‘ 118513.0867 1.2990 44 109293.8067 \ 1.2395
Sex 1 83544.0000 .9157 44 19.0817 .0002
Interaction 2 54667.3400 .5992 44 37704.1267 .4276
Within cells 144 91231.769722 88172.664028

 

 

 

 

 

 

Test of Hngthesis 1d

"1d Differences will exist in reflection-impulsivity as measured
by the group mean time score on the Matching Familiar Figures
Test between males and females.

96

TABLE 14

Mean Time Scores (in seconds) on the Matching
Familiar Figures Test for the Two Sexes

 

 

 

Males Females
Sample 1 4 654.53 4 607.33
Sample 2 4 593.32 4 594.03

 

 

 

Table 14 presents the MFF mean time scores for both sexes and
Table 13 presents the ANOVA table for test of the hypothesis. For sex

as for major, the null hypothesis was retained.

Test of Hypothesis 1e

H1. Differences will exist in reflection-impulsivity as measured
by the group mean error score on the Matching Familiar Figures
Test among humanities, social science, and natural science
majors with natural science majors scoring fewer errors (more
reflective) followed by social science, then humanities
majors.
Table 15 presents the mean MFF error scores for the three majors
and Figure 5 is a graphic representation of these mean scores and the
individual cell mean scores by sex and major. Table 16 presents the

ANOVA table for Hypotheses 1e and 1f.

TABLE 15

Mean Error Scores on the Matching Familiar Figures Test
for Three Categories of College Major

 

 

4 Humanities 4 Social Science 4 Natural Science

 

SWIC 1 1 10.36 1 8e60 1 6092

Sample 2 9.04 9.78 6.74

 

 

 

 

v___

97

 

 

 

12 Lyn-A Males
o—-o Females
e--e Both
11 r
10
3
E 9
m
8
7
\
6 - e a - - Q0:
Humanities Social Natural Humanities Social Natural
Science Science Science Science

Sample 1 Sample 2

Figure 5. Mean error scores on the Matching Familiar Figures Test
for three categories of college major.

TABLE 16

Test of Hypotheses 1e and 1f: Analyses of Variance
Differences among Three Categories of College Major and between the
Sexes on the Error Score of the Matching Familiar Figures Test

 

 

 

 

~—~ Sample 1 Sample 2
Source df 4 MS F MS F
Major 4 2 4 147.9461 3.8613" 44 125.6600 3.389S*
Sex 1 18.0267 .4705 44 15.3600 .4143
Interaction 2 30.9067 .8066 10.1400 .2735
Within cells 4 144 4 38.3150 44 37.072778

 

 

 

 

 

* p<.03

98

From Table 16 it can be seen that the null hypothesis of main
effect by major was rejected. Table 17 presents the Tukey post hoc

comparisons for this main effect.

TABLE 17

Confidence Intervals Based on Tukey Post Hoe Comparisons for
Hypothesis 1e: Differences among Three Categories of College Major
on the Error Score of the Matching Familiar Figures Test

 

 

 

 

 

Sample 1 Sample 2
‘differ- Confidence differ- Confidence
ence Interval ence Interval

 

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* p <I.05

The Tukey post hoc comparisons reveal significant differences
between humanities and natural science majors in Sample 1 and social
science and natural science majors in Sample 2 on the MFF error score.
Since the results were not consistent, the alternate hypothesis was not
retained. In the first sample the scores were in the predicted direc-

tion, but in Sample 2, the humanities majors made slightly fewer errors

than the social science majors.

Test of Hzggthesis 1f

“1f Differences will exist in reflection-impulsivity as measured

by the group mean error score of the Matching Familiar Figures
Test between males and females.

99

Table 18 presents the mean error scores for the two sexes.
Table 16 presents the ANOVA tables for the test of the hypothesis. As

can be seen from Table 16, the null hypothesis has been retained.

TABLE 18

Mean Error Scores on the Matching Familiar
Figures Test for the Two Sexes

 

 

 

Males Females
Sample 1 8.97 4, 8.28
Sample 2 4 8.84 4. 8.20

 

 

 

Test of Mmthesis lg

H18 Differences will exist in the degree of intuitive thinking
as measured by the group mean nuber correct score on the
flestcott Intuition Test among humanities, social science,
and natural science majors.

Table 19 presents the mean flIT nuber correct scores obtained by
three categories of college major and Table 20 presents the nova tables
for test of the hypothesis. Figure 6 is a graphic representation of
these mean scores and the individual cell mean scores by sex and major.

As can be seen from Table 20, the null hypothesis was retained.

100

TABLE 19

Mean Number Correct Scores on the Hestcott Intuition
Test for Three Categories of College Major

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
Sample 1 4 4.20 4 3.66 4 6.92
8‘91. 2 1 “s46 15 4.28 y “s72
6 6‘11 Males
.5 o——o Females
o ,0 s—s Both
E s ’ ’0
c
'i 4.
5
z:
3 f - - , e t
Humanities Social Natural Humanities Social Natural
Science Science Science Science
Sample 1 Sample 2

Figure 6.

Mean number correct scores on the Westcott Intuition
Test for three categories of college major.

101

TABLE 20

Test of Hypotheses lg and lhl

Analyses of Variance for Differences

among Three Categories of College Major and between the Sexes on
the Number Correct Score of the Westcott Intuition Test

 

 

 

 

Sample 1 Sample 2
Source df MS F MS F
Major 4 2 4 17.4467 4.4394 41 2.4467 .5274
Sex 1 4.1667 1.0602 8.1667 1.7605
Interaction 2 8.9267 2.2714 .2067 .0446
Within cells 4 144 4 3.9300 44 4.638889

 

 

 

 

 

Test of Hypothesis 1h

th Differences will exist in the degree of intuitive thinking
as measured by the group mean number correct score on the
Westcott Intuition Test among humanities, social science,
and natural science majors.

Table 21 presents the mean NIT number correct scores obtained by

the two sexes. Table 20 presents the ANOVA tables for test of the hypo-

thesis. As can be seen from Table 20, the null hypothesis has been

retained.

TABLE 21

Mean Number Correct Scores on the Hestcott
Intuition Test for the Two Sexes

 

 

 

4 Males 4 Females
Sample 1 4 4.07 4 4.40
Sample 2 4.25 4.72

 

 

 

Test of Hypothesis li

102

“1i Differences will exist in the degree of intuitive thinking
as measured by the group mean clue use score on the Nestcott
Intuition Test among humanities, social science, and natural
science majors with natural science majors scoring highest
(least intuitive) followed by social science, then humanities

msjors.

Table 22 presents the mean NIT clue use scores obtained by the

three categories of college major and Table 23 presents the ANOVA tables

for test of the hypothesis. Figure 7 is a graphic representation of the

mean scores and the individual cell mean scores by sex and'major.

TABLE 22

, Mean Clue Use Scores on the Nestcott Intuition
Test for Three Categories of College Major

 

W

 

7======Il=

 

Humanities Social Science Natural Science
M1. 1 14 31s98 14 3‘s‘6 1 ”s36
M1. 2 4 31s72 1 32s“ 1 30.90

 

 

 

 

From Table 23 it can be seen that the main effect by major was

significant in Sample 1, but that it was not upheld in Sample 2. Table

24 contains the Tukey post hoc comparisons for Sample 1. From Table 24,

it can be seen that the significant difference was between social

science and natural science majors.

103

   

 

 

36 1 A"AMales
o-woFemales
o—eBoth

35

34

-o

8 33

a

O

3

.4 32 4

U

31
\\
44
\

30 25

29 e - - - e

Humanities Social Natural Humanities Social Natural

Science Science Science Science
Sample 1 Sample 2

Figure ‘7. Mean clue use scores on the Westcott Intuition Test
for three categories of college major.

TABLE 23

Test of Hypotheses 11 and lj: Analyses of Variance for Differences
among Three Categories of College Major and between the Sexes on
the Clue Use Score of the Hestcott Intuition Test

 

 

 

 

Sample 1 Sample 2
.Sgurce 4 df 4 MS F MS F
Major 4 2 4 213.2067 5.0095* 44 47.4200 1.2896
Sex 1 77.7600 1.8270 21.6600 .5891
Interaction 2 10.2200 .2401 16.3400 .4444
within cells 144 42.560556 36.770556

 

 

 

 

 

104

TABLE 24

Confidence Intervals Based on Tukey Post Hoc Comparisons for
Hypothesis li: Differences among Three Categories of College Major
on the Clue Use Score of the Westcott Intuition Test in Sample 1

 

 

 

 

difference q Confidence interval
Y“ ~iss - -2.48 g 3.88 (1.40, -6.36)
"if" -3343 - 1.62 3 3.88 (5.50. -2.26)
{gs-ins - 4.10 g 3.88 (7.98, .22)*
* p ‘<.01

Test of Hypothesisglj

H11 Differences will exist in the degree of intuitive thinking
as measured by the group mean clue use score on the Host-
cott Intuition Test between males and females.

Table 25 presents the mean HIT clue use scores obtained by the

two sexes. Table 23 presents the ANOVA tables for test of the hypothe-
sis. As can be seen from Table 23, the null hypothesis has been

retained.

TABLE 25

Mean Clue Use Scores on the Hestcott
Intuition Test for the Two Sexes

 

 

‘ Males 0 Females

 

$818910 1 1 ‘ 31.55 14 32s99

Sample 2 31.44 32.20

 

 

 

105

Test of Hypothesis 2

Ho Differences will exist among humanities, social science, and
natural science majors as to the distribution in those major
categories of dominant sensors, dominant intuiters, dominant
thinkers, and dominant feelers as identified by the Myers-
Briggs Type Indicator.

Table 26 presents the chi-square tables for test of the hypothesis.

It can be seen that in neither sample was the chi-square value significant.
The null hypothesis was retained.

Although not a part of the original hypothesis, an extension of
the test of the relation of Jungian typology to college major was made by
utilizing the complete Jungian classification system of attitude with dom-
inant function. To provide a large enough N for a valid chi-square test,
subjects from both samples were combined. The results are presented in
Table 27. As can be seen from Table 27, the chi-square was significant.

Visual inspection of the distribution reveals the areas of
greatest differences among majors are with the introverted and extra-
verted sensing types, and extraverted intuitive and thinking types.
Introverted sensing types seem to favor the natural sciences over the
humanities, while extraverted sensing types favor natural science over
social science. Proportionally fewer extraverted intuitives are at-

tracted to the sciences and extraverted thinking types seem strongly

attracted to the humanities as opposed to the social sciences.

Test of Hypothesis 3

Ho There will be no differences with respect to average per-
formance on five cognitive style variables, grade point
average, and American College Test composite score in the
degree each contributes to the differentiation between
dominant sensors and dominant intuiters as identified by
the Myers-Briggs Type Indicator.

106

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108

TABLE 28

Test of Hypothesis 3: Multivariate Analysis of Variance for
Mean Differences on Five Cognitive Style Measures, Grade Point
Average, and American College Test Composite Score between

Dominant Sensors and Dominant Intuiters

 

 

 

 

df F
without ACT-C 4 6/74 1.0624
Sample 1
With ACT-C 4 7/41 1.1181
without ACT-C 6169 1.4780
Sample 2
Hith ACT-C 4 7/55 1.6146

 

 

Table 28 presents the MANOVA table for Hypothesis 3. It can
be seen that in neither sample was the F value significant. The null

hypothesis was retained.

Test of Hypothesis 3a

H3. Differences will exist in the degree of field-dependence-
independence as measured by group mean scores on the Group
Embedded Figures Test between dominant sensors and dominant
intuiters as identified by the Myers-briggs Type Indicator.
Table 29 presents the mean scores obtained on five cognitive
style measures used in the test of this and the next four hypotheses.
Means and standard deviations are presented in Appendices E and F.
Table 30 presents the ANOVA tables for test of this hypothesis and the
next four hypotheses.
As can be seen from Table 30 the null hypothesis was retained.
From Table 29 it can be seen that the direction of the difference in both

GEFT samples was the same: dominant intuiters tend to be more field-

independent than dominant sensors.

109

TABLE 29

Mean Scores on Five Cognitive Style Measures, Grade Point Average,
and American College Test Composite Score Obtained by
Dominant Sensors and Dominant Intuiters

 

 

 

 

 

 

 

 

 

Sample 1 Sample 2
44 Sensors Intuiters 44 Sensors Intuiters
(N=20) (N=61) (N=32) (N-45)
GEFT 11.75 11.96 12.44 12.77
MFF time 763.58 657.66 632.92 515.69
MFF errors 5.25 8.25 7.81 9.80
WIT correct 4.10 4.07 4.41 4.89
WIT clues 31.75 31.38 32.44 32.11
ACT-C 21.54a 23.47b 21.84° 22.39d
GPA 2.89 2.87 - 2.83 2.99
*3 Vsn.
b N - 38.
°N-2s.
d N e 38.

Test of Hypothesis 3b

H3b Differences will exist in reflection-impulsivity as measured
by the group mean time score of the Matching Familiar Figures
Test between dominant sensors and dominant intuiters as
identified by the Myers-Briggs Type Indicator.
As can be seen from Table 30 the null hypothesis was retained.
From Table 29 it can be seen that the direction of the difference in

both samples is the same: intuiters tend to be more impulsive.

110

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111
Test of Hypothesis 3c

33c Differences will exist in reflection-impulsivity as measured
by the group mean error score of the Matching Familiar
Figures Test between dominant sensors and dominant intuiters
as identified by the Myers-Briggs Type Indicator.
As can be seen from Table 30, the null hypothesis was rejected
in Sample 1 but retained in Sample 2. From Table 29 it can be seen
that the direction of the difference in both samples is the same: intui-
ters again tend to be more impulsive. This observation is consistent

with the observation on the other measure of reflection-impulsivity, the

time score.

Test of Hypothesis 3d

33d Differences will exist in the degree of intuitive thinking
as measured by the group mean clue use score of the Hestcott
Intuition Test between dominant sensors and dominant intui-
ters as identified by the Myers-Briggs Type Indicator.

As can be seen from Table 30, the null hypothesis was retained,

and Table 29 reveals the direction was not the same in both samples.

Test of Hypothesis 3e

H3. Differences will exist in the degree of intuitive thinking
as measured by the group mean number correct score of the
westcott Intuition Test between dominant sensors and domi-
nant intuiters as identified by the Myers-Driggs Type
Indicator.

As can be seen from Table 30, the null hypothesis was retained.
Though the difference is very slight, Table 29 reveals that intuiters
used fewer clues in both samples and therefore tend to be more intuitive

on this scale of the HIT.

112

Test of Hypothesis 4

Ho There will be no differences with respect to average per-
formance on five cognitive style variables, grade point
average, and American College Test composite score in the
degree each contributes to the differentiation between
dominant thinkers and dominant feelers as identified by
the Myers-Briggs Type Indicator.

Table 31 presents the MANOVA table for Hypothesis 4.

TABLE 31

Test of Hypothesis 4: Multivariate Analysis of Variance for
Mean Differences on Five Cognitive Style Measures, Grads Point
Average, and American College Test Composite Score between
Dominant Thinkers and Dominant Feelers

 

 

 

df F
'Hithout ACT-C 4 6162 .3476
Sample 1
Hith ACT-C a 7/33 .2648
Without ACT-C 4 6167 1.3300
Sample 2
Hith ACT-C 7/46 .8947

 

 

From Table 31 it can be seen that in neither sample was the F

value significant. The null hypothesis was retained.

Test of Hypgthesis 4a

Hg. Differences will exist in the degree of field-dependence-
independence as measured by group mean scores on the Group
Embedded Figures Test between dominant thinkers and domi-

nant feelers as identified by the Myers-Driggs Type
Indicator.

Table 32 presents the mean scores obtained on five cognitive

style:messurss used in the test of this and the next four hypotheses.

11

3

Means and standard deviations are presented in Appendices E and F.

Table 33 presents ANOVA tables for the test of this hypothesis and the

next four hypotheses.

TABLE 32

Mean Scores on Five Cognitive Style Measures, Grade Point Average,
and American College Test Composite Score Obtained by
Dominant Thinkers and Dominant Feelers

 

 

 

 

 

 

 

Sample 1 Sample 2“
Thinkers Feelers Thinkers r..1é§.
_gn-13)_, (N-SO), _§N818) (N-S6)
GEFT 13.57 12.36 13.17 13.54
MFF time 537.89 580.61 625.64 622.25
MFF errors 9.42 10.14 8.67 7.87
HIT correct 4.32 4.46 4.50 4.21
HIT c1008 32.79 33.36 29.89 31.86
ace-c 23.152" 23.07b 23.o7¢ 23.132‘l
GPA 2.96 2.91 2.70 2.95
9 N I 13.
b N - 28.
° N - 15.
d u - 39.

As can be seen from Table 33, the null hypothesis was retained.

Table 32 reveals that there was no consistency in the direction of

scores between samples.

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114

 

 

 

 

 

 

 

 

 

 

 

 

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115

Test of Hypothesis 4b

H4b Differences will exist in reflection-impulsivity as measured
by the group mean time score on the Matching Familiar Figures
Test between dominant thinkers and dominant feelers as
identified by the Myers-Briggs Type Indicator.
As can be seen from Table 33, the null hypothesis was retained.
Table 32 reveals that there was no consistency in the direction of

scores between samples.

Test of Hypothesis 4c

34c Differences will exist in reflection-impulsivity as measured
by the group mean error score on the Matching Familiar
Figures Test between dominant thinkers and dominant feelers
as identified by the Myers-Briggs Type Indicator.
As can be seen from Table 33, the null hypothesis was retained.
Table 32 reveals that there was no consistency in the direction of

scores between samples.

Test of Hypothesis 4d

"4d Differences will exist in the degree of intuitive thinking
as measured by the group mean clue use score of the Hest-
cott Intuition Test between dominant thinkers and dominant
feelers as identified by the Myers-briggs Type Indicator.

As can be seen from Table 33, the null hypothesis was retained.

Table 32 reveals that there was no consistency in the direction of scores

between samples.

116

Test of Hypothesis ae

 

“he Differences will exist in the degree of intuitive thinking
as measured by the group mean number correct score on the
westcott Intuition Test between dominant thinkers and
dominant feelers as identified by the Myers-Briggs Type
Indicator.

As can be seen from Table 33, the null hypothesis was retained.

Though the difference is very slight, Table 32 reveals that thinkers

used more clues in both samples, and therefore tend to be more intuitive

on this scale of the WIT.

Summary

Table 34 presents in summary form the results of the multivariate
hypotheses and those univariate hypotheses which dealt with the relation-
ship of cognitive style, GPA, and ACT-C to the three categories of college
major. Table 34 reveals that the main effect by sex was significant in
both samples, but that in only one sample did a measure--GPA--meet the
alpha criterion. This result is complicated by the fact that GEFT met
the alpha criterion in the sub-sample with ACT-C. The results are
therefore inconclusive as to differentiation between the sexes.

A main effect by major was found in Sample 1 and GEFT was found
to differentiate the majors best. Therefore, there is a suggestion that
field-dependence-independence is the construct which best differentiates
the categories of college major.

Subhypotheses concerning the relation of college major to cogni-
tive style were examined through one-way analyses of variance. Majors
were differentiated on three measures but only on two measures did they
survive replication. While some measures were not found to be significant,

results were in the predicted direction.

117

TABLE 34

Summary of Results on Multivariate Hypotheses and
Univariate Subhypotheses concerning Cognitive Style and Major
(Based on the Full Sample Size, M 8 150 Each Sample)

Multivariate Hypotheses

 

 

 

 

 

 

 

 

 

 

 

 

 

Main effect Step-down F

Hypo- Major Sex Major Sex

theses Sample 1 2 ‘ Sample 1 2 ¢¢ Sample 1 2 . Sample 1 2
”1 yes no . yes yes ,¢ yes no 1 yes no
H3 no no - - - - r '
H4 no no - - .¢ - - r -

Univariate Subhypotheses

Subhypo- Main Effect Direction

theses . Sample 1 Sample 2 , Sample 1 Sample 2
“la yes yes no no
Hlb no no yes yes
ch no no yes yes
Hld no no - -
H19 yes yes yes no
Hlf no no - -
H18 no no - -
th no no - -
H11 yes no no no
Hlj no no - -

1

 

 

 

 

118

Differences between social and natural science majors existed on
the GEFT in both samples. Natural science majors were more field-indepen-
dent. while differences by sex were not significant in either sample,
males tended toward field-independence in both. On the MFF time score,
natural science majors tended to be reflective followed by social science
majors, then humanities majors, though the differences were not significant.

On the MFF error score, majors were differentiated in both samples
in the predicted direction in one sample but not the other. Nor were the
areas of differentiation consistent. In both samples, natural science
majors were differentiated, but in one sample they were differentiated
from humanities majors and in the other, from social science majors.

The WIT clue use score differentiated majors in the first sample
but not in the second. In that first sample the differentiation was be-
tween social science and natural science majors, the natural science
majors being more intuitive.

Dominant Jungian functions were not found to be clustered by
major. However, when the dominant function was paired with the attitude
of extraversion or introversion, some clustering of the types into major
categories was observed.

The investigations relating cognitive style to Jungian dominant
functions yielded but one difference in one sample. The MFF error score
differentiated dominant sensors from dominant intuiters. However, dif-
ferentiation of dominant sensors and dominant intuiters was in identical
and logical directions on four of the five measures in both samples. When
the same investigation was carried to dominant thinkers and dominant
feelers, results were negative and inconsistent in all but one direction.

Dominant thinkers consistently scored lower on the WIT clue use score.

CHAPTER V

SUMMARY AND CONCLUSIONS

Summary

That the campus counseling psychologist's expanding role may
well place him in the position of consultant to faculty on the academic
dimensions of the collegiate experience provided impetus for the present
study. It was proposed that an investigation dealing with the personal
ways people approach learning situations-a concept to which the term
"cognitive style" is frequently attached-could provide information
useful to the counseling psychologist in his new role.

Cognitive style was to be investigated through the medium of
college major. Discovering a relationship between the two could be
useful for assisting faculty in understanding their students better and
it could provide information useful to the counseling psychologist in
dealing directly with students' concerns over choice of major. Know-
ledge of the variation in learning styles could assist the counseling
psychologist in understanding and dealing with his clients' styles.

Following a general discussion of cognitive style, the specific
cognitive style dimensions utilized in the present study-~field-dependence-
independence, reflection-impulsivity, intuition, and Jungian typology--
were discussed. Thereview of the literature indicated that field-

119

120

dependence-independence, a widely researched construct, provided the most
hope for differentiating majors. The dimension of reflection-impulsivity,
well established in the realm of educational psychology, provided the
second dimension, though research on its relation to college major was
scanty. The work of Malcolm Hestcott on intuition-less well known but
having important implications for instructional practiceb-was chosen.

The Jungian functions of sensation, intuition, thinking, and feeling pro-
vided the fourth subject area. Previous research suggested strong links
between the functions and college major.

Research pointing to the relation of other cognitive styles to
college major was presented.

Multivariate analysis of variance was chosen to analyze mean
differences on related measures of cognitive style between three categories
of college~major--humanities, social science, and natural science--and
between the sexes, and chi-square was chosen to analyse the distribution
of dominant functions across major categories. Investigation of the rela-
tion of the cognitive style measures across the categories of dominant
‘ Jungian function was also performed using multivariate analysis of
variance.

Two samples of 150 undergraduate students equally divided through
the three majors and two sexes were solicited to volunteer as subjects in
the study. The first sample was drawn during the spring mini-session and
in the summer term of 1973 and the second sample drawn in the first three
weeks of the fall term of 1973. Since aptitude and intelligence have been
found in some cases to be marginally related to cognitive style, ACT-C and
the other most common measure of academic achievement, GPA, were included

as comparison measures.

121

Conclusions

No hypothesis in the study was confirmed as stated across both
samples. What results there were suggested the following.

1. The dimension of field-dependence-independence as measured
by GEFT (Witkin) best differentiates college majors.

2. College majors can be differentiated on the basis of Jungian

typology if type is assessed using both attitude and dominant
function.

Discussion

 

The results of the present study do not give strong support to the
thesis that cognitive style is related to college major, but neither do
they negate it. The evidence cited in the review of the literature also
points to a significant but small factor in the differentiation of college
majors. Probably students majoring in different areas do have variations
in cognitive style but they are most apparent only in a few individuals
or at certain times. It is a characteristic of which the knowledgeable
professor should be aware and should utilize when the need arises. Per-
haps in assisting an individual student to acquire a difficult concept,
another approach more in keeping with that student's learning style might
be tried.

The findings of the present study also give support to the hypo-
thesis that field-dependence-independence taps more than acadmic ability.
It seems to be a more inclusive variable, consisting of stylistic variations,
thus continuation of the designation, "cognitive style,” seems warranted.
The only evidence to the contrary is that low level, but significant,
correlations of .32 and .2h (p‘<;.01) between ACT-C and GEFT scores were
found. (See Appendix H.) Also ACT-C was found to correlate with more

cognitive style variables than any other measure.

122

As evidence supporting the hypothesis, the results of the step-
down F tests show that GEFT discriminates majors at a much higher p value
than ACT-C, despite the fact that the pattern by which they differentiate
majors is similar, as shown in Figures 2 and 3. Also in support of the
hypothesis is the finding that, although ACT-C correlated with more cog-
nitive style variables than any other measure, the variables (MFF errors
and WIT correct) were that component of the measure least concerned with
differentiation in style of approach to the problem. MFF errors and WIT
correct estimate the end product of cognitive effort, not the style by
which the end product was achieved.

Goldschmid (1967) proposed that on the continuum from natural
science to humanities, social science would stand as a mediating link.
Evidence from the present study suggests that it is more often at one of
the extremes. A visual inspection of the group means show that the social
science majors were the most field-dependent and the least intuitive on
both the WIT scales. The finding that social science majors are most
field-dependent can be explained when it is recalled that the review of
the literature revealed that field dependents were more oriented to their
social context. That natural science majors were most intuitive can be
explained by the fact that, particularly in the natural sciences, the

greatest information must be inferred from the fewest facts.

Limitations

 

The present study had two primary limitations. First, the im-
practicality made random selection an impossibility. So that valid in-
ferences may be drawn, the reader must compare samples to see if they
could have been drawn from the hypothetical population which samples in

the present study represent.

123

The fact that Sample 1 was drawn from a significantly older group
attending shortened spring and summer sessions and that Sample 2 was drawn
from a younger group attending a regular term makes more difficult the
task of determining whether failure to replicate the experiment in Sample
2 was that the samples represented different hypothesized populations or
whether there was in fact no relationship between college major and cog-
nitive style.

Another limitation concerns itself with the intra-discipline
variation of the three categories of major, i.e., some disciplines have
within themselves science to humanities orientations. Such is the case
of speech. At Central Michigan University, theatre, interpersonal and
public communication, and speech pathology are all areas in which speech
majors may concentrate. The same type of variation may be found in a
social science area, psychology, and an area classified as a humanity,

journalism.

Implications for Future Research

Should the present study ever be replicated, assurance that the
two samples were drawn from the same population would be necessary.

Though the issue is peripheral to the present study, the review
of the literature and issues discussed in the previous section suggest
that a further clarification of the relation of field-dependence-
independence and measures of academic ability would be fruitful.

Most of the research on reflection-impulsivity has shown relevance
of the dimension to other intellectual characteristics. Further investi-
gation into other areas such as has been done by workers investigating

field-dependence-independence could expand the usefulness of the concept.

124

Campbell (1967) identified through multivariate procedures a
helping people vs. business dimension. Perhaps the relation of cognitive
style to this dimension of college major could be investigated with
profit.

Perhaps the most fruitful area for further research lies in the
area of Jungian typology via the MBTI. The method of analysis using dis-
crete data makes it possible that valuable information was lost. There-
fore using continuous MBTI scores, particularly in the area of relating
dominant type to cognitive style, may be fruitful. Also as was noted in
the discussion of the test of Hypothesis 2, including the total type in
the analysis led to significant findings. Perhaps yet more could be

learned by including the auxiliary process in the analysis.

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Williams, C. The pervasiveness of cognitive preferences. Dissertation
Abstracts International, 1971, 31, 4565.

Hitkin, H., Dyk, R., Faterson, H., Goodenough, D., 6 Harp, S. Psycho-
lggical differentiation. New York: Wiley, 1962.

Witkin, H. A., Lewis, H. D., Hertzman, M., Machover, M., Meissner, P.,

6 Hapner, 3. Personality through pgrception. New York: Harper,
1954.

Hitkin, H. A., Oltman, P. M., Raskin, E. A., 6 Karp, S. A. ‘éLmanual
for the Embedded Figures Tests. Palo Alto, California: Consulting
Psychologists Press, 1971.

Ziegler, B. A. A measure in search of a theory. Contggporary‘ggyghglggy.
1963’ 8 ' 133-13Se

APPENDICES

APPENDIX A

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,

GRADE POINT AVERAGE, AND AGE FOR SAMPLE 1 WITH

AMERICAN COLLEGE TEST COMPOSITE SCORE

Sample 1 Cell Size by Sex and Major

TABLE A1

 

 

 

 

 

 

 

 

 

 

 

N888 Humanities Social Science Natural Science
Males T 12 L 16 T 14
Females . 14 y 14 y 18
TABLE A2
Group Embedded Figures Test
Humanities Social Science Natural Science
__ ' 1’ sn ‘3? so ‘1? 80
Males ¢ 11.0833 3.9648 , 10.4375 4.9929 0 14.2143 3.2387
11.8571 3.6973 . 12.0714 4.7631 0 14.1111 2.9880

Females +

 

 

 

 

130

131

TABLE7A3

Matching Familiar Figures Time

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
7 so T so 7’ sow
Males 7 563.1250 234.0606 586.8437 233.1506 7 720.7857 223.2174
Females 7 510.3929 245.5660 7 618.2143 313.0689 7 642.2778 220.9241
TABLE A4
Matching Familiar Figures Errors
Humanities Social Science Natural Science
' 1? so ”I so ‘2’ so
Males 7 13.8333 10.2499 7 8.2500 3.3566 7 7.2857 5.1505
Females 7 9.4286 8.4918 7 8.7857 5.8989 7 6.3889 6.0112
TABLE A5
Westcott Intuition Test Correct
Humanities Social Science Natural Science
' '1" so if so if so
Males 7 4.1667 2.0375 7 2.9375 110626 7 4.5714 2.1738
Females 7 4.5000 1.7867 7 3.7857 2.0821 7 5.0556 2.2353

 

 

 

 

132

TABLE A6

Westcott Intuition Test Clue Use

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
_‘T so 3? so it so
Males J 31.9167 6.2734 7 32.2500 7.7158 7 27.7857 5.1914
Females J 31.9286 6.3907 7 35.4286 7.2929 J 31.4444 6.4828
TABLE A7
American College Test Composite Score
:::*
Humanities Social Science Natural Science
T so T so ‘7 so
Males , 22.9167 4.2310 J 21.8125 3.4490 7 24.7143 4.7138
Females J 21.0000 4.2245 7 22.2857 3.6675 . 25.3889 2.8105
TABLE A8
Grade Point Average
Humanities Social Science Natural Science
1? so T so T so
Males 7 2.6000 .5134 J 2.6956 .5041 J 2.8543 .5924
Females J 2.9550 .5291 J 2.9936 .6061 J 3.2383 .4983

 

133

 

 

 

 

TABLE A9
Age
Humanities Social Science Natural Science
"""T so _‘2‘ so Y so
Hales 7 21.8333 1.7495 7 22.0625 1.8786 7 21.2143 1.7177
Females 7 20.4286 1.2225 J 20.3571 1.1507 6 20.2222 .9428

 

 

 

 

APPENDIX B

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,
GRADE POINT AVERAGE, AND AGE FOR SAMPLE 1 WITHOUT

AMERICAN COLLEGE TEST COMPOSITE SCORE

TABLE Bl

Sample 1 Cell Size by Sex and Major

 

 

 

 

 

 

 

 

 

 

 

N8150 Humanities Socia1 Science Natural Science
M8128 q 25 y 25 u 25
Females 7 25 J 25 J 25
TABLE B2
Group Embedded Figures Test

Humanities Social Science Natural Science

T so 7 so “if so
Hales 11.72 4.6683 7 10.96 5.0206 7 14.44 3.2924
Females J 10.84 4.9555 . 11.48 5.4323 7 14.20 2.8868

 

 

 

134

 

Matching Familiar Figures Time

135

TABLE B3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
J Y so 7 so T so
Males 7 620.22 349.1914 618.40 372.8969 7 724.96 285.1040
Females 7 542.50 251.9368 7 647.08 308.6467 7 632.40 215.3711
TABLE B4
Matching Familiar Figures Errors
Humanities Social Science Natural Science
1? so T so ’2 so
Hales 7 11.20 8.6603 7 8.04 3.4578 J 7.68 4.7233
Paul-e, 9052 701770 J A 9016 603815 1 6016 503282
TABLE BS
Westcott Intuition Test Correct
Humanities Social Science Natural Science
1? so ‘2‘ so if so
Hales 7 4.52 2.0232 7 3.28 1.5684 7 4.40 2.2174
Females 3.88 1.9858 7 4.04 2.0!00 7 5.28 2.0314

 

 

 

 

136

TABLE B6

Westcott Intuition Test Clue Use

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
Y so Y so Y so
Hales 7 31.64 5.9992 7 33.24 7.3387 7 29.76 5.3796
Females 7 32.32 7.0871 7 35.68 7.1281 7 30.96 5.9615
TABLE B7

Grade Point Average

 

 

 

 

Humanities Social Science Natural Science
Y so Y so Y so
“3198 J 205460 06742 2.7868 .4512 J 209028 05831

Females 7 3.0144 .5368 7 2.9516 .5368 7 3.1888 .4589

 

 

 

 

APPENDIX C

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,
GRADE POINT AVERAGE, AND AGE FOR SAMPLE 2 WITH

AMERICAN COLLEGE TEST COMPOSITE SCORE

TABLE Cl

Sample 2 Cell Size by Sex and Major

 

 

 

 

 

 

 

N-117 Humanities Social Science Natural Science

M818! 7 17 1 15 0 22

Females J 23 7 18 7 22
TABLE C2

Group Embedded Figures Test

 

 

 

 

Humanities Social Science Natural Science
‘ Y so if so Y so
Males 7 14.7059 2.8453 7 13.9333 3.6345 7 13.6364 3.6062

Females 7 13.4348 3.6034 7 10.6111 4.1036 7 13.5000 3.7129

 

 

 

 

137

Matching Familiar Figures Time

138

TABLE C3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
R SD TIE so SEPT SD
Males 7 539.8529 257.6914 7 634.5333 320.5212 7 636.1591 321.8926
Females 7 585.5870 225.3590 7 542.6667 375.2525 7 660.0000 315.7025
TABLE C4
Matching Familiar Figures Errors
Humanities Social Science Natural Science
'7 Y Y so 7 7 so
Males 8.7647 7.6692 9.2667 6.7978 7 7.5909 4.2388
Females 7 8.6522 4.8393 10.3333 6.5530 7 5.7727 5.0984
TABLE CS
Westcott Intuition Test Correct
Humanities Social Science Natural Science
' I so f so I so
Males 7 4.5882 1.8391 7 4.0000 1.2536 7 4.5455 2.0172
Females 7 4.8696 1.5755 7 4.7778 2.2375 7 5.1818 2.7540

 

 

 

 

139

TABLE C6

Westcott Intuition Test Clue Use

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
7 1? so 7 5? so 7 if so
Hales 7 32.6471 5.3495 34.2667 6.1000 7 30.5000 5.6967
Females 7 32.4348 6.8213 7 32.5556 4.8776 7 31.9545 6.5282
TABLE C7

American College Test Composite Score

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
7 5? so if so 7 it so
Males 7 23.5882 4.1391 7 22.6000 3.9424 6 22.7727 4.2976
Females 7 22.8696 3.9347 7 20.9444 5.1389 7 23.6364 3.3173
TABLE CB

Grade Point Average

 

 

 

 

Humanities Social Science Natural Science
7 T SD 1 SD 1 SD
"ale, 1 208935 04685 7 208640 04920 4 206882 04696

Females 7 3.0087 .4652 7 2.9867 .4612 7 3.0568 .4582

 

 

 

 

140

 

 

 

 

TABLE C9
Age
Humanities Social Science Natural Science
T so 7 7 so T" so
Males 7 20.7059 1.2632 7 20.4667 2.2636 7 21.3636 1.8138
Females 7 20.2609 1.1762 7 20.2778 1.7758 7 19.5909 1.0980

 

 

 

 

APPENDIX D

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,
GRADE POINT AVERAGE, AND AGE FOR SAMPLE 2 WITHOUT

AMERICAN COLLEGE TEST COMPOSITE SCORE

TABLE D1

Sample 2 Cell Size by Sex and Major

 

 

 

 

 

 

 

N-150 Humanities Social Science Natural Science

Males 7 25 7 25 7 25

Females 7 25 7 25 J 25
TABLE D2

CroUp Embedded Figures Test

 

 

 

 

 

Humanities Social Science Natural Science

‘7 '1 so it so T so
Males 7 13.96 4.0976 7 12.56 4.7441 7 13.68 3.5204
Females 7 13.60 3.5237 7 10.92 4.0714 7 13.48 3.5721

 

 

 

 

141

142

TABLE D3

Matching Familiar Figures Time

 

 

 

 

Humanities Social Science Natural Science
7' I so 7 T so 7 T so
Males 7 543.72 276.1963 7 600.44 298.9831 7 635.80 316.1425

Females 7 584.26 239.3444

 

538.50 320.7193 7

 

 

659.34 321.3534

 

 

 

 

 

TABLE D4
Matching Familiar Figures Errors
Humanities 'Social Science Natural Science
" so 7 1 so r so
Males 7 8.92 7.3707 7 10.08 6.2378 7.52 4.6915
Females 7 9.16 6.2161 9.48 6.2857 7 5.96 5.3889

 

 

 

 

TABLE D5

Westcott Intuition Test Correct

 

 

 

 

Humanities Social Science Natural Science
7 1? so 7 Y so if so
"‘19; J ‘00 20 20 1409 7 4 0 12 20 0678 1 ‘04“ 10 9596

Females 7 4.72 1.8148

 

7 4.44 2.2376 7

 

 

5.00 2.6300

 

7|

143

TABLE D6

Westcott Intuition Test Clue Use

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Humanities Social Science Natural Science
‘ I so I so 7. I so
Males 7 31.00 6.4356 7 33.12 5.8189 7 30.20 5.5151
Females 7 32.44 6.6588 7 32.56 5.5308 7 31.60 6.3246
TABLE D7
Grade Point Average
Humanities Social Science Natural Science
7 so if so 7 a! so
Males 2.8204 .4428 2.8308 .4996 2.6996 .4588
866.16. 7 3.0016 .4594 7 3.0624 .5037 J 3.0224 .4456
TABLE D8
Age
7 Humanities Social Science Natural Science
7 ’1 so 1! so 7 If so
Hales 7 20.84 1.2138 20.72 2.8065 7 21.44 1.8726
Females 7 20.84 2.7940 7 20.96 2.6690 7 19.64 1.1504

 

APPENDIX E

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,

GRADE POINT AVERAGE, WITH AND WITHOUT AMERICAN COLLEGE TEST

COMPOSITE SCORE BETWEEN DOMINANT JUNGIAN TYPES IN SAMPLE 1

144

145

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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APPENDIX F

MEANS AND STANDARD DEVIATIONS FOR THE FIVE COGNITIVE STYLE MEASURES,

GRADE POINT AVERAGE, WITH AND WITHOUT AMERICAN COLLEGE TEST

COMPOSITE SCORE BETWEEN DOMINANT JUNGIAN TYPES IN SAMPLE 2

147

148

 

 

 

 

 

 

 

 

 

 

 

 

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Column

10

11

Major 8 1
2
3
Sex I 1
2
Type '1
2
3
4

APPENDIX G

RAW DATA

Humanities
Social Science
Natural Science

Male
Female

Dominant Sensor
Dominant Intuiter
Dominant Thinker
Dominant Peeler

Group Embedded Figures Test

Matching Familiar Figures Time

Hatching Familiar Figures Errors

Westcott Intuition Test Clues Used

Westcott Intuition Test Number Correct

American College Test Composite Score

Grade Point Average

Age

150

Cohmm

Sample 1

...-I
N

HNNNNNUNHUF‘WUFNNUNUHNNWNU’WHWUWNWWNNI-‘WNWUNNHHNHF‘NHP‘

NNNo—o-nr-Nv—Nv—NHr—NHHHNHHNNHHNHHNNI—Hv—NNHNNHNNNNHNNHHI—HN

U

‘prw’NHbkw’N”#HU’H’NNNUNNW‘FWF‘HHHNN#NNUW’»’NW-b~#~u~4b

07
10
17
13
14
11
15
14
12
14
15
10
12
17
14
07
18
14
06
18
15
16
13
15
17
17
18
15
14
13
17
12
17
15
17
13
15
15
13
06
09
18
15
13
10
17
14
03
13
11

1024.0
0395.0
0522.5
0421.5
0612.5
0719.5
0509.0
0904.5
1393.0
0502.5
0745.5
0875.0
0597.0
0130.5
0619.5
0595.5
0286.0
0668.0
1200.0
0674.0
0675.0
0866.5
0931.0
0267.5
0623.5
0445.0
0759.5
0941.5
0495.5
1048.5
0481.0
0653.5
0580.0
0684.0
0222.0
1689.5
0521.0
0537.5
1026.0
0265.5
0413.5
0809.5
1478.5
0651.5
0333.0
0207.0
0821.5
0820.0
1429.5
0808.0

04
17
05
06
13
05
04
14
01
02
07
07
06
25
03
10
19
00
03
08
03
02
00
12
11
07
06
07
08
02
07
09
09
04
12
03
03
10

21
19
03
05
01

08
05
17
04
11

05
05
05
03
06
O7
05
05
04
06
04
04
05
03
07
01
09
05
04
02
04
06
04
06
05
08
03
05
05
06
04
02
02
03
03
04
02
03
03
05
01
06
06
02
04
04
04
04
01
04

28
27
27
39
30
45
35
32
31
31
34
23
38
34
25
25
32
32
34
26
30
33
39
31
33
30
33
20
34
37
28
38
37
23
29
31
49
28
24
37
31
36
34
36
41
37
28
40
25
19

22

24
24
25
27

28

27
26
22

22

21
25
17

22
24
21

23

28
21
19
15
24

21
25

28

26

10

3.64
2.91
3.47
2.29
3.62
3.49
2.61
2.04
3.64
2.64
3.89
2.72
3.09
3.69
3.20
3.14
3.53
2.87
2.51
2.48
3.58
2.65
3.13
1.97
3.34
3.33
3.60
2.88
3.13
2.95
2.89
2.15
2.63
2.82
3.34
2.83
3.70
3.23
2.90
2.49
2.13
2.79
2.93
2.75
2.31
3.12
2.75
2.23
3.65
2.23

11

20
21
31
24
21
20
21
22
41
23
21
21
19
21
19
55
25
22
24
25
30
22
19
25
26
20
20
21
21
21
21
27
23
20
25
37
26
21
19
22
22
21
22
19
22
21
22
20
21
20

Column

Sample 1
continued

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05
13
16
18
05
08
07
17
11
17
12
08
14
14
01
07
18
11
09
16
13
15
13
16
10
06
11
12
10
16
09
11
18
18
17
08
03
03
11
17

0835.0
0913.5
1159.0
0883.0
0285.5
0166.5
0633.5
0487.5
0966.5
0448.5
0614.0
0526.0
1107.5
0499.5
0874.0
0162.5
0845.5
0514.0
0322.0
0251.5
0330.5
0617.5
0560.5
0472.0
0266.0
0465.0
0633.0
0349.0
0576.5
0206.0
0547.0
0609.5
0800.5
0453.5
0506.5
0393.5
0388.5
0858.0
0482.5
0791.5
0681.0
0806.5
0167.5
0758.5
0611.5
0286.5
0534.5
0231.5
1512.5
1164.5

04
05
00
00
20
15
12
12
02
17
05
06
09
10
03
19
10
13
14
15
09
09
28
11
13
04
07
21
06
16
07
09
07
10
12
09
03

.07

09
02
O8
04
16
03
06
35

13
02
05

03
02
02
07
03
03
06
06
06
03
06
07
07
03
02
01
02
08
04
08
05
03
02
01
03
01
07
03
04
05
07
06
02
04
06
07
06
05
01
05
05
03
06
09
04
02
02
01
06
07

41
38
28
31
22
32
30
32
34
34
31
34
37
34
33
30
16
28
29
35
24
39
34
41
49
35
31
28
43
25
29
21
23
21
34
38
27
30
32
39
30
32
27
23
30
46
29
45
24
35

26
25
27
27
27

22

21
21

23
22

16
28

23
18

15
24

17

25
28

24
28
23
23
26
22
23
28

13

10

2.69
3.03
2.46
3.24
2.68
3.63
3.39
3.55
2.45
2.29
2.26
3.56
3.16
3.17
3.41
2.52
2.08
2.19
3.71
2.06
3.16
2.45
3.07
2.45
2.40
2.42
3.58
2.45
3.00
3.54
3.69
3.69
3.71
3.00
2.17
2.99
2.25
1.86
2.47
2.29
3.08
3.25
3.32
2.89
2.10
2.44
2.76
2.36
2.26
2.55

11

22
23
21
21
22
18
20
22
22
20
20
20
19
22
24
21
20
23
17
21
25
21
19
26
22
21
22
22
21
20
21
19
19
24
22
24
24

20
21
21
21
21
20
26
22
21
26
24
23

Cohmm

Sample 1
continued

HWNNNNwr-wHwNNwNo-uwwwNNwmwwwNwaNNNNwHuH-Hur‘uNWv—HHNr-w

NNHNHHNNNNF‘F‘NNHNNO-‘NO-‘Nl-‘NI-‘NNNNNI—NNNHNHHNNNHNHNNF‘HHHN

FWNUUNJ‘NNNNNNJ‘NHWNNJ‘J-‘NNNWJ‘#HHNbNHNNNHHw-bNI-‘NNJ‘NNNHJ‘

15
07
13
00
17
10
12
10
14
18
17
04
11
13
13
16
O3
14
10
02
18
08
12
18
17
14
06
15
18
14
16
14
18
17
00
09
15
14
05
14
09
08
02
18
07
17
16
17
16
15

0638.0
0878.0
0840.5
0515.5
1297.5
0145.5
0725.0
0787.5
0431.0
0230.5
0525.5
0358.5
0565.0
1386.5
0821.0
0574.0
0818.5
0771.0
0226.0
0642.5
0821.5
0678.5
0331.5
0709.5
0222.5
0585.0
0752.5
0901.0
0662.0
0320.5
0412.5
0425.5
0749.5
0478.5
0320.5
0304.5
0667.5
0831.0
0366.5
0425.5
0444.0
0911.5
0459.5
0868.0
0676.0
0245.5
0613.0
0204.0
0824.0
0813.0

09
08
02
21
02
33
06
07
07
13
04
05
09
04
02
07
10
04
20
19
05
02
09
03
13
08
04
11
03
09
07
11
12
06
17
09
05
03
14
04
06
04
15
02
05
12
03
14
03
03

04
O7
03
03
04
01
04
03
06
05
08
03
05
00
05
03
03
03
00
03
09
07
04
03
05
07
02
03
05
06
06
09
07
04
00
02
05
02
04
04
05
03
00
05
04
02
06
03
03
06

29
28
32
30
32
29
34
21
35
38
35
27
42
31
39
21
32
44
25
46

29

27
22
39
44
33
25
38
19
36
44
31
28
32
31
31
32
43
47
27
42
33
32
21
33
37
39
26
47
30

27

18
29
19

27
16
15

22
22
24

23

33
27
14
26

20
21
24
27
19

27

22
28
22
16
28
20
25

26
21
19
29
19
26

10

3.52
2.71
3.16
2.13
1.97
2.65
2.61
2.20
3.12
2.44
4.00
3.46
2.21
2.70
2.33
2.63
3.62
2.72
2.32
3.25
3.72
3.75
2.47
3.71
3.13
3.08
2.26
3.79
3.67
2.66
2.67
3.98
3.62
3.30
2.72
2.68
2.71
2.15
2.91
3.08
2.62
2.84
3.21
3.17
2.05
2.50
3.65
2.58
2.69
2.56

11

20
24
22
34
20
21
21
23
20
20
18
20
22
25
25
21
22
22
19
35
21
20
21
19
27
21
22
20
22
19
22
20

20
22
21
19
20

20
20
20
21
21
23
21
19
26
21
19

Cohmm

Sample 2

HNNHU’NNNWNNWNHWwwr-‘NUWWNNWHWHHNHWNWNHWHNWHHHNNWWNNW

NNNNNNHNNNP‘NNNP‘HNNNNHNNNNHHHHFHNHNNNHNHHHHHHHHNHNH

N¢waHwNNHHbeHHbebubmrmbwwbv—wbbbNNbv-wo-‘bmmwbwb##‘H

15
06
17
15
17
14
07
14
05
09
17
16
14
11
11
15
13
14
10
18
02
16
18
17
13
07
17
05
12
08
08
12
16
12
10
13
17
12
17
06
16
14
11
18
O7
18
17
11
04
18

0172.0
0352.5
0920.0
0311.0
0794.0
0740.0
0893.0
0362.5
0297.0
0542.5
0733.5
0259.0
0271.5
0524.0
0736.0
0073.0
0378.5
0993.0
1149.0
0705.0
0964.5
0531.5
0190.0
0204.0
0480.5
0382.0
0653.5
0616.0
0489.5
1034.5
1293.5
0464.0
0741.5
0387.5
0255.0
1134.0
0927.5
0670.5
0478.0
0449.5
0646.0
0248.0
0463.0
0386.0
0709.5
0865.0
0420.5
0837.0

154

08
12
04
17
03
O4
08
07
03
06
03
12
11
09
10
30
11
00
01
02
10
02
32
10
08
18
02
06
05
00
03
05
05
06
17
01
02
07
09
20
07
00
12
06
11
04
03
07
14
00

03
01
04
04
06
05
02
08
05
00
05
03
03
01
07
04
06
05
03
09
04
03
03
05
05
06
06
02
00
04
03
03
05
06
05
07
06
04
07
04
03
09
06
02
02
08
09
04
04
05

26
45
31
33
32
31
28
28
27
18
27
38
37.
31
42
37
31
33
24
22
25
35
39
33
33
35
36
34
36
38
37
26
38
30
24
34
37
42
36
29
31
12
37
25
37
32
3O
29
36
24

12
29

26
24

19
14
19
21
21
16
26
27

31

28
23
22
26

18
20
17
25

16
17

29

20
24

28
26
21
16
25
25
21
15
29

10

2.02
2.35
3.48
2.48
3.54
2.99
2.05
2.37
2.28
3.24
2.14
2.30
2.79
2.54
2.38
2.92
2.77
3.86
3.00
3.29
2.60
2.39
1.96
3.08
3.80
3.10
3.27
2.45
2.78
2.55
2.82
3.91
3.08
3.46
3.08
3.52
2.54
2.82
3.27
2.86
2.93
3.14
3.79
2.44
2.56
3.08
3.59
2.15
2.76
3.03

11

21
23
19
19
19
22
21
20
20
21
20
17
19
21
20
19
21
20
19
20
20
22
22
20
19
19
25
18
17
26
20
22
19
21
20
21
22
21
19
19
30
20
19
27
21
20
23
20
18
20

Cohmm

Sample 2
continued

1 2

HHNWWr—HwHer-wwwwmwwNNNNNNwNwHNr-vNwHHHwHNwWNHNr-HHNWL»

NF‘NNHHNHNHl-‘NNO-‘l-‘Ni-‘NHNO-‘l-‘HNNHHNHHHHHNNNHHNNHF‘HNHNHNNN

NN-beI-‘J‘HWHNJFNNJ‘Pr-‘br-‘NNJ‘J‘J‘J‘UJNHNNNNJ‘J‘NN“bbNWNbNWF-‘J‘Nbb

16
13
09
16
12
03
05
14
10
14
15
18
12
13
15
10
14
18
18
17
13
12
05
12
06
08
08
14
17
O6
15
17
16
07
15
17
17
13
15
16
16
15
17
18
16
09
17
07
15
12

0638.0
0786.5
0524.0
0500.5
0831.0
1122.0
0353.0
0244.5
0356.0
0254.0
0457.5
0267.0
1142.5
1171.0
0586.5
0504.5
0210.5
0660.0
0258.0
0116.0
0784.0
0348.5
0603.5
0186.0
0274.0
0559.5
0532.0
0423.0
0913.5
0354.0
0836.0
0290.0
0884.5
0503.5
0938.0
0677.0
1356.5
0526.5
0302.5
0758.0
0752.0
0254.5
0408.5
0602.0
0557.5
0653.0
1593.0
0449.5

155

08
04
08
06
04
11
05
11
21
12
05
09
01
08
08
09
28
09
14
25
03
14
01
19
16
13
16
05
05
13
17
02
06
07
04
09
08
01
08
12
02
13
11
09
06
06
03
00
05
16

08
04
05
05
04
03
01
04
05
07
03
08
05
03
03
04
00
07
09
00
04
02
03
03
07
08
01
04
03
02
04
07
03
00
04
04
05
04
05
06
04
03
01
06
06
04
04
08
06
05

34
32
37
22
42
39
31
29
27
23
36
28
38
21
23
22
28
31
33
17
34
32
34
45
30
26
23
25
37
36
28
36
33
36
30
29
32
24
36
35
32
19
34
22
33
33
34
35
31
35

19
25

25
23

21
17
25
24
24
30
28
26
22
23

25

19
20
20
19
27
29

19
20
19
22
21

27
25
25
23

17
25
29
25
24
26
28
28
20

10

2.15
2.92
3.47
3.00
2.23
2.55
2.44
3.14
2.29
2.32
3.22
3.62
2.79
2.12
2.65
2.86
3.30
2.58
2.45
2.54
2.73
2.93
2.62
2.80
3.14
3.62
2.87
3.82
2.90
3.11
3.32
2.45
3.20
3.39
2.83
2.82
3.44
3.72
3.52
2.81
3.00
2.60
2.44
3.35
3.36
2.73
3.59
3.33
3.02
3.61

11

20
20
20
22
22
22
21
19
20
21
18
21
21
21
21
21
33
22
21
23
18
19
18
21
22
19
20
19
20
19
26
27
21
21
22
21
21
19
20
21
21
20
22
21
21
21
21
20
21
21

Cohmm

Sample 2
continued

WNNNWWNP‘WNWHUNHHNWPNHHWUWPWPHWNNHNNNNNWL’JWHWHFNHNHH

HNNHNNNNHHHMF‘P‘NHHHNHHHNNNNNNNNHNNHHNHNHHHHNNHNF‘P‘NF‘

WNNNNNNwwv-I#Hkt-‘UJJ‘UJNv-‘HbHJ‘HwwaJ‘NbNNNJ‘4‘##NHNHJ‘HNNJ‘vL‘NJ‘

18
03
18
17
14
14
11
15
13
17
12
13
14
10
14
17
16
12
12
08
18
18
17
16
10
12
12
09
O7
18
14
16
17
16
14
10
07
09
12
09
15
16
11
07
17
18
18
12
14
15

0597.0
0803.0
0414.0
0440.0
0328.0
0462.0
1085.5
0389.5
1075.5
0683.5
0753.0
0898.0
0719.0
0479.0
0666.5
0626.5
0193.0
0781.0
0948.5
0607.0
0787.0
0337.0
0520.5
0512.5
0772.0
1078.5
0389.0
0363.5
0506.0
0541.5
0749.5
0386.0
0886.5
0567.0
0563.5
0425.5
1028.0
0319.5
0790.5
1348.0
0232.0
0455.5
0330.5
0873.0
0124.0
0126.0
1037.5
0284.5
0709.5

156

05
09
04
20
13
03
02
08
03
10
08
04
09
16
01
13
12
05
02
18
00
15
06
06
15
03
03
12
08
11
09
11
09
02
05
04
17
05
19
07
00
14
11
07
00
17
12
11
13
12

06
05
06
02
07
02
07
00
04
04
04
06
05
02
06
04
09
04
04
06
03
05
06
06
06
03
07
09
03
04
O4
03
06
02
05
03
03
02
05
02
04
06
06
02
05
10
06
07
06
03

41
42
35
4o
30
35
32
32
32
24
36
43
37
27
3o
33
38
31
24
31
24
37
28
25
37
37
27
35
31
27
35
36
28
28
3o
32
38
33
38
33
3o
22
3o
27
44
36
48
33
35
23

25
17

23
21
16
26
22
23
27
14
24
24

25

27
22
23
26
24
29
21
23
23
28
26
20

23
25
27

20
23

23
17
19
24
23
25
11

27‘

17
27
17
23
24

10

2.45
2.61
2.47
2.25
3.22
3.18
3.20
2.97
2.66
2.85
2.38
3.77
3.13
2.75
4.00
2.19
3.11
3.36
3.03
2.31
3.86
2.94
3.79
2.70
3.25
3.00
3.28
2.64
2.73
3.13
3.18
3.47
2.39
2.27
2.38
2.47
2.31
2.86
2.13
2.62
3.10
2.44
3.09
2.85
3.85
2.31
3.28
2.51
3.24
2.66

11

22
22
31
22
20
21
19
19
18
21
20
21
21
19
19
21
20
20
21
22
19
20
20
20
18
21
19
20
21
20
20
19
21
25
22
19
20
21
20
21
21
21
21
21
19
21
20
20
19
20

APPENDIX H

INTERCORRELATION BETHEEN THE FIVE COGNITIVE STYLE MEASURES

AND GRADE POINT AVERAGE HITH AND HITHOUT AMERICAN

COLLEGE TEST COMPOSITE SCORE IN SAMPLE 1 AND SAHPLE 2

157

158

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APPENDIX I

THE MATCHING FAMILIAR FIGURES TEST (MFF):

INSTRUCTIONS, SCORE SHEET, AND SAMPLE ITEMS

162

163

INSTRUCTIONS - MFF

E opens test booklet to first item so that S is looking at the
practice item with the standard at the top and the variants at the bot-
tom. The standard is nearly at a right angle to the variants.

E, pointing to the variants, then says, ”Only one of these is an
exact duplicate of this" (pointing next to the standard). "Your task is
to find that one. Tell me when you think you have found it. If you are
wrong, you keep looking until you have found it. If you are right, then
you go on to the next item, but please wait to turn the page until I
tell you. The first two are practice items. Ready? Go."

E answers any questions 8 may have while 3 solves the practice
items. E records latency to the first response for each item to the

nearest half-second and the responses 8 makes in order.

164

SCORE SHEET - MFF

 

 

 

 

NAME DATE
AGE SEX MAJOR
Time to first response Responses

a. boat (2)

 

b. cowboy (4)

 

 

 

 

 

1. dog (4)

 

2. rose (6)

 

 

3. soldier (2)

 

 

4. graph (7)

 

 

5. baby (4)

 

 

6. lamp (8)

 

 

7. dress (1)

 

 

8. lion (5)

 

 

9. glasses (7)

 

 

10. plane (4)

 

 

 

ll. leaf (2)

 

12. bed (5)

 

 

 

167

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX J

THE NESTCOTT INTUITION TEST (WIT):

INSTRUCTIONS, TEST VITH CLUES UNDEVELOPED,

TEST WITH CLUES DEVELOPED

168

169

INSTRUCTIONS SHORT FORM WIT B

Place the problem page in front of you and look at it closely. The page contains
twelve problems for you to solve with a space at the right to record the answers.

Each row of boxes is a problem and each problem is separate from the others.

In each box in a row there is progressive information about the problem and about what
answer is to go on the line at the right. To find the information in a box, brush across
the box with a single stroke of the developing pen. For each problem, the correct answer
is the 255 answer which would be right if all boxes were developed and all the information
were used.

The task is to solve each problem using as little information as possible.

The first two problems are for practice only, to familiarize you with the task, so
work through them as follows:

Problem 1. Note that the answer space for problem 1 is entirely blank (while the
answer space for problem 2 already is partly filled). Use your developing pen to develop
the first box in problem 1 and see what it says. If you have an idea what would go on the
answer sheet if you developed all the rest of the boxes, write it down. You probably don't
have any idea yet, so develop the next one. Now the information reads l-Z-blank-blank-blank

(answer).

If you develop the next box, you will find that the information then reads l-2-3-b1ank-
blank (answer). By now you may be willing to guess what is in the boxes that you haven't
developed, and you may be willing to write the one answer which would be correct if you went
ahead and did develop them.

As you deveIOp the rest of the boxes in the row, one by one in order, you find that
the information, when fully revealed, is 1-2-3-4-5 (answer), and the one correct answer
is 6. Thu might have been able to reach this conclusion after developing only one or two
boxes, but remember the right answer to this problem would be 6 no matter how-few boxes you
developed.

Remember, your task is to solve the problems correctly usigg as little information as
possible. When you develop boxes, you must develop them in order from left to right.

Problem 2. Note that the answer space already contains part of an answer. Develop the
first box, and see what it says. If you want to complete the answer, try it. If not,
develop the next box, and so on, until you find that the one correct answer is High/low.

In these first two problems, you probably developed most or all of the boxes, in order
to understand the nature of the two problems. In the next ten problems your aim is to
solve them correctly developing as few boxes as possible, in order from left to right.

Only 222 can decide how many boxes you need to develop and how certain you want to be
about your answers. Remember that there is 225 correct answer for each problem and it
must take account of all the information provided in all the boxes, whether you have
developed them or not.

The time limit for the task is fifteen minutes, and it is important that you attempt
a solution to each problem during that time.

Remember: develop the boxes in order from left to right, and try to solve each problem,

using as little information as possible. Ybur answer must take account of the information
you have seen as well as the information you have not seen.

 

 

 

 

 

 

 

 

 

 

 

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