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ABSTRACT

AN EXAMINATION OF THE RELATIONSHIP OF THE
EDUCATIONAL COGNITIVE STYLE AND DRIVING
BEHAVIOR OF SELECTED NOVICE DRIVERS AS

MEASURED BY THE DRIVER PERFORMANCE
MEASUREMENT PROCEDURE

BY

Paul G. Specht

.The purpose of this study was to examine the rela-
tionship of the educational cognitive style of novice
drivers and their driving behavior. To measure cognitive '
style the Educational Cognitive Style Interest Inventory
of Oakland Community College (Michigan) was used. The
Driver Performance Measurement Procedure (DPM), deve10ped
at Michigan State University, was employed to measure driv-
ing behavior.

The subjects for this study were high school driver
education graduates from the Lansing, Michigan area who
had less than three months licensed driving experience.
Fifty-six subjects, who had participated in an earlier
study in which DPM scores were produced, volunteered to
take the Educational Cognitive Style Interest Inventory.

Twenty-five of these subjects came from the fourth

Paul G. Specht
quartile of DPM scores and were labeled the "good"
drivers. The remaining thirty-one volunteers scored in
the first quartile of the DPM and were labeled the "poor"
drivers. The DPM measured the four variables of behavior
pattern, search, speed control and direction control. The
Educational Cognitive Style Interest Inventory measured
twenty cognitive traits which describe the way an indi-
vidual seeks meaning in his environment.

Two procedures were used to examine the relation-
ship of educational cognitive style and driving behavior.
The first was to compare the collective cognitive styles
of the highest scoring DPM group with the styles of the
lowest scoring DPM group. The second procedure was to
formulate regression models (equations) to determine what
cognitive style elements could be generated to predict
the driving behaviors measured by the DPM.

Collective cognitive style maps were produced
for both groups of drivers. Only one element, QCH (Qual-
itative Code Histrionic), appeared between the two that
was significantly different. The "good" drivers had a
major orientation in this element while the "poor" drivers
had a minor orientation. A Chi-square analysis was used
in this comparison and the results were significant at
the .10 level.

Through the use of a Stepwise regression pro—

cedure, a model was produced for all four dependent

Paul G. Specht

variables, i.e. pattern concept, search concept, speed

control, and direction control. This model, which can

be used to predict driving behavior, was significant at
the .10 level.

This model could be useful to driver education
teachers who take their students' predicted driving
behavior and develop individual instructional plans based
on the students' strengths and weaknesses.

The models generated by the Stepwise regression
procedure cannot be guaranteed to represent real world
situations accurately. However, they do indicate elements

of cognitive style which should be investigated further.

AN EXAMINATION OF THE RELATIONSHIP OF THE
EDUCATIONAL COGNITIVE STYLE AND DRIVING
BEHAVIOR OF SELECTED NOVICE DRIVERS AS

MEASURED BY THE DRIVER PERFORMANCE

MEASUREMENT PROCEDURE

BY

Paul G. Specht

A DISSERTATION

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

DOCTOR OF PHILOSOPHY

Department of Secondary Education
and Curriculum

1978

DEDICATION

To the late Dr. Joseph E. Hill, teacher and
educational scientist, who provided the

foundation for this study.

11

ACKNOWLEDGMENTS

The writer wishes to take this opportunity to
thank the many peOple who have helped in the completion
of this study.

Special appreciation is extended to Dr. Donald L.
Smith, his chairman, for many hours of guidance and
assistance which were provided.

Appreciation is also extended to the other members
of his committee, Dr. Peggy Riethmiller, Dr. Joseph
Dzenowagis, and Dr. Robert O. Nolan, for their time and
assistance.

A special note of thanks is extended to Dr. Willard
North and Dr. Robert Ulrich of Central Missouri State
University, and Mr. Martin Dolan of East Lansing High
School.

Most especially, thanks is offered to his wife,
Carol, who willingly followed and encouraged him in the

pursuit of dreams.

iii

TABLE OF CONTENTS

LIST OF TABLES . . . . . . . . . . . .
LIST OF APPENDICES . . . . . . . . . . .
Chapter

I. THE PROBLEM . . . . . . . . . . .

II.

III 0

IV.

Statement of the Problem . . . . . .
Background of Study . . . . . . . .
Purpose of the Study . . . . . . .

Significance of the Study . . . . .
General Questions to be Answered . . .
Basic Assumptions . . . . . . . .

Definition of Terms . . . . . . . .
Summary . . . . . . . . . . . .

REVIEW OF LITERATURE . . . . . . . .

Driving Behavior . . . . . . . . .
Cognitive Style . . . . . . . . .
The Educational Sciences . . . . . .
Current Cognitive Style Research . . .
Summary . . . . . . . . . . . .

DESIGN AND PROCEDURES OF THE STUDY . . .

Source of Data . . . . . . . . .
Sample Employed . . . . . . . .
Methods and Conditions of Data Collection
Design of the Study . . . . . . . .
Instrumentalities of Data Collection . .
Summary . . . . . . . . . . . .

ANALYSIS OF DATA . . . . . . . . .

Collective Cognitive Style Profiles . .
The Stepwise Regression Procedure . . .
smary O O Q 0 O O Q I O O O 0

iv

Page
vi

vii

Chapter Page

V. SUMMARY, CONCLUSIONS, DISCUSSION, AND

RECODH‘IBIJDATIONS . o o o o o o o o 6 7
Summary . . . . . . . . . . . . 67
Conclusions . . . . . . . . . . 71
Discussion . . . . . . . . . . . 72
Recommendations . . . . . . . . . 79
REFERENCES . . . . . . . . . . . . . . 80
APPENDICES . . . . . . . . . . . . . . 87

Table

1.

LIST OF TABLES

Sample Rating Sheet . . . . . . . .

Sample Cognitive Style Inventory Questions
and Elements Measured . . . . . .

Collective Educational Cognitive Style Map
of Students in Highest DPM Scoring Group

Collective Cognitive Style Profiles . .

Collective Educational Cognitive Style Map
of Students in Lowest DPM Scoring Group

Significance Levels of Regression Models for

Predicting Pattern Concept Scores at the
.10 Level of Significance . . . . .

Significance Levels of Regression Models for

Predicting Search Behavior Scores at the
.10 Level of Significance . . . . .

. Significance Levels of Regression Models for

Predicting Speed Control Scores at the
.10 Level of Significance . . . . .

Significance Levels of Regression Models for
Predicting Direction Control Scores at the

.10 Level of Significance . . . . .

vi

Page

42

45

51

54

56

59

62

63

65

Appendix

A. The Educational Sciences . . . .

B. Twelve Cognitive Style Models . .

C. Educational Cognitive Style Interest
Inventory . . . . . . . .

D. Sample Computer Printed Cognitive Style
Maps 0 I O O O O O O O I

E. Dissertations Directly Related to the
Educational Sciences . . . . .

F. Driver Performance Measurement Recording
Form . . . . . . . . . .

G. The Stepwise Procedure . . . . .

H. Maximum R Square Improvement Study Data

1. Cognitive Map Instrument Developed by
Dr. Joseph Bosco . . . . . .

J. Letter from C. Bruce Martin, Director of

LIST OF APPENDICES

Academic and Management Information
Systems, Oakland Community College

vii

Page

88

100

106

119

122

131
137
144

152

160

CHAPTER I

THE PROBLEM

Statement of the Problem

 

The central problem of this study was to examine

the relationship of the educational cognitive styles of

 

novice drivers as determined by the Educational Cognitive

Style Interest Inventory and their driving behavior as

 

measured by Michigan State University's Driver Performance
Measurement Procedure. In general terms, this study
attempted to determine if a person's learning style

influences his driving style.

Background of Study

 

The knowledge and skill necessary to pr0perly
perform the driving task requires that the vehicle
Operator constantly evaluate and reevaluate his environ-
ment and make adjustments to changing traffic and
environmental conditions. The driver is, essentially,
reading the environment to interpret its significance.
This reading of the traffic environment is performed by
searching for those factors outside the vehicle which

can affect the driving task. The ability to read the

traffic environment must be used in combination with the
psychomotor skills necessary to control Speed and direc—
tion while maneuvering a car in the highway transportation
system.

According to Michigan State University's Driver
Performance Measurement (DPM) procedure, the factors of
speed control, direction control and search behavior,
together with the relative timing of these components,
determine the suitability of a person's driving pattern
(Forbes, 1973:47). Because the driving task is dynamic,
due to changing traffic and environmental conditions,
driver behavior patterns must be constantly changing to
adjust to the traffic environment.

These behaviors can be taught but are not neces-
sarily learned equally well by all drivers. This is
because individuals have different learning styles,
cognitive and psychomotor abilities, and preferred ways
of processing information about their environment.

These differences are known as a person's cognitive
style. Kagan, Moss, and Sigel (1963) have defined
cognitive style as "stable individual preferences in

the mode of perceptual organization and conceptual
categorization of the external environment." By applying
this process to how a person learns to drive, it is

possible that a relationship exists between how a novice

driver seeks meaning in the traffic environment and his
educational cognitive style.
A system for identifying educational cognitive
style has grown out of a body of work undertaken by
Dr. Joseph E. Hill and Dr. Derek N. Nunney (197l) which
has come to be known as the "Educational Sciences."
The Educational Sciences provide a conceptual frame-
work and scientific language for the applied field
of knowledge called education. These "sciences"
approach a level of precision that is found in such
other derivative fields as medicine, pharmacy,
engineering and law (Hill, 1976:2).
There are currently seven educational sciences:
(1) symbols and their meaning; (2) cultural determinants;
(3) modalities of inference; (4) memory; (5) teaching,
administrative, student, and counseling styles; (6)
cognitive style; and (7) systemic analysis decision-
making. All seven of these sciences have approached
a high level of precision and "are designed to explain
phenomena and solve problems in the practical aspects
of the human situation" (Hill, 1971:2).
The educational science of cognitive style was
of particular interest in this study because it was
used to identify the learning styles of beginning

drivers. Educational cognitive style is actually the

*
Cartesian product of three sets of sciences, i.e.,

 

* .
A mathematical equation developed by Rene

Descartes which graphically displays an ordered list

of three concepts or sets that are interrelated. In

symbolic mediation, cultural determinants, and modalities
of inference (C.F. Definition of Terms). The product of
these sets provides a graphical illustration, called a
map, of the strengths, skills, or cognitive traits a
person relies on in seeking meaning in his environment.

The first set of the Cartesian product, symbolic
mediation, indicates preferences in learning such as'
listening or reading, and preferences in expressing one's
self, such as speaking or writing. These preferences
are known as theoretical symbols. Qualitative symbols
are also included in this set. These symbols indicate
dependency on different senses and social sensitivity
such as empathy or ethics.

The second set, cultural determinants, provides
an insight into whg influences a person's acquisition
of knowledge and meanings i.e., family/authority figures,
associates and self.

The third set, modalities of inference, explores
a person's method of drawing conclusions about the
information he takes in. Included under this heading
are different methods of reasoning such as inductive,
deductive, categorical, comparative, and analytical

reasoning.

 

the.case of educational cognitive style, the sum of
these three sets equals an individual's cognitive style.

How frequently an element in each set is used and
the importance an individual attaches to it will deter-
mine if this element shows up on a person's map as a
major, minor, or negligible strength in learning. An
individual's educational cognitive style depends on the
combination and strength of the elements which he relies
upon.

Since driving behavior can be rated and cognitive
styles can be identified, it is of interest to driver
educators to discover ifthose novice drivers who have
a certain cognitive style are more competent at handling
dynamic driving situations than those who have another
particular cognitive style. If it is possible for
teachers to identify, before hand, the strengths and
weaknesses in students' cognitive styles which are
correlated with driving behavior, there is a possibility
that the teacher could make adjustments when planning
the driver education curriculum and thereby improve the
students' learning of specific driving behaviors. Such
a procedure could also save students time in learning
driving tasks. This efficient use of time for students,
and teachers as well, could be translated into financial
savings for school districts through a more efficient
'system of teaching beginning drivers; but more importantly,

a better job of instruction and learning will result.

Purpose of the Study

 

All three of the educational sciences which are
combined in educational cognitive style, i.e., symbolic
mediation, cultural determinants, and modalities of
inference, could have an influence on driving behavior.
However, the extent of this influence, if any, is
presently unknown. The purpose of this study was to
map the educational cognitive styles of a selected
group of subjects. Elements from these maps were
correlated with satisfactory or unsatisfactory behaviors
associated with the driving task using the DPM as the
criterion variable.

Before predictions can be made concerning the
use of cognitive style mapping, it is necessary to first
identify those factors related to behaviors which can be
observed and rated. Rating of driving behavior can be
accomplished through the use of the DPM. This procedure
was deveIOped by the Department of Psychology and the
Highway Traffic Safety Center at Michigan State University
in an effort to obtain a reliable measure of dynamic
driving performance in real world situations.

The method developed is unique in that it measures
dynamic driving behavior patterns in actual traffic,
uses simultaneous ratings by two observers to allow
evaluation of the measurements and makes possible
measurement of driving performance immediately and

at intervals after the subjects' completion of driver
education (Forbes, 1973:1).

Driver Performance Measurement scores for 288
novice drivers, i.e., high school driver education
graduates with less than one year driving experience,
were available as a result of a research project con-
ducted in the Fall of 1976 by the Highway Traffic Safety
Center. This study mapped the educational cognitive
styles of a selected group of participants in that
project.

Educational cognitive styles maps can be produced
from a subject's responses to a 224 item interest inven-
tory developed by Dr. Joseph Hill of Oakland Community
College. Through the use of a computer system, 20
factors can be identified to provide a picture of the
ways a person acquires meaning in his environment.

If a relationship exists between any of the 20
cognitive style elements and driving behavior, it should
be revealed by comparing the collective cognitive styles
of the subjects who rank in the 25th percentile of the
DPM (the better drivers) and those who rank in the 75th
percentile on this procedure which was conducted in the
Fall of 1976. Also, a regression model (equation) was
formulated to determine what cognitive style variables
can predict the driving behaviors measured by the DPM.
However, with both of these procedures, generalizations

cannot be made beyond the specific groups in this study.

Significance of the Study

 

The main significance of this study lies in its
potential as a tool for high school driver education
teachers. Most driver education courses are planned
and scheduled long before the students arrive. Indi-
vidual differences and needs of the students are dif-
ficult to meet in this type of system. However, as
each student learns in his own unique way, certain
phases of a driver education curriculum could present
information to a student in a manner which he finds
difficult to assimilate.

If certain elements of a person's educational
cognitive style can be shown to be related to certain
elements of driving performance, this information could
be used to determine individual student needs in order
to overcome deficiencies through adjustments in the
driver education curriculum. For example, if a relation-
ship exists between a driver's search behavior and his
ability to perceive meaning through the senses (called
Qualitative symbols in the Educational Sciences developed
by Dr. Hill), a student found to be weak or have negli-
gible strength on this element may require extra instruc-
tion in perceptual skills. Before a hypothesis of this
type can be made, it is first necessary to analyze the

relationship of educational cognitive style and driving

behavior. At this time, speculations beyond the original
statement of the problem can only be recommended for

another study.

General Questions to be Answered

 

This study attempted to answer the following
questions:

1. What elements of the collective educational
cognitive styles were common to the group which scored
in the first quartile of the DPM?

2. What elements of the collective educational
cognitive styles were common to the group which scored
in the fourth quartile of the DPM?

3. What elements of a person's educational
cognitive style were correlated at a minimum significance
level of .10 with the "Pattern Concept" score of the DPM
as evidenced by the regression model?

4. What elements of a person's educational
cognitive style were correlated at a minimum level of
significance of .10 with the "Search Behavior" score on
the DPM as evidenced by the regression model?

5. What elements of a person's educational
cognitive style were correlated at a minimum significance
level of .10 with the "Speed Control" score on the DPM

as evidenced by the regresSion model?

10

6. What elements of a person's educational
cognitive style were correlated at a minimum significance
level of .10 with the "Direction Control" score on the

DPM as evidenced by the regression model?

Basic Assumptions

 

In this study the following assumptions were made:

1. The validity and reliability of the Driver
Performance Measurement Procedure are sufficient for
the purposes of this study.

2. The validity and reliability of the Educational
Cognitive Style Interest Inventory developed by Oakland
Community College and used in this study are sufficient
for the purposes of this study.

3. The educational cognitive styles of the
subjects have not changed appreciably since taking the
Driver Performance Measurement.

4. Expressed opinions are held Opinions.

5. Satisfactory driving behaviors can be taught.

Definition of Terms

 

To clarify terms used in this study, the following
definitions have been presented:

Cartesian Product.--A mathematical equation

 

developed by Rene Descartes which graphically displays

an ordered list of three concepts or sets that are

11

interrelated. In the case of educational cognitive
style, the sum of these three sets equals an individual's
cognitive style.

Cognitive Style.-—The way in which an individual

 

seeks and acquires meaning in his environment.

Collective Coqnitive Style.—-Elements of an indi-

 

vidual's cognitive style which are unique to a specific
group, e.g. the cognitive style of all those within the
group identified as good drivers.

Cognitive Style Map.--A computer print-out or

 

hand drawn graph giving a pictorial display of cognitive
traits which describe the way in which an individual
acquires meaning from his environment. As many as 28
traits may be identified in forming a map.

Cultural Determinants.--One of the educational

 

sciences which explains the influences affecting the way
an individual derives meaning from symbols as modified
by individuality, associates and family.

Associates Determinant (A).--The influences

exerted by associates on an individual in his or her
understanding of symbols and their meanings.

 

Family Determinant (F).--The influences
brought to bear by immediate family or authority figures
on an individual's understanding of symbols and their
meaning.

 

Individual Determinant (I).--The influences
brought to bear by the individual on the meaning of
symbols. '

 

12

Driver Performance Measurement.--A procedure

 

referred to as the DPM used to measure dynamic driving
behaviors under actual traffic conditions. It includes
measurement of search behavior, speed control, and
direction control with regard to relative timing in
relation to the changing traffic and environmental
conditions.

Direction Control.--A term used in the DPM
to identify steering control or tracking of the vehicle.
The coordination of steering and turning maneuvers

with regard to proper timing in relation to changing
traffic and environmental conditions.

 

Search Behavior.--A term used in the DPM to
describe an observable behavior in which the driver
looks systematically toward possible sources of traffic
information. It includes the coordination of searching
with regard to proper timing in relation to changing
traffic and environmental conditions.

 

Speed Control.--A DPM term used to describe
the use of the accelerator or brake to fit the traffic
and driving task requirements while coordinating the
timing of this behavior.

 

Pattern Concept.--A term associated with the
DPM used to describe a series or sequence of observable
driving behaviors (i.e., search, speed and direction
control), that often occur together in the same order
or in different orders in relation to the timing required
by changing traffic and environmental conditions.

 

Dynamic Situation.--The driving situation created

 

by the many and varied components of changing traffic
and environmental conditions.

Educational Sciences.--A conceptual framework and

 

scientific language for the field of human activity

called education. (Definitions associated with this

13

concept were taken from their original source, The

Educational Sciences, which can be found in Appendix A.)

 

Modalities of Inference.--One of the Educational

 

Sciences which explores a person's method of drawing

conclusions about the information he or she takes in.

This includes the following forms of inference: Magnitude,

Difference, Relationship, Appraisal and Deductive.
Magnitude (M).-—A form of categorical reason-

ing that utilizes norms or categorical classifications

as the basis for accepting or rejecting an advanced
hypothesis.

 

Difference (D).--This element suggests a
tendency to reason in terms of one-to-one contrasts or
comparisons of selected characteristics of measurements.

 

Relationship (R).--This modality indicates
the ability to synthesize a number of dimensions or
incidents into a unified meaning, or through analysis
of a situation to discover its component parts.

 

Appraisal (L).--The modality of inference
employed by an individual who uses all three of the
modalities noted above (M, D, and R), giving equal
weight to each in his reasoning process.

 

Deductive (K).--This modality indicates
deductive reasoning or the form of logical proof used
in geometry or that employed in syllogistic reasoning.

 

Orientation/Strength in Learning.--How frequently

 

a symbol is used and the importance an individual
attaches to it will determine if the symbol shows up
on a cognitive style map as a major, minor, or negli-
'gible strength in learning.

Major Orientation.--This is given to a
particular element if it occurs in the 50th- 99th per-

centile range of a distribution. It usually indicates
above average ability in an element.

 

14

Minor Orientation.--This indicates average
ability in a particular element that occurred in the
26th-49th percentile range. It is displayed on a
cognitive style map as a "prime" connected to a symbol.
For example, the symbol T'AL would indicate a minor
orientation in that element.

 

Negligible Orientation.--This is given to an
element if It occurs in the 25th percentile or below of
a distribution of scores. Elements of negligible
strength do not appear on an individual' 5 cognitive
style map.

 

Qualitative Cultural Symbols.--Part of the edu-

 

cational sciences associated with symbols which are
derived from ten cultural codes created and used by
individuals to acquire knowledge and gain meaning from
their environments and personal experiences.
Qualitative Code Empathic (QCEM).--The

capacity to derive meaning through sensitivity to the
feelings of others.

 

Qualitative Code Esthetic (QCES).--The
capacity to derive meaning through the enjoyment of
the beauty of an object or an idea.

 

Qualitative Code Ethic (QCET). --The ability
to derive meaning through commitment to a set of values,
a group of principles, obligations, and/or duties.

 

Qualitative Code Histrionic (QCH). --Capacity
to exhibit a deliberate behavior, or play a role to
produce some particular effect on other persons. This
type of person knows how to fulfill role expectations.

 

Qualitative Code Kinesics (QCK).--The capacity
to understand, and to communicate by non-linguistic
functions such as facial expressions and motions of
the body.

 

Qualitative Code Kinesthetic (QCKH).--The
capacity to perform motor skills, or effect muscular
coordination according to a recommended, or acceptable
form.

 

15

Qualitative Code Proxemics (QCP).--The
capacity to judge physical and social distance that
the other person would permit, between oneself and
that other person.

 

Qualitative Code Transactional (QCT).--The
capacity to maintain a positive communicative Inter-
action which significantly influences the goals of
the persons involved in that interaction.

 

Theoretical Symbols.--Part of the educational

 

sciences denoting a set of four symbols which present
to the nervous system, and then represent to it, some-
thing different from that which they themselves are.
For example, spoken or written words can represent
objects which are different from the symbol itself.
Theoretical Visual Linguistics (TVL).--The
ability to take in meaning from words you see. A major

in this area indicates someone who reads with a better
than average degree of speed and comprehension.

 

Theoretical Auditory Linguistics (TAL).--The
ability to acquire meaning through hearing spoken words.

 

Theoretical Visual Quantitative (TVQ).--The
ability to acquIEe meaninggin terms of numerical symbols,
relationships, and measurements.

 

Theoretical Auditory Quantitative (TAQ).--The
ability to find meaning in terms of numerical symbols,
relationships, and measurements that are spoken.

Summary

It was shown in this chapter that both cognitive
styles and driving behaviors can be identified. A need
exists to determine if a significant relationship between
the two can be established. If elements of a person's

educational cognitive style can be shown to influence

16

elements of driving performance, this information could
be used to predict driving behavior and identify stu-
dent deficiencies. To accomplish this, it is necessary
to first examine the relationship of the cognitive
styles of novice drivers and their driving behavior.
This relationship has not yet been examined;
however, literature related to both educational cogni-
tive style and driving performance measurement will be

reviewed in the following chapter.

CHAPTER II

REVIEW OF LITERATURE

Educational cognitive style investigations are a
relatively new area of interest among educators. Most of
the studies which are applicable to academic situations
have been conducted within the past ten years. Cognitive
style inventories have been used to predict performance
in disciplines such as mathematics, language arts and.
vocational education. However, no studies have been
found which involve cognitive style and driving behavior.
Many of the studies on the prediction of driving behavior
have been based on accident records or limited observa-
tion techniques. With this in mind, the review of
literature in this chapter will include the following
topics: (1) Driving Behavior; (2) Cognitive Style;

(3) The Educational Sciences; and (4) Current Cognitive

Style Research.

Drivinngehavior

 

Any study which attempts to measure driving
behavior should first identify those behaviors which
comprise the task of driving. In a study by Fine,

Malfetti and Shoben (1965) 1,057 traffic safety experts

17

18

were surveyed in an effort to develop a list of driving
behaviors. The results included over 3,000 observable
behaviors. This information was used to classify drivers
as either "good" or "bad" in their operation of a motor
vehicle.

The Human Resources Research Organization
(HumRRO) developed a similar method to analyze and
evaluate critical driving behaviors (McKnight, et al.,
1970). Each aspect of the highway transportation system,
i.e., driver, vehicle, roadway, traffic and natural
environment, was examined. Over 1500 behaviors were
identified, and then presented to a group of 100 traffic
safety professionals who evaluated the behaviors for
driving criticality. Out of this study came a comprehen-
sive list of driving task descriptions.

Both of the studies presented above have empha-
sized that the driving task involves numerous behaviors
that are often used in combination with one another.

The measurement and identification of driving
behavior through different systems of observation has
been the objective of many researchers over the years,
with varying levels of success. An international
research group, the Organization for Economic Co-operation
and Development (1970:18) has identified four forms which
have been used to observe items of driving behavior. They

include the following:

19

l. remote observations from outside the vehicle;
2. measurement by electro-mechanical means;

3. recording of psycho-physiological processes;
4. multiple in-car observer techniques.

A study by Billion (1957), which compared person-
ality factors and driving behavior, used remote observa-
tions of driving behavior by following drivers who did
not know they were being observed. They were rated on
speed, following distances, conduct at traffic control
devices and passing. However, the test results were
insignificant when compared with the measured personality
factors.

In a similar study, Edwards and Hahn (1964)
followed drivers (without their knowledge) and recorded
behaviors on five minutes of motion picture film. The
drivers averaged over nine errors each, with speeding
being the most frequent error. When a comparison of
measured driving behaviors was made with participants'
accident records to predict future accident potential,
no significant difference was found.

When observations were made from stationary posi-
tions outside the vehicle, the studies were hampered by
either simulated traffic situations (Crawford, 1963) or
tended to dwell on only one or two variables (OECD,

1970:30).

20

A number of studies (Greenshields, 1963; Safrin,
1970; and McLean, 1972) have used vehicles equipped with
electro-mechanical devices to measure and record driving
behavior. The results of these studies were based on
three primary control movements, i.e., steering, acceler-
ation and braking. The frequency and magnitude of these
movements have been used to describe a level of skill
involved with a particular driving task. Difficulties
with this method existed due to changes in traffic and
environmental conditions which created problems in the
assessment of the results.

Most investigations in psycho-physiological test-
ing have measured heartbeat, galvanic skin response, or
pulse rate under varying levels of stress. An exception
to this was a study of eye movement by Thomas (1968).
This investigation found that the eyes of an average
driver systematically perform patterns of observation.
Both voluntary and involuntary movements were noted as
drivers focused on visual attractions, such as vehicle
position in relation to the road and other vehicles.

The information presented in this study was of value in
the identification of driver search patterns.

In-car observation techniques have been used
most extensively by driver licensing agencies. A manual
designed to establish criteria for road testing has been

published by Northwestern University (Baker, et al.,

21

1960). It includes a checklist for measuring 67 driving
behaviors.

Testing instruments from over 40 driver licensing
agencies were reviewed in a study by McGlade (1960).
From the results of this investigation, McGlade produced
a checklist which could be used to rate singular,
isolated behaviors.

Outside the realm of driver licensing, Quenault
and Parker (1973) used a method of systematic observa-
tion of driver behavior to compare newly qualified drivers
with a random sample of drivers. Two obserVers in the
subjects' vehicles rated 15 remotely related driving
behaviors. The results indicated that fewer of the newly
qualified drivers were assessed as safe drivers. In
this study, all the new drivers were administered a
personality test and an intelligence test. The subjects
were matched according to sex and age. However, mean
scores were used for the groups rather than individual
scores. The results indicated no significant difference
between the groups with regard to the personality and
intelligence test scores.

The disappointing results of studies in the
measurement of driver behavior can be attributed to two
factors, i.e., (1) the use of inadequate observation and

rating techniques, and (2) the use of accident records

22

as a criterion for evaluation. According to Forbes
(1974:3) observation and rating techniques need to
employ a systems measurement approach which he said

should include the following list:

Observing, measuring and analyzing different styles
of behavior in response to complex practical
situations. Measuring noncognitive behavior as
well as cognitive. Taking account of alternate
possible response patterns . . .

All these factors need to be present for a system of
measuring driving behavior to be a valid indicator of
"real world" driving ability.

The use of accident records as a criterion for.
evaluating driver behavior was found to be unreliable
by an international research organization. In a report
by the Organization for Economic Co-operation and
Development (1970:40), the authors emphasized the
inadequacy of accident records when they stated:

Numerous studies have shown that this criterion has
little applicability to the evaluation of driving
behavior. This is mainly due to insufficient
reliability, or repeatability over relatively

short time intervals when applied to an unselected
population of drivers.

Forbes (1974:2) supported these findings when he
stated that:

Accident records involve many unknown factors such
as incomplete data, differences in conditions,
reporting, coding and the like. Public accident
records, even when most complete in the best
systems, require three years or more to attain
stability. On the whole, research on factors in

safe driving using an accident record criterion
have been disappointing.

23

Despite this evidence against the use of accident
records, research projects are still being conducted
which will use these records as the criterion for mea-
suring driving behavior (HumRRO, 1973).

A procedure for the measurement of driver per—
formance has been developed which was designed to avoid
the problems mentioned above. The Driver Performance
Measurement procedure, which is of prime importance in
this study, was develOped by the Highway Traffic Safety
Center and Department of Psychology at Michigan State
University. This procedure covered over 90 percent of
the applicable "critical" or "very critical" driving

behaviors identified in the Driver Task Analysis

 

(Forbes, 1972:29). The Driver Performance Measurement
procedure (DPM) was intended to provide a reliable
criterion to be used in place of accident records.
Trained raters made observations concerning the suita-
bility of driving patterns in relation to traffic and
environmental conditions.
In describing the DPM procedure Forbes (1973:4)

stated:

This research develOped an in-car driver perform-

ance measurement technique which is quite different

from the ordinary road test or the usual checklist

approach. The procedure involves observation and

rating by specially trained observers, of actual

driver behavior patterns in relation to the changing

traffic situations in carefully selected and described
locations and traffic conditions.

24

For measuring driving behavior, Forbes (l973:5) pointed
out that the DPM is a highly reliable and valid system.
Unlike many of the earlier studies on driving behavior,
the DPM was designed to be used in "real world" traffic
situations while measuring a large number of interrelated
tasks. Vanosdall (1977:16) described the superiority of
the DPM as a measure of driving behavior when he gave
the following description:

Emphasis was placed on both situational factors and

patterns of behavior, including timing. Painstaking

descriptions of the many behavior patterns and how

they increased or decreased hazard potential were

prepared. The psychological functions required

for "suitable" behaviors (behaviors that decreased

or did not increase hazard) were determined for
each location [where observations were noted].

 

Vanosdall (1977:19) further expressed his support of the
DPM when he said, “The evidence indicates that there is
a general factor of safe driving, and that the DPM method

provides a valid and reliable measure of this factor."

Cognitive Style

 

Early work in the area of cognitive style was
promoted when psychologists such as G. W. Allport and
P. E. Vernon (1933) conducted studies on personality and
motivation. Allport (1937:494) held that in the perform-
ance of various activities, individuals demonstrate a
pattern of behaviors which he called "style."

With the advent of World War II, interest in the

measurement and identification of individuals' cognitive

25

styles increased greatly (Bosco, 1978). This was due to
the fact that military leaders were in need of instru-
ments which could help identify strengths and weaknesses
of personnel who were called on to serve in the armed
forces before they were assigned specific duties.

In spite of all the interest in this area, prob—
lems existed in the definition of cognitive style and
the identification of what needed to be measured. Even
as late as the 1960's, Herman A. Witkin (1962:80), a
noted researcher in cognitive style, commented on the
lack of unity in this field. He stated:

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.

Definitions of cognitive style have ranged from

the very simple to complex. In a recent monograph

entitled the State of the Art of Cognitive Style Research

 

(1978), Dr. Witkin called it "self-consistencies which
people show." In the same article, Dr. Samuel Messick
of the Educational Testing Service at Princeton, N.J.
defined cognitive styles as "self-consistent modes of
thinking or mental functions."

Dr. Joseph Bosco (1978), a researcher in cognitive
style from the State University of New York at Albany,

defined cognitive style by first stating what it is not.

26

He said that cognitive style is not cognitive ability
like I.Q., which has a value. It is the way a person
prefers to learn.

While these are rather simplistic explanations of
a complex concept, they serve as a starting point upon
which more advanced definitions can be built.

Broverman (1960:240) expanded commonly held
definitions of cognitive style by including variations
in the performance of conceptual and perceptual motor
tasks. The importance of sensory modalities should also
be included when measuring a person's cognitive style.
The senses play a vital role in the processing of infor-
mation (State of the Art, 1978:13).

The complexity of the situation was summed up by
Blanton (1971:277) who commented about several of the
leading researchers in cognitive style:

Witkin speaks of field independent and field depend—
ent cognitive styles. Broverman speaks in terms of
conceptual versus perceptual dominance. Gardner
describes cognitive control patterns such as
leveling and sharpening . . . [and] Kagan, Moss

and Sigel speak of three cognitive styles.

There appears to be a great deal of confusion
when it comes to defining and explaining cognitive style.
However, in conducting an overview of the field, there

are basically twelve prominent models which identify

different aspects of a person's cognitive style, and

27

numerous instruments to measure these models. A list

of all twelve models, along with definitions, principal
researchers and some measuring instruments, is contained
in Appendix B.

By synthesizing concepts related to the twelve
cognitive style models, Hill and Nunney (1971:10-15)
developed a new framework for measuring cognitive styles
called the "Educational Sciences." Students' cognitive
styles were measured (mapped) through the use of a
battery of six tests which comprise part of the "Edu-
cational Sciences." They saw the need for a practical
testing instrument which would be the basis of indi-
vidualized instructional programs. Fortunately, as
college administrators, they were in a position to take
their ideas a step further and apply them to an actual
community college situation (Manilla, 1971).

Researchers Coop and Sigel (1971:160) lent
support to the methods used by Hill and Nunney when they
proposed that a ”number of existing measures of cognitive
style may prove to provide more sensitive data for edu-
cators as a basis for truly individualized instructional
programs." They also suggested the construction of
style profiles of individual students. Efforts in this
direction resulted in the success of the "Educational

Sciences."

28

The Educational Sciences

 

A system for identifying educational cognitive
styles has grown out of a body of work studied by Dr.
Joseph E. Hill which has come to be known as the "Edu-
cational Sciences." The term "educational sciences"
was first used by Dr. James B. Conant (1960:120) to
denote a conceptual framework describing education, not
as a single science, but as a composite of several
precise sciences. He stated:

I prefer not to speak of the science of engineering
but of the engineering sciences. I doubt that
there is or ever will be a science of medicine,

yet I am sure enormous strides have been made

in the medical sciences . . . It would be better
[to call them] the educational sciences or
educational discipline rather than the science

or discipline of education.

Hill (l97l:2) identified seven educational
sciences which include the following: (1) symbols and
their meaning; (2) cultural determinants; (3) modalities
of inference; (4) cognitive styles of individuals;

(5) electrophysiology and bio-chemistry of memory function;
(6) teaching, administrative, counseling, and student
style; and (7) systemic analysis decision-making. All
seven of these sciences have approached a high level of
precision in explaining educational problems. According
to DeLoach (1969:5), this high level of precision was

attained because the educational sciences were successful

in establishing four necessary conditions, i.e., the

29

clarification of purposes, consistency in the interpre-
tation of issues and information, increased reliability
and validity of generalizations and predictions of
associated data, and the establishment of universal
terminology.

According to Hill (1971:3), "Cognitive styles
are determined by the way individuals take note of their
surroundings-~how they seek meaning, how they become
informed." To properly measure an individual's cognitive
style, Hill developed an instrument combining the first
three sciences of the "Educational Sciences," which
includes symbols and their meanings, cultural deter-
minants, and modalities of inference. This instrument,
The Cognitive Style Mapping Interest Inventory (see
Appendix C), contains 224 items which measure as many as
28 factors to provide a picture of the methods by which
a person acquires meaning in his environment. Each
individual's cognitive style is displayed in the form
of a Cartesian product (see Definition of Terms) of the
three sets of sciences mentioned above.

The first set of the Cartesian product, symbolic
mediation, indicates preferences in learning such as
listening or reading, and preferences in expressing one's
self, such as speaking or writing. These preferences

are known as theoretical symbols. Qualitative symbols

30

are also included in the first set and indicate depend-
ency on different senses and social sensitivity.

The second set, cultural determinants, provides
an insight into who influences a person's acquisition
of knowledge and meanings, i.e., family and/or authority
figures, associates, and self.

The third set, modalities of inference, explores
a person's method of drawing conclusions about the infor—
mation he takes in. Included under this heading are
different methods of reasoning such as inductive,
deductive, categorical, comparative, and analytical
reasoning.

Because these three sets are so closely inter-
related, with regard to an individual's cognitive style,
they are presented in the form of a Cartesian product

as the following model demonstrates.

s E 2!.
Cognitive T I M L
Style I Q x A x D (K)

F R

The letter S represents the first set called symbolic
mediation; T refers to theoretical symbols; Q indicates

qualitative symbols. E represents the second set which

31

is the science of cultural determinants; I indicates the
influence of "individuality" on symbolic mediation;

A denotes the influence of "associates"; and F stands
for "family" influence. The set of modalities of infer-
ence is denoted by H, under which M, L, D, R, and (K)
indicate methods of reasoning. When referring to a
particular profile of an individual in this form of-a
Cartesian product, it is usually called a map. An
example of an actual computer print-out of a cognitive
style map can be found in Appendix D.

Through the use of these maps, Hill (l97l:9)
foresaw the possibility of personalizing education. He
stated:

Mapping an individual's cognitive style enables the
educator to consider the individual in terms that
without the map he or she might not have employed.
The diagnosis of an individual's cognitive style
and the modes of understanding required by an edu-
cational task can be used to match the student to
the task. Through this approach it is possible to
prescribe educational activities that provide a
better probability of successful accomplishment by
the individual than otherwise might be possible.
Current Cognitive Style Research

Research completed at Oakland Community College,
combined with information gained from over eighty
doctoral dissertations (see Appendix E), has contributed

to the establishment of high validity and reliability

indices for educational cognitive style mapping

32

(Scarbrough, 1976:148). A number of these studies
investigated the relationship of teachers' cognitive
style and the cognitive style of their students. Fragale
(1969) and Wasser (1969) found that students obtained
higher grades from teachers who possessed similar cog-
nitive styles than students whose style differed from
the teachers'. Witkin (1972) using his own cognitiVe
style inventory, supported these conclusions when he
found that teachers evaluated students more favorably
when the students had a cognitive style which resembled
their own.

Research based on collective cognitive style
profiles has revealed that certain specific groups have
unique cognitive styles. DeNike (1973) determined that
a collective coqnitive style existed for certain students
categorized as achievers and another collective cognitive
style for the non-achievers. These collective maps were
used to identify students who were most likely to benefit
from a particular instructional technique.

The relationship of letter grades and collective
cognitive styles was identified by Berry (1973), who
reported that students with more major cognitive style
elements tend to get better grades. In a similar study
that dealt with a specific academic discipline, Shuert
(1970) identified cognitive style elements that were

related to successful and unsuccessful mathematics

33

students. Lepke (1975) found "that some of the elements
in Hill's construct do significantly differentiate
between achievers and non-achievers" in learning Begin-
ning German. Dehnke (1966) reported that successful
English teachers had an identifiable cognitive style
which was significant for elements of symbolic mediation.
In a study of vocational education programs by Crowe
(1975), she found that distinct collective cognitive
style profiles existed for specific subject areas.
Hoogasian (1970) used collective cognitive style
profiles to predict the final grades students received
in freshman level English courses. The findings indi-
cated that collective cognitive styles were useful as
“gross" predictors of success or failure. DeNike's
study (1973) also used collective cognitive style pro-
files to predict which students were most likely to
learn from simulation game experiences. Beleutz (1975)
identified elements of educational cognitive style which
could be utilized as indicators of success in mastering
computer programming. Beleutz suggested that this
information be used as a tool for counseling potential

computer programming students.

Summary

The studies that have been reviewed are related

to this study by virtue of their application to driving

34

behavior and to educational cognitive style. They were
intended to emphasize the value of the Driver Performance
Measurement procedure and educational cognitive style
mapping. The Driver Performance Measurement procedure
was shown to be a valid and reliable method for measuring
driving behavior. The validity and reliability of
educational cognitive style mapping has been substan-
tiated through numerous studies in the "Educational
Sciences." Whereas the literature presented in this
chapter suggests a broad range of problems which could

be analyzed through the use of either procedure, it is

of interest in this study to examine the relationship

between the two.

CHAPTER III

DESIGN AND PROCEDURES OF THE STUDY

The major objective of this study was to examine
the relationship of the cognitive style of selected
novice drivers and their driving behavior. A second
objective was to compare the collective educational
cognitive styles of good novice drivers with those
identified as poor novice drivers.

The preceding chapter dealt with a review of
literature related to these objectives, i.e., cognitive
style and driving behavior. In this chapter, the fol-
lowing items will be presented: (1) source of data,
(2) sample employed, (3) design of the study, (4) methods
and conditions of data collection, and (5) instru-

mentalities of data collection.

Source of Data

 

The subjects for this study were high school
driver education graduates in the metropolitan Lansing,
Michigan area who had less than three months licensed
driving experience. From this population, 288 subjects
agreed to participate in a driver licensing project in
which the Driver Performance Measurement Procedure (DPM)

35

36

scores were collected on each driver. The sample used
in this study was drawn from this specific population.
A total of nine high schools were asked and agreed to

cooperate.

Sample Employed

 

Since it was impossible to employ all driver.
education graduates or even all 288 participants involved
in the driver licensing project which produced the needed
DPM scores, a less encompassing selection procedure was
used. 144 subjects were selected from the original
population of 288. Using DPM scores as the criterion,

72 drivers in the 25th percentile and 72 drivers in 75th
percentile were selected. This division separated the
sample into two groups which were identified as the
”good" or high performance drivers, and the "poor" or
low performance drivers (as related to each other).

An attempt was made to contact all 144 students,
however, a minimum number of fifty subjects, twenty
five from each group, was sought for statistical vali-
dation. Because the nature of this study was exploratory
and "hypothesis generating," a larger number was not
required for statistical validation (Hill & Kerber,
1967:41). A total of fifty-six subjects volunteered

to participate. Thirty-one subjects came from the lowest

37

quarter of DPM scores while twenty five came from the

highest quarter.

Methods and Conditions of Data Collection

 

The procedures used for collection of data
included: (1) retrieval of recorded Driver Performance
Measurement scores, and (2) completion of the Educational
Cognitive Style Interest Inventories.

The DPM scores and subjects names were made
available through the Highway Traffic Safety Center at
Michigan State University. These scores were part of
the data produced as a result of a driver licensing
project which was conducted during the Fall of 1976.
When the names of the selected 144 subjects were obtained,
an attempt was made to contact each one by telephone to
ask them to participate. This procedure, conducted
during the Summer of 1977, necessitated the elimination
of approximately fifty percent of the qualified subjects
due to their unavailability. Of those subjects who were
directly contacted, approximately seventy percent took
part in the second phase of data collection, i.e.,
completion of the Educational Cognitive Style Interest
Inventory.

During the course of the telephone conversation
the students were (1) told the purpose of the study,

(2) asked if they would be willing to complete a cognitive

38

style interest inventory, (3) given an appointed time
and directions to the test site, and (4) offered gift
certificates to McDonalds Restaurants valued at $2.00
per participant.

The second half of data collection was obtained
by giving the selected instrument to the subjects at
their own individual high schools. Permission to use
a classroom in each high school was received prior to
contacting subjects. The students' own schools were
chosen as the test sites because the students were
familiar with the building and neighborhood. This also
eliminated transportation problems to and from a test
site. School officials willingly granted permission to
use the school facilities in the interest of driver

education. The same examiner monitored all the tests.

Design of the Study
The DPM scores employed in this study consisted
of four separate measured behaviors which were used as
the criterion variables. The Educational Cognitive
Style Maps consisted of 20 independent variables.*
Therefore, each subject generated four DPM scores
(dependent variables) and 20 cognitive style charac-

teristic scores (independent variables).

 

*As noted in Appendix A, there are 8 additional
elements. Due to limitations of the computer program,
only 20 elements were analyzed.

39

To analyze this information, the Stepwise Regres»
sion Procedure was applied. This technique is part of

a program contained in the SAS Manual by Anthony Barr

 

and James H. Goodnight (1976). For each dependent
variable, this procedure performs separate calculations
to screen the independent variables which should be
included in a regression model. The main objective of
this procedure was to generate a linear correlation of
independent variables with dependent variables. With
each dependent variable (Yn) the Stepwise procedure
hypothesizes that Yn is a function of 20 independent

variables or

Yn = f(20X1)

Another way to represent this would be as follows:

Y =

a + a x + a x
n 0

l 1 2 2 ' ° '

The variables a1, a2, a3, etc., are added to the model
until no variable produces a significant F-statistic

for predicting the dependent variable. When no independ-
ent variable made a contribution which was statistically
significant at the .10 level, it was dropped from the
equation. Therefore, only those elements of the edu-
cational cognitive style which made the greatest contri—

bution to each driving behavior on the DPM remained.

40

This design was useful in the prediction of the cri-
terion, i.e., driving behavior.

A second objective of this study was to compare
the collective educational cognitive styles of "good"
novice drivers with those of "poor" novice drivers.

The quality of one's driving performance was a relative
process by which the upper 25 percent of DPM scores
comprised the "good" drivers while the lower 25 percent
were labeled the "poor" drivers.

To determine a composite cognitive style map for
both groups, a manual process was used. First, it was
necessary to look at each element of the cognitive style
map and to count the number of times it occurred in the
group of maps. Any element which occurred 70 percent of
the time was considered to be representative of that group
(Martin, 1977). In this manner, a collective cognitive

style profile was obtained for both groups of drivers.

Instrumentalities of Data Collection

 

The instrumentalities used in this study included
the following: (1) The Driver Performance Measurement
Procedure, and (2) the Oakland Community College Edu-
cational Cognitive Style Interest Inventory.

The DPM procedure required the novice drivers to
operate a vehicle through a pre-determined route that

contained twelve specific sequences. These sequences,

41

called BETSS (behavioral environmental traffic situ-
ational sequences), described the driving tasks required
for a particular situation. A variety of typical
driving situations were included within four BETSS.
Each BETSS was divided into three subBETSS to provide
a more manageable division for rating the numerous
driving behavior patterns. An example of a test
sequence found on a DPM rating form can be seen in
Table 1. The entire recording form is contained in
Appendix F. As each subject drove through specific
BETSS or subBETSS, an observer rated the driver's
performance. The observer checked the apprOpriate box
describing the driver's behavior as "U" (unsatisfactory)
or "S" (satisfactory). This was done for all four
elements evaluated on the DPM, i.e., Pattern Concept,
Search Behavior, Speed Control, and Direction Control.
Pattern Concept was the first element to be rated
because it included the relative timing of the other
three driving behaviors while allowing observers to
rate and observe succeeding segments which could other-
wise go unobserved. Following the recording of the
Pattern behavior, the elements of Search, Speed and
Direction Control were rated.

Since the Stepwise Procedure requires numeric

data, in this study DPM ratings were given one point

 

42

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43

for a satisfactory performance or zero for unsatisfactory
performance of a behavior. Two DPM runs were conducted
for each subject, therefore each of the four dependent
variables could generate a maximum of twenty-four points.

As an index of safe driving ability the DPM
procedure had reliability correlations of 0.75 to 0.85.
"Content validity rested on the expert opinion and
experience of the project team in various fields of
traffic and psychological research" (Forbes, l973:5).
Based on these findings, it is logical to assume that
the validity and reliability of the DPM are sufficient
for the purposes of this study. A more detailed
description of the procedures used in determining reliaf'
bility and validity of the DPM can be found in the 1
Driver Performance Measurement Procedure Research.

The Educational Cognitive Style Interest Inventory,
from which a map of an individual's cognitive style is
produced, was develOped by Dr. Joseph E. Hill, President
of Oakland Community College. Permission to use this
test for the purposes of this study was obtained from
Dr. Hill in March of 1977. This inventory contains 224
questions which can measure up to 28 cognitive traits
describing the manner in which an individual acquires
meaning from his environment. A total of 20 traits were

measured in this study. For each trait, eight questions

44

were asked. Table 2 gives examples of the questions
and the 20 traits that were measured. The entire inven-
tory and answer sheet can be found in Appendix C.

The students were instructed to decide to what
degree the statement was like themselves. Their choices
were "U" (usually), "S" (sometimes), or "R" (rarely).

The validity and reliability indices of Educational
Cognitive Style Mapping that have been found are based
on 84 doctoral dissertations in addition to the work
which has been completed by Oakland Community College
(Scarbrough, 1976:148). These dissertations are listed
in the Appendix of this study.

Validity was determined through the use of point
bi-serial correlation. By averaging all the elements of
the cognitive style maps, the value of the bi-serial

coefficient was:

rbis = .783

To determine the value of the reliability coeffi-
cient, the Kuder-Richardson formula was used. The

results of this procedure were:
r = .81

For both the validity and reliability coefficients,
the data processing center at Oakland Community College

was used (Scarbrough, 1976:149).

45

TABLE 2

Sample Cognitive Style Inventory Questions
and Elements Measured

22;; Lxm.:. rust-:w‘_ "' “————~-_.-

Question

1. I prefer the traditional lecture
type classes

2. I quote statistical data to others
in order to prove my point in an
argument

3. I prefer Traps to verbal directions
when I am going to a strange place

4. I solve mathematical problems rrore
rapidly if they are written

5. I try not to say things to hurt the
feelings of others

6. I would go out of my way to see
beautiful scenery

7. I believe that a promise should be
kept

8. I an able to "play a role" anywhere
if I agree to

9. I use facial expressions to
carmmicate actions
10. I am better coordinated than most
people
11. Unless spoken to first, I do not
speak to a teacher

12. I predict accurately if I will be
able to get my work done

13. In group discussions, I assume
the leadership to nove the group
to reach a decision

14. I make personal decisions after

discussing them with my friends
15. I caxsult with my immediate family
16. I prefer to study on my cm

17. I understand a topic better if I
analyze it to learn how it differs
fran other topics

18.'n\emreIlcmaboutapmblemthe
mIeIwanttolcwabcutit

19.1.ifeissinpleifycugobytheniles

20. I like to see several exarrplee before
startirg a new project

Element
TVL Theoretical Visual Linguistics

TAL Theoretical Auditory Linguistics

'IVQ Theoretical Visual Quantitative
TAO Theoretical Auditory Quantitative
QCEM Qualitative Code Empathic

(TIES Qualitative Code Esthetic

CXZEI‘ Qualitative (bde Ethic

OCH Qualitative Code Histrionic

ocx Qualitative Code Kinesics

QCKH Qualitative Code Kinestetic

(It? Qualitative Code Proxemics

QCS Qualitative Code Synnoetics

OCT Qualitative Code Transactional

A Associates
F Emily
I Individuality

D Difference

a Relationship

M Magnitaxle
L Appraisal

 

46

Summary

In summary, the following procedures for the
collection of the data were conducted:

1. During the Fall of 1976, 288 students partici-
pated in a driver licensing project which produced DPM
scores for each subject.

2. Permission to use these DPM scores was obtained
from the Highway Traffic Safety Center of Michigan State
University during the Spring of 1977.

3. Permission to use the Educational Cognitive
Style Interest Inventory in this study was obtained from
Dr. Joseph E. Hill, President of Oakland Community College.

4. The selection of subjects was conducted by
methods described in the section on Sample Employed.

5. The area high schools of each subject were
contacted for permission to use a classroom as a test
site.

6. Students were contacted by telephone and asked
to participate.

7. 56 subjects were administered the Educational
Cognitive Style Interest Inventory during July, 1977.

8. Completed tests were scored by the Oakland
Community College (Michigan) Testing Center on August 15,

1977.

47

9. The dependent and independent variables were
analyzed (using the Stepwise Procedure) on October 17,

1977 at Oakland Community College Computer Center.

CHAPTER IV

ANALYSIS OF DATA

The purpose of this study was twofold:

1. To compare the collective cognitive styles of
good novice drivers with those identified as poor novice
drivers; and

2. To examine the relationship of the edu-
cational cognitive style of selected novice drivers and
their driving behavior as evidenced by the regression
model.

In the preceding chapter the design and procedures
of the study were presented. In this chapter the analysis
of data is represented. The following items are included
in this section: (1) collective cognitive style profiles;

and (2) the Stepwise regression procedure.

Collective ngnitive Style Profiles

 

One of the purposes of this study was to deter-
mine which elements of cognitive style were common to
each group of drivers tested, i.e., those subjects who
scored in the upper and lower quartiles of the Driver

Performance Measurement Procedure (DPM). Cognitive style

48

49

elements were separated into major and minor orientation
categories. Drivers with major orientation in a cognitive
style element are said to have above average ability or
strength in that area, i.e., at a given level of edu-
cational development these individuals realized an element
score in the 50th-99th percentile range. A minor orien~
tation indicated average ability in an element, i.e., at

a given level of educational development an individual
realized a score in the 26th-49th percentile range (Hill,
1971:6).

The highest scoring group of DPM subjects had
twelve factors of major orientation and eight of minor
orientation for its collective cognitive style. The
factors in the major category were TVL (Theoretical
Visual Linguistics), QCEM (Qualitative Code Empathic),
QCES (Qualitative Code Esthetic), QCET (Qualitative Code
Ethic), QCH (Qualitative Code Histrionic), QCK (Qualitative
Code Kinesics), QCKH (Qualitative Code Kinesthetic), QCP
(Qualitative Code Proxemics), QCS (Qualitative Code
Synnoetics), I (Individuality), M (Magnitude), and D
(Difference). The minor orientation elements included
TAL (Theoretical Auditory Linguistics), TVQ (Theoretical
Visual Quantitative), TAQ (Theoretical Auditory Quantita-
tive), QCT (Qualitative Code Transactional), A (Associates),

F (Family), R (Relationship), and L (Appraisal).

50

To give the reader a sense of the meaning of the
collective map for the highest scoring group, a behavioral
interpretation is provided. A person's cognitive style
is comprised of three sets of elements: symbolic medi-
ation; cultural determinants; and modalities of inference.
Because of their inter-relationship, these sets are printed
in the form of a Cartesian product (see Definition of
Terms). For example, Table 3 shows the map of these sets
for this particular group of subjects. The Cartesian
product is used to display all the elements of a person's
cognitive style because the three main categories of
cognitive traits which describe the ways a student seeks
meaning should not be treated separately.

Using the collective map of the drivers in the
highest scoring DPM group as an example, the first set of
the Cartesian product shows the symbols which indicate
the ways individuals acquire meaning through words, numbers
and the senses. Average ability, as defined above, can
be seen in the following elements: (1) T'AL, the ability
to listen to directions; and (2) T'VQ and T'AQ, the ability
to derive meaning from both reading and hearing mathe-
matical concepts. In this set, above average ability
was revealed in the element TVL, the ability to derive
meaning from written materials and comprehend what is

read.

51

 

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52

The qualitative symbols, which are included in
the first set of the map, indicated average ability to
interact verbally with others in a positive manner as
displayed by the symbol Q'CT. However, this collective
map contained eight elements where above average abilities
appeared. These drivers demonstrated an above average
ability in the following elements: (1) QCP, the ability
to judge physical and social distance; (2) QCK, the
ability to communicate by motions of the body; (3) QCS,
the ability to know one's limitations; (4) QCKH, the
ability to perform motor skills (such as those required
to operate an automobile); (5) QCH, the ability to
perceive the role expectations of a situation and act
them out; (6) QCET, the ability to commit oneself to a
set of principles, obligations and duties; (7) QCES,
the ability to see the beauty of an idea or object; and
(8) QCEM, the ability to empathize and see things from
another person's point of view.

The cultural determinants of the meaning this
"collective driver" derives from symbols indicate an
above average orientation in individuality (I) yet he
would still give consideration to the opinions of family
and/or authority figures (F') and associates (A'). These
three influences comprise the second set of the Cartesian

product which make up a cognitive style map.

53

The third set shows the way in which this group
of drivers reason or infer. In this set there is an
above average use of categorical reasoning (M) and a
tendency to contrast and compare selected characteristics
when seeking meaning (D). To a lesser extent, this group
would be inclined to synthesize a number of incidents
into a unified meaning (R').

A collective cognitive style element in a parti-
cular group's profile was based on the strength of each
individual's factors. If an element was present as a
"major," or "minor" (or combination of the two as a
"minor") 70 percent of the time or greater it was con-
sidered to be representative of that group (Martin, 1977).
Two frequency distributions, contained in Table 4, were
formed to determine group orientation on each of the
twenty elements tested for the independent variables.

{The figures in parenthesis indicate the total number of
subjects who had a major orientation in a particular
element. Only five subjects had negligible orientations

in an element and they are identified by a double asterisk
(**). Since there was a maximum possibility of 25 subjects
in the high group and 31 subjects in the low group, the
remaining unidentified subjects were those having a minor
orientation. For example, on the element TVQ for the high

scoring DPM group contained on Table 4, eleven subjects

54

TABLE 4

Collective Cognitive Style Profiles

High DPM Scoring Drivers' Iow'DPM Scoring Drivers'

 

Group Orientation Group Orientation
(17 subjects or more needed (22 subjects or more needed
for major orientation) for major orientation)

T VL Major (17)* Major (23)
T AL Minor (7) Minor (12) (2)**
T VQ Minor (11) (1)** Minor (11) (1)**
T AQ Minor (7) Minor (10)
Q CEM Major (23) Major (27)
Q CES Major (20) Major (24)
Q CET Major (20) Major (26)
Q CH Major (19) Minor (16)
Q CK Major (17) Minor (15)
o cxn Major (21) Minor (20) (1)**
Q CP Major (17) Minor (19)
Q CS Major (24) Major (28)
Q CT Minor (15) Minor (16) (1)**
I Major (23) Major (28)
A Minor (7) (l)** Minor (7)
F Minor (13) Minor (16) (1)**
M Major (21) Major (26)
D Major (19) . Minor (19)
R Minor (12) Minor (16)
L .Minor (14) .Minor (18)

 

*
Total number of subjects per group with a major
orientation.

** .
Total number of subjects per group with a negl1-
gible orientation.

55

had a major orientation, one had a negligible orientation
and therefore the remaining unidentified 13 subjects had
a minor orientation.

The highest DPM scoring group was composed of 25
subjects. Since an element had to be present at least
70 percent of the time to be included in a particular
orientation category, that element had to appear as'a
major (or minor) orientation on at least 17.5 maps
(rounded to 17) to be considered a major (or minor)
orientation on the collective profile. Similarly, with
31 subjects in the lowest scoring DPM group, an element
had to appear as a major (or minor) on 21.7 maps (rounded
to 22) to be included as a major (or minor) on the
collective map. In both groups, a factor that occurred
in the combination of major and minor orientations in
at least 70 percent of the maps was considered a minor
element.

The collective cognitive style of the lowest
scoring group of DPM subjects included seven factors of
major orientation (see Table 4). It included TVL, QCEM,
QCES, QCET, QCS, I and M. The remaining factors were of
minor orientation, i.e., TAL, TVQ, TAQ, QCH, QCK, QCKH,
QCP, QCT, A, F, D, R, and L. A map of this collective
cognitive style in the form of a Cartesian product is

found in Table 5.

56

 

 

 

 

 

 

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m mandﬁ

57

When a chi square was used to see if there was a
significant difference between the collective cognitive
styles of both groups, the only significant difference
appeared with the element QCH, Qualitative Code Histrionic.
On this item the highest scoring DPM group had a major
orientation while the low scoring group had a minor
orientation. The difference between the groups was
significant at the .10 level. Based on this data,
generalizations about a collective cognitive style and
driving behavior cannot be made beyond the specific

groups in this study.

The Stepwise Regression Procedure

 

The Stepwise regression procedure is a statistical
term used to describe any one of five different techniques
which generate regression models. These techniques in-
clude Forward Selection, Backward Elimination, Stepwise,
Maximum R Square Improvement, and Minimum R Square
Improvement. With all these techniques, the relative
strengths of the relationship between a collection of
independent variables and dependent variables is calcu-
lated. Through these procedures a regression model can
be produced to identify those independent variables most
likely to be related to the dependent variables on which
they were regressed. These models can then be used to

predict a score on each dependent variable.

58

The Stepwise technique chosen for this study was
the Maximum R Square Improvement procedure. It is con—
sidered the best procedure because the Maximum R Square
evaluates every variable before entering a new variable
into a model. For each step calculated, the best model
is produced. As a consequence of this, the Maximum R
Square technique looks for the best one-variable model,
then finds the best two-variable model by comparing and
switching variables to produce the greatest increase in
the R square statistic. The process continues comparing
and switching to produce the best three-variable model,
the best four-variable model, etc. The model reaching
the highest level of significance (with all the independent
variables within the specified significance level) was
selected as the best all around model for predicting a
score on the dependent variable. A more complete
description of all five Stepwise techniques can be found
in Appendix G.

Under the Maximum R Square procedure a significant
model was produced for all four dependent variables
investigated in this study. Included in these criterion
variables were the DPM rating categories of Pattern
Concept (Y1), Search Concept (Y2), Speed Control (Y3),
and Direction Control (Y4).

As seen in Table 6, the best model (as defined

above) for predicting the dependent variable Y at the

1

59

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w manda

60

.10 significance level occurred in STEP 5 of the statisti-
cal procedure. The models in all of the first five steps
were significant. However, STEP 5 contains the model
which reached the highest level of significance without

a non-significant variable entering into a model. In

STEP 1 the variable QCKH (psychomotor ability) alone had
an F ratio of 7.30 which was significant at the .0092
level. (The Critical Value of F at the .10 level for 1
and 54 degrees of freedom = 2.84.) All the variables
added to the models up to STEP 5 were significant at the
.10 level. (The Critical Value of F in STEP 5 for 5 and
50 degrees of freedom = 2.00.) STEP 6 through STEP 20
contained no models which met the .10 level of significance
because of the entrance of non—significant variables into
the model. The steps containing the non-significant
variables can be found in Appendix F. In STEP 5 the
variables TAQ, QCH, QCET, TVL and QCKH formed a model

for predicting Pattern Concept (Y1) which was significant
at the .0023 level with an F ratio of 4.36. The model is

as follows:

Y1 = 16.07 - .077TVL - .083TAQ - .069QCET + .OGBQCH

+ .114QCKH

This means that a score for the predicted driving behavior

(Pattern Concept) of Subject N can be calculated by

61

entering the subject's cognitive style scores for the
elements in the equation. The numerical data contained
in this equation, along with the R square values can be
found in Appendix H.

The model developed for predicting Search
Behavior (Y2) contained only one variable which was
significant at the .10 level. As seen in Table 7, the
element QCH (the ability to meet role expectations) had
an F ratio of 3.25 which was significant at the .0771
level. The Critical Value of F with 1 and 55 degrees of
freedom was 2.84. The regression equation fer predicting

Y2 was:

Y2 = 8.52 + .OSlQCH

There were no other significant models developed at the
specified level for this dependent variable.

The fifth step, contained in Table 8, shows the
model which is most likely to predict Speed Control
scores (Y3). All four of the preceding models were
significant at the .10 level, however, STEP 5 contained
the best model as defined above. This model had an F
value of 5.37 which was significant at the .0005 level.
The elements contained in this model were TVL, QCEM,
QCET, QCKH, and QCP. The Critical Value of F was 2.00
for 5 and 50 degrees of freedom. The following equation

was developed to predict this dependent variable:

62

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t

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h mnmdﬁ

63

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. om deem cocoons

 

 

 

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64

Y3 = 17.75 - .069TVL - .062QCEM - .088QCET + .113QCKH

+ .097QCP

The best model for predicting a score on the
variable Direction Control (Y4) at the .10 significance
level contained one cognitive style element. The inde-
pendent variable QCKH had an F ratio of 3.25 which was
significant at the .0771 level. The Critical Value of
F with 1 and 55 degrees of freedom was 2.84. The
regression model (see Table 9) which best predicts Y

4
was :

Y4 = 13.35 + .061QCKH

No other models were significant at the .10 level.

Summary

One of the purposes of this study was to compare
the collective cognitive style profiles of those subjects
in the highest quartile of DPM scores with those in the
lowest quartile. Except for one cognitive style element,
QCH (the ability to perceive the role expectations of a
situation and act them out), there was no significant
difference between the groups.

Also included in this chapter was a discussion
of how the Stepwise regression procedure was employed.
Specifically, the Maximum R Square Improvement technique

was used to show the relationship of the cognitive style

65

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m mammﬁ

66

of selected novice drivers and their driving behavior.
Through the use of this statistical method, regression
models were developed to predict driving performance.
At the .10 significance level a model was produced for
the prediction of all four dependent variables, i.e.,
Pattern Concept, Search Behavior, Speed Control and

Direction Control.

CHAPTER V

SUMMARY, CONCLUSIONS, DISCUSSION

AND RECOMMENDATIONS

The concluding chapter of this study will include:
(1) a summation of this study including methods and find-
ings; (2) the conclusions warranted by the resulting data;
(3) a discussion; and (4) recommendations for further

study.

Summary
The primary purpose of this study was to examine
the relationship of the educational cognitive style of
novice drivers and their driving behavior. To measure cog-
nitive style the Educational Cognitive Style Interest

Inventory of Oakland Community College (Michigan) was

 

used. The Driver Performance Measurement Procedure (DPM)
developed at Michigan State University was employed to
measure driving behavior.

The subjects for this study were high school driver
education graduates from the Lansing, Michigan area who had
less than three months licensed driving experience. From
this population, 288 subjects agreed to participate in a

driver licensing project during the Fall of 1976 in which

67

68

the DPM scores were collected on each driver. A sample of
56 volunteers from this group were administered the Egggg-
pional Cognitive Style Interest Inventory during the Summer
of 1977. These subjects were divided into two groups, i.e.,
the "good" and "poor" drivers, based on their DPM scores.
The "good" drivers were those subjects who scored in the
fourth quartile of the DPM. Twenty—five of the volunteers
came from this group. The "poor" drivers were those who
scored in the first quartile of the DPM. Thirty-one of the
volunteers were from this group.

To examine the relationships of cognitive style and
driving behavior two procedures were used. The first was
to compare the collective cognitive styles of the highest
scoring DPM group with the styles of the lowest scoring
DPM group. The second procedure was to formulate regression
models (equations) to determine what cognitive style vari-
ables, if any, could be generated to predict the driving
behaviors measured by the DPM.

Specifically, this study answered the following
questions:

1. What elements of the collective cognitive
styles were common to the group which scored in the highest
quartile on the DPM?

In forming the collective cognitive style for this
group, twelve factors of major orientation and eight of

minor orientation were found. The elements in the major

69

category were: TVL (Theoretical Visual Linguistics),

QCEM (Qualitative Code Empathic), QCES (Qualitative Code
Esthetic), QCET (Qualitative Code Ethic), QCH (Qualitative
Code Histrionic), QCK (Qualitative Code Kinesics), QCKH
(Qualitative Code Kinesthetic), QCP (Qualitative Code
Proxemics), QCS (Qualitative Code Synnoetics), I (Indi-
viduality), M (Magnitude), and D (Difference). Included
among the elements with a minor orientation were: TAL
(Theoretical Auditory Linguistics), TVQ (Theoretical
Visual Quantitative), TAQ (Theoretical Auditory Quantita-
tive), QCT (Qualitative Code Transactional), A (Associates),
F (Family), R (Relationship), and L (Appraisal).

2. What elements of the collective cognitive
styles were common to the group which scored in the lowest
quartile on the DPM?

The collective cognitive style profile for the
lowest scoring group of DPM subjects included the seven
following factors of major orientation: TVL, QCEM, QCES,
QCET, QCS, I and M. The remaining factors were of minor
orientation: TAL, TVQ, TAQ, QCH, QCK, QCKH, QCP, QCT, A,
F, D, R, and L. The Chi square test of significance
revealed only one variable at the .10 level, QCH, which
was significantly different on the two collective profiles.

3. What elements of a person's cognitive style

were correlated at a minimum significance level of .10

70

with the "Pattern Concept" rating on the DPM as evidenced
by the regression model?

The elements TAQ, QCH, QCET, TVL, and QCKH were
all the factors correlated with the dependent variable
"Pattern Concept" (Y1) within the .10 level of significance.
The regression equation for the predicted value of this

variable was:

91 = 16.07 - .077TVL - .083TAQ

- .069QCET + .063 QCH + .114QCKH

4. What elements of a person's cognitive style
were correlated at a minimum significance level of .10
with the "Search Behavior" rating on the DPM as evidenced
by the regression model?

The only element correlated with the dependent
variable "Search Behavior" (Y2) at the .10 significance
level was QCH. The regression equation in this case was:

if

2 = 8.52 + .051QCH

5. What elements of a person's cognitive style
were correlated at a minimum significance level of .10
with the "Speed Control" rating on the DPM as evidenced
by the regression model?

Five elements were correlated with the dependent

variable "Speed Control" (Y3) including TVL, QCEM, QCET,

71

QCKH and QCP. These elements were significant at the .10

level. The following equation was developed to predict

Y3:

i3 = 17.75 - .069 TVL - .062QCEM

- .088QCET + .113QCKH + .097QCP

6. What elements of a person's cognitive style
were correlated at a minimum significance level of .10
with the "Direction Control" rating on the DPM as
evidenced by the regression model?

QCKH was the only element correlated with the
dependent variable "Direction Control" (Y4) at the .10

level. The regression equation most likely to predict

Y4 was:

f4 = 13.35 + .oslocxa

Conclusions
The following conclusions are based on the find-
ings in this study.
1. A general collective cognitive style was not
found which identifies good and poor drivers.
2. Driving behaviors measured by the DPM were
related to elements of educational cognitive

style.

72

3. Regression models were found which predict
driving behaviors based on cognitive style

mapping scores.

Discussion

 

Based on the findings of this study it appears
that driver education teachers have a tool available
(Oakland Community College Educational Cognitive Style
Interest Inventory) for predicting driving behavior.
This information is valuable for the teacher who wants
to identify before hand, individual student strengths
and weaknesses in driving. The teacher would have to
administer this cognitive style inventory to a class
before any of the laboratory phases of driver education
were begun. This teacher could then calculate predicted
driving behaviors by applying cognitive style scores to
the related equations. For example, if a teacher wanted
to predict overall driving ability, which "Pattern Con-

cept" (Y1) measures, you would take the equation.

- .069QCET + .063QCH + .114QCKH

Into this equation would be entered the corresponding
cognitive style scores. In a hypothetical situation,
Student A had the following scores: TVL = 50; TAQ = 30;

QCET = 60; QCH = 50; QCKH = 70.

73

The equation then becomes

Y1 = 16.07 - .77(50) - .083(30) - .069(60)

+ .063(50) + .114(70)

Y1 = 16.72

Another student, Student B, may have the following Scores:

TVL = 70; TAQ = 40; QCET = 70; QCH = 40; QCKH = 50.

Y = 16.07 - .O77(70)

1 .083(40) - .069(70)

+ .063(40) + .114(50)

Y

1 10.75

In interpreting these scores, it would probably
be most advantageous to the average classroom teacher to
arrange the scores of all the students in descending order
to estimate the relative driving ability predicted for
these people. For those desiring a more precise cutoff
point between a satisfactory and unsatisfactory scores,
researchers in the Michigan Road Test Evaluation study
decided that a minimum passing score corresponded to 65
percent of the maximum total score (Vanosdall, 1977,

p. 98). Since the maximum total score for actual driving
behaviors in this study was 24, a student needed a score
of 15.80 or higher to pass. Based on this information,

a teacher could speculate that Student A would demonstrate

74

a higher level of proficiency in operating a vehicle than
Student B.

Weaknesses that are identified can be attended to
through a more intense instructional procedure. For
example, students who are weak in their search behavior
could be drilled in the development of perceptual skills.

Estimating a score on the dependent variable'
"Pattern Concept" is probably the most useful since it
includes the timing of all the driving behaviors._ However,
the importance of each individual behavior should not be
under-rated.

It is probably no surprise to driver education
teachers that psychomotor skills (QCKH) play such an
important role in "Speed Control" and "Direction Control."
In both cases the simplest model (although not necessarily
the most statistically significant) for predicting these
behaviors contained the single variable of QCKH.

The dependent variable of "Search" was the only
exception to this. It is interesting to note that the
independent variable QCH, Qualitative Code Histrionic, was
the only significant element for predicting this score.
QCH indicates an ability to exhibit a deliberate behavior
or to play a role to produce some particular effect on
other persons. An individual with a major orientation in
this element knows how to fulfill role expectations. One

can only speculate on reasons why there was a correlation

75

between these two variables. One possibility is that when
the novice drivers in this study got behind the wheel they
understood what the role expectations of a driver were,
expecially with regard to lane changing and looking
systematically for traffic information. These are pro-
cedures that do not necessarily require highly developed
motor skills. However, they do require the exhibition of
deliberate behaviors. Another possibility is that these
novice drivers simply "acted" like good drivers because

an observer was present when their driving behavior was
being rated. HOpefully, the former explanation is the
reason why the "Search" behavior was significant.

Even if there was no significant relationship
between educational cognitive style and driving behavior,
it is still a very valuable instrument for any classroom
teacher. Teachers should realize that their students have
varying cognitive styles. They do not all learn in the
same way. However, teachers tend to present material
according to their own cognitive style. As pointed out
in the Review of Literature, a student's academic perform-
ance increases when a positive correlation exists between
his cognitive style and that of his teacher. The student
whose cognitive style differs greatly from his teacher's
cognitive style actually gets lower grades. The teacher
who recognizes these differences could take advantage of

the students' cognitive style by varying instructional

76

techniques. For example, assume Student A has the fol-

lowing map of his cognitive style:

SET I SET II SET III

TAL A R
_ TVL M
Style QCEM
QCT
QC H

COgnitive

The elements TAL (Theoretical Auditory Linguistic) and TVL
(Theoretical Visual Linguistic) indicate above average
ability in deriving meaning from both written and spoken
words. QCEM (Qualitative Code Empathetic) shows a high
degree of sensitivity to the feelings of others. Very good
communicative skills are indicated by the element QCT
(Qualitative Code Transactional). QCH (Qualitative Code
Histrionic) is the element which was correlated with the
driving behavior of "Search." It shows above average
ability in knowing how to fulfill role expectations. The
symbol A (Associates) indicates that this person prefers
to "bounce" insights off peers as a means of deriving
meaning from information acquired.i The type of reasoning
used by this person, M (Magnitude) and R (Relationships)
shows a need for pre-selected categories, classifications,
rules and definitions, as well as a need for a number of
examples. While it is somewhat of a generalization, this
person would probably benefit from the use of small dis-

cussion groups with peers.

77

Another example of the information a teacher can

gain from a cognitive style map is the following:

 

SET I SET 11 SET III
Cognitive TVL I M
= TVQ x x
Style QCET

For this person, a structured independent study program
would take advantage of his preferred learning style. I
(Individuality) shows that this person prefers to learn on
his own. TVL (Theoretical Visual Linguistic) and TVQ
(Theoretical Visual Quantitative) indicate abilities to
acquire meaning of words and numerical concepts through
written materials. The absence of TAL and TAQ would show
that this student does not prefer to learn through listen-
ing as in lectures. However, with a major orientation in
M (Magnitude) a teacher would have to tell this student
exactly what he is supposed to acquire on his own.
Admittedly, these two models are over simplifi-
cations of the actual maps which were scored and printed
at Oakland Community College. (An example of these maps
is contained in Appendix F.) An inventory developed by
Dr. Joseph Bosco of the State University of New York at
Albany, Center for Curriculum and Instruction, does produce
maps which are easier to administer and interpret. A copy

of this inventory can be found in Appendix G. Research

78

has not been conducted to examine the relationship
between the DPM and Dr. Bosco's inventory. Until then,
the scores obtained through the use of this inventory
cannot be substituted for the scores on the Oakland
Community College inventory.

The regression equations developed in this study
have combined several of the elements of educational
cognitive style to predict driving behavior. It is
interesting to note that in the prediction of the "Pattern
Concept" score (Y1) and the "Speed Control" score (Y3)
the element TVL (reading ability) and QCET (commitment to
a set of values) carried negative regression weights.
This means that these elements were negatively correlated
with the two driving behaviors. An explanation of this
phenomena could not be found.

Most students can acquire some level of learning
regardless of how the teacher presents information. How—
ever, as shown in the two examples above, there are ways
of enhancing the learning situation for some of the stu-
dents. While individualized instruction is not always
possible, a teacher who does not vary his teaching style
is doing some of his students an injustice.

It is important for anyone who intends to use
educational cognitive style mapping as a predictor of

driving behavior to remember three points:

79

1. Scores from other cognitive style inventories
should not be entered in the equation provided until
further research is conducted using specific instruments.

2. The models produced are not guaranteed to

 

accurately represent "real world" conditions. In the use
of any statistical procedure there is always the possi-
bility of error.

3. The DPM procedure should only be conducted

under the guidelines established by Forbes (1973).

Recommendations

 

1. Replication of this study using only those
elements of the Educational Cognitive Style Interest
Inventory which were related to driving behavior.

2. The use of a larger group of subjects to
determine if a collective cognitive style map of good and
poor drivers would be statistically significant.

3. Replication of the study using a simpler
version of educational cognitive style measurement.

4. Practical application of the regression
equations combined with a follow-up use of the DPM to
check the validity and reliability of a system for
predicting driving behavior.

5. Replication of the study employing the quali-
tative symbols which indicate the influence of sensory

stimuli used by an individual to acquire knowledge.

REFERENCES

80

REFERENCES

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Allport, G. W. and P. E. Vernon. Studies in Expressive
Movement. New York: Macmillan, 1933.

 

 

Baker, J. Stannard and Glenn V. Carmichael. Giving and
Scoring Driver Road Tests. Chicago: Traffic
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Barr, Anthony J., James H. Goodnight, et a1. SAS Manual.
Raleigh, N.C.: Sparks Press, 1976.’

 

Belentz, John A. "Cognitive Style as an Indicator of
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1975.

Berry, J. J. "Collective Cognitive Style and Academic
Performance in an Introduction to Psychology
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College, 1973.

Billion, C. E. "Driver Characteristics and Behavior
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D.C., 1957.

Blanton, William E. and Terry Bullock. "Cognitive Style
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276-287.

 

Bosco, Joseph. Personal interview, April 13, 1978.

Broverman, D. M. "Cognitive Styles and Intra-individual
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28 (1960), 240-256.

 

Coop, R. H. and I. E. Sigel. “Cognitive Style: Implica-
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81

82

Conant, James B. The Education of American Teachers.
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Crawford, A. "The Overtaking Driver." Ergonomics, 6,
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Crowe, Kathleen P. "A Comparative Analysis of Selected
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Dehnke, Ronald. "An Exploration of the Possible Isomorph-
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Secondary School English." Dissertation Abstracts
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DeLoach, Joseph F. "An Analysis of Cognitive Style Dis-
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in Instructional Evaluation: An Exploratory Study
in the 'Educational Sciences.'" Dissertation
Abstracts International, 31:3806-08A, 1970.

 

 

DeNike, Lee. "An Exploratory Study of Cognitive Style as
a Predictor of Learning from Simulation Games."
Dissertation Abstracts International, 1973.

 

Draper, N. R. and H. Smith. Applied Regression Analysis.
New York: Wiley, 1966.

 

Edwards, D. S. and C. P. Hahn. "The Use of Filmed Driver
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American Institute of Research, July, 1964.

Fine, J. L., J. L. Malfetti, and E. J. Shoben. "The
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The Safety Research and Education Project, New
York: Teachers College, Columbia University, 1965.

Forbes, T. W., et a1. Driver Performance Measurement
Research, Phase 1, Method Development. Prepared
for U.S. Department of Transportation, National
Highway Traffic Safety Administration, Contract
F-11—7627. National Technical Information Service,
Springfield, Virginia, DOT—HS-800-881, September
1972. .

 

 

. Driver Performance Measurement Research, Final
Report, Volume 2. Prepared for U.S. Department of
Transportation, National Highway Traffic Safety

 

 

83

Administration, Contract F-11-7627. National
Technical Information Service, Springfield, Vir-
ginia, DOT—HS-800-881, February 1973.

Forbes, T. W., et a1. "Driver Performance Measurement."
Presented at the Committee on Road User Character-
istics of the Highway Research Board, Washington,
D.C., January 21, 1974.

"Driver Performance Measurement," January 21,
1974, p. 3, citing J. E. Uhlaner, Human Perform-
ance Jobs, and Systems Psychology--The Systems
Measurement Bed, Technical Report S-2, pp. 31.
Arlington, Va.: U.S. Army Behavior and Systems
Research Laboratory, 1970.

Fragale, Marvin. "A Pilot Study of Cognitive Styles of
Selected Faculty Members and Students in a Com-
munity College Setting." Dissertation Abstracts
International, 31:1595-04A, 1970.

 

 

Gardner, R., et a1. "Cognitive Control: A Study of
Individual Consistencies in Cognitive Behavior."
Psychological Issues, 1, No. 4 (1959).

 

Greenshields, B. "Driving Behavior and Related Problems."
Highway Research Record, 25 (1963), 14-32.

 

Hill, Joseph E. The Educational Sciences. Bloomfield
Hills, Michigan: Oakland Community College, 1971.

 

Hill, Joseph E. and August Kerber. Models, Methods and
Analytical Procedures in Educational Research.
Detroit: Wayne State University Press, 1967.

 

 

Hoogasian, Vaughn. "An Examination of Cognitive Style
Profiles as Indicators of Performance Associated
with a Selected Discipline." Dissertation

- Abstracts International, 32:199-01A, 1970.

 

 

Human Resource Research Organization. The Safe Performance
Curriculum. Prepared for U.S. Department of
Transportation National Highway Traffic Safety
Administration, Contract DOT-HS-003-2427, 1974.

Kagan, J., et a1. "Conceptual Style and the Use of Affect
Labels." Merrill-Palmer Quarterly, 6 (1960),
261-278.

 

84

Kagan, J., et al. "The Psycholoqical Significance of
Styles of Conceptualizationﬂ' In J. F. Wright and
J. Kagan (eds.). "Basic Cognitive Processes in
Children." Monograph of Societygfor Research in
Child Development, 28 (1963), 73-112.

 

 

Lepke, Helen S. "An Exploratory Study of Cognitive Style
as an Aspect of Prediction of Achievement in
Individualized and Conventional Instruction in
Beginning College German." Dissertation Abstracts
International, 36:6632-10A, 1975.

 

 

London, David T. "Concurrent Validity of Hill's Educa-
tional Cognitive Style Model as a Prototype for
Successful Academic Programs Among Lower-Class
Students." Dissertation Abstracts International,
36:4357-07A, 1975.

 

Manilla, S. James. "A History of Oakland Community College
with Emphasis on Multi-Campus Administration,
Systems Approach to Instruction, and the 'Educa-
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Martin, C. Bruce. Letter received in personal corres-
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McKnight, A. James, et a1. Driver Education Task Analysis
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McLean, J. and E. Hoffmann. "Analysis of Drivers' Control
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Nunney, Derek N. and Joseph E. Hill. "Personalized Edu-
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85

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1977.

86

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Witkin, H. A. "Some Implications of Research on Cognitive
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APPENDICES

87

APPENDIX A

THE EDUCATIONAL SCIENCES

88

 

 

 

 

 

 

 

 

 

%%

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ICC

OAKLAND
COMMUNITY
COLLEGE

Copyright, February 11111

2480 Opdyko Rood Bloomhctd Holls, Michngm 48013

89

 

 

 

E
[MS
88

Dr. Joseph E. Hill

Fundamental disciplines are bodies of knowledge generated
by communities of scholars that produce pure and distinctive
forms of information about phenomena which they study.
Biology, history, art, psychology and mathematics are
examples of fundamental disCiplines.

 

 

 

 

A fundamental discipline must be either a science or an art,
it cannot be both. Sciences, as bodies of information, must
recognize the principles of completeness and that of closure.
The arts (e.g., history, a synoptic art, and art, an esthetic art)
do not need to recognize these two principles.

Fundamental Disciplines

  

'J‘ ("Academic 56'0”...)
wrist" g f
.5 ’ ’
V g g g S 8
O x f

 

Nettle) and Life

  

Applied or Derivative Fields
of Knowledp
(“Hofessiomls”)

Complementing the fundamental disciplines are the applied
or derivative fields of knowledge. These bodies of
information are generated by practitioners who deal with
practical considerations of the human condition. Medicine,
pharmacy, engineering and law are examples of applied fields
of knowledge.

The applied fields are composed of terms and methods of
inquiry borrowed from the fundamental disciplines and other
"cog'iate" fields. Their practitioners are not concetned with
producing pure and distinctive forms of information. In this
context, the applied fields are composed of both sciences and
arts that are designed to explain phenomena and solve
problems in the practical aspects of the human situation. For
example, the applied field of knowledge called "medicine” is
composed of the medical sciences and medical arts.
Engineering of the engineering sciences and the engineering
M8. ‘

90

Although much of the knowledge produced by academicians
in their disciplines and professionals in their "fields” is
frequently beyond the comprehension of persons outside the
specializations in question, and although this knowledge may
appear at times to have little relevance to the immediate
concerns of persons not committed to it by affiliation with
these specializations, there is a great need for at least
knowing about the structures and functions of such bodies
of information. In order to make such information available
to society, clusters of information related to such broad
areas as natural and life sciences, social and behavioral
sciences. humanities, and communications can be formed on
the basis of representative ideas, methods of inquiry
employed, and significant applications of these ideas to
problems extant in the human condition.

The areas of general information provide'a means for
presenting the fundamental disciplines and the applied fields
of knowledge in forms that will allow persons to realize the
essentiality of the: disciplines and fields to their own, and
to contemporary society's ultimate potential and welfare.
The aim of the areas of general information is to present
selected characteristics in logical patterns of the fundamental
disciplines and applied fields to which they pertain. The
organization of ideas included in an area of general
information is based upon making relevant to the education
of any person, rather than to the education of the student
specializing in a given body of knowledge, essential
understandings of the disciplines and fields under
consideration.

Ihe .EUJLQSJOML Sgieqoes provide a mnceptual framework
and scientific language for the applied field of knowledge

"c'illed' .egucatipn. These ”sciences" approach a level of

precision that is found in such other derivative fields as
medicine, pharmacy, engineering and law.

With the development of the Educational Sciences, the
solutions of problems and explanations of phenomena are
facilitated, and educational problems accruing to inadequate
communication, misinterpretation of information, and
fragmentation of effort are alleviated.

in the process of creating and developing the Educational
Sciences, the following assumptions are made:

1) Education is the process of searching for meaning.

2) Thooght is different from language.

3) The human creature is social in nature and has an unique
capacity for deriving meaning from its environment and
personal experiences throum the creation and use of
symbols.

4) Not content with biological satisfactions alone,
humankind continually seek meaning.

These assumptions are essential to the conceptual framework
for education called the Educational Sciences.

At the present time, there are seven educational sciences:
1) Symbols and their meanings
2) Cultural determinants of the meanings of symbols
‘ 3) Modalities of inference-
4) Educational memory
5) Cognitive styles of individuals
6). Teaching styles, administrative styles and counseling
_styles
7) .Systemic analysis decision-making

91

 

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Educational Cognitive Style

Oakland Community College accepts the premise that no
two students seek meaning in exactly the same manner. We
believe that 90% of the students with normal ability can
learn 90% of the material 90% of the time if the teaching
methods and media are adjusted to the student's educational
cognitive style. The College maps the cognitive style of each
student to prOvide a picture of the various ways in which the
individual searches for meaning. Each student has a relatively
unique cognitive style or way of seeking meaning or knowing.
Cognitive styles are determined by the way individuals take
note of their surroundings - how they seek meaning, how
they become informed. Are they listeners or are they readers?
Are they concerned only with their own viewpoints or are
they influenced in decision-making by their families or
associates? Do they reason as mathematicians, or as social
scientists, or as automotive mechanics?

These are but a few examples of the facets of human
makeup that are included in a student's cognitive style.
Family background, life experiences, and personal goals
make each of us unique. Each map reflects each student's
cognitive style. A cognitive map provides a picture of the
diverse ways in which an individual acouires meaning. It
identifies cognitive strengths and weaknesses. This information
can be used to build a personalized program of instruction.

Results from a battery of tests and inventories are processed
through the College's computer system to produce a map of
cognitive traits that describe the many ways each student
might seek meaning. Cognitive maps are printed out in the
form of a cartesian product of three sets. The first set
indicates a student's tendency to use certain types of
symbols, one's ability to understand words and numbers,
Qualitative sensory symbols, qualitative programmatic
symbols, and Qualitative codes. The second set indicates
influences which the student brings to bear in deriving
meaning from symbols. These influences are effected mainly in
terms of one's own individuality (I). or one's associates (A), or
those of one's family (F). The third set indicates the manner in
which the individual reasons, or the way in which one infers.
Whether the individual thinks in categories (M), or in terms of
differences (D), or synthesizes multiple relationships (R). or
uses all three (L). one's modality of inference influences, and
is influenced by, symbols and the cultural determinants that
are employed in that person's style. These three sets of
elements, i.e., symbolic mediation, cultural determinants, and
modalities of inference, comprise the cognitive style of the
individual. A maximum of 3,260 different profiles of these
elements are possible in an individual's map at a given level of
educational development.

Major Orientation/Minor Orientation

Major orientation is noted by capital letters. For example,
TlVL) would indicate a major orientation in theoretical
visual linguistic symbolic mediation. A major orientation is
accorded a given element if it OCCurS in the 50th-99th
percentile range of a distribution of that element at a given
“developmental" level. The person showing a TlVL) in the
cognitive style map at, say, the twelfth level of educational
development w0uld have realized a score which occurred
somewhere within the range of the SOth—99th percentiles of
the distribution of that element, TWL), for persons at a
twelfth level of educational development.

The symbol T'(AL), read "T prime AL", indicates a minor
orientation in this element of style. If T'lAL) were indicated
in an individual's cognitive style map, it would mean that the
individual had realized a score for this element that occurred
in the range of the 26th-49th percentiles, inclusively, of a
distribution of scores for that element at a given level of
educational development.

If an individual realized a score that occurred at the 25th
percentile or below of a distribution of scores for a given
element, at a given level of educational development, that
individual would be said to have a negligible orientation and
the symbol for that element would be omitted from the
individual 's cognitive style map.

I. SYMBOLS AND THEIR MEANINGS

Two types of symbols, theoretical (e.g., words and numbers)
and qualitative (e.g., sensory, programmatic, and codes), are
created and used by individuals to acquire knowledge and
derive meaning from their environments and personal
experiences. Theoretical svmbnls m'm the nervous
system, and then represent to it, something different from
that which they themselves are. For example, the spoken
word "cup” is an auditory sensation which represents to the
individual hearing it the physical object of a cup. Since this
auditory sensation (the sound "cup") presents to the
individual's nervous system something different from that
which it (the symbol) itself is, it is called a “theoretical
auditory linguistic symbol." In the visual dimension, the
imagery resulting from the individual's observing the printed
word ”cup", which wOuld present to the awareness of the
individual the same physical object that the word "cup"
wOuld produce. is an example of theoretical visual linguistic
symbolic mediation.

Qualitative symbols present and then represent to the
nervous system of the individual that which they (the
symbols) themselves are to that individual. Meanings for
Qualitative symbols are derived from three sources: I)
sensory stimuli; 2) cultural codes (games): and 3)
programmatic effects of objects which convey an almost
automatic impression of a definite series of images, scenes,
events or Operations. At the present time, there are 25
qualitative symbols included in the "symbolic" set: five of
them associated with sensory stimuli, ten that are
programmatic in nature, and ten associated with cultural
codes.

There are two main types of theoretical symbols - auditory
and visual - each of which can be divided into linguistic and
quantitative elements. The four theoretical symbols are
defined as follows:

92

TiVL) Theoretical Visual Linguistics - ability to find
meaning from words yOu see. A major in this area
indicates someone who reads with a better than
average degree of comprehension.

Theoretical Auditory Linguistics - ability to
acquire meaning through hearing spoken words.
Theoretial Visual Quantitative - ability to
accuire meaning in terms of numerical symbols,
relationships, and measurements.

Theoretical Auditory Quantitative - ability to find
meaning in terms of numerical symbols,
relationships, and measurements that are spoken.

TlAL)

TWO)

TlAQ)

The five qualitative symbols associated with sensory stimuli
are:
QlA) Qualitative Auditory - ability to perceive meaning
thrOugh the sense of hearing. A major in this area
indicates ability to distinguish between sounds,
tones of music, and other purely sonic sensations.
Qualitative Olfactory - ability to perceive meaning
through the sense of smell.

Qualitative Savory —- ability to perceive meaning
by the sense of taste. Chefs shOuld have highly
developed qualitative olfactory and savory abilities.
Qualitative Tactile — ability to perceive meaning
by the sense of tooch, temperature, and pain.
Qualitative Visual - ability to perceive meaning
tl'erugh sight.

0(0)

0(5)

OlT)

ON)

The qualitative symbols that are programmatic in nature are:
OlPF) Qualitative Proprioceptive (Fine) - ability to
synthesize a number of symbolic mediations into a
performance demanding monitoring of a complex
task involving small, or fine, museulature (e.g.,
playing a musical instrument, typewriting); or into
an immediate awareness of a possible set of
interrelationships between symbolic mediations,
i.e., dealing with "signs." While qualitative
prOprioceptive fine symbolic intelligence is most
readily observable in seemingly automatic motor
responses such as reading and playing music.
certain types of theoretical symbolic mediation
also require qualitative proprioceptive activity. For
example, the synthesis of a number of symbolic
mediations is evident when an individual upon
seeing a sign of smoke immediately interprets it as
evidence of fire and experiences an interplay of
many sensations including smell of smoke, taste of
smoke, and sensation of heat. In this instance a
network -of previous experiences and related
associations produces the theoretical mediation of
fire along with the other qualitative aspects.
Qualitative Proprioceptive (Gross) - ability to
synthesize a number of symbolic mediations into a
performance demanding monitoring of a complex
task involving‘large, or gross, musculature (e.g.,
throwing a baseball, skiing).

Qualitative Proprioceptive Dextral (Fine) - a
predominance of righteyed, right-handed and
right-footed tendencies (a typically right-handed
person) while synthesizing a number of symbolic
mediations into a performance demanding
monitoring of a complex task involving small, or
fine, musculature (e.g., writing right-handed).

OlPG)

OlPOF)

Q(PDG) Qualitative Proprioceptive Dextral (Gross) - a
predominance of right-eyed, right handed and
right~footed tendenCies (a typically righthanded
person) while synthesizing a number of symbolic
mediations into a performance demanding
monitoring of a complex task involving large, or
gross, musculature (e.g., throwing a baseball with
the right hand).

Qualiutive Proprioceptive Kinematics (Fine) —-
ability to synthesize a number of symbolic
mediations into a performance demanding the use
of fine museulature while monitoring a camplex
physical activity involving motion. _
Qualitative Proprioceptiva Kinematics (Gross) -
ability to synthesize a number of symbolic
mediations into a performance demanding the use
of gross musculature while monitoring a complex
physical activity involving motion.

Qualitative Proprioceptive Sinistral (Fine) - a
predominance of lafteyed, Ieft~handed and
left-footed tendencies (a typically Iefthanded
person) while synthesizing a number of symbolic
mediations into a performance demanding
monitoring of a complex tadt involving small, or
fine, musculature (e.g., writing left-handed).
Qualitative Proprioceptive Sinistral (Gross) - a
predominance of left-eyed, left-handed and
left-footed tendencies (a typically left-handed
person) while synthesizing a number of symbolic
mediations into a performance demanding
monitoring of a complex task involving large, or
was, musculature (e.g., throwing a baseball with
the left hand).

Qualitative Proprioceptive Temporal (Fine) -
wility to synthesize a number of symbolic
mediations into a performance demanding the use
of fine musculature while monitoring a complex
physical activity involving timing.

Qualitative Proprioceptive Temporal (Gross) -
ability to synthesize a number of symbolic
mediations into a performance demanding the us
of gross musculature while monitoring a complex
physical activity involving timing.

QlPKF)

QlPKG)

Q(PSF)

QlPSG)

Q(PTF)

Q(PTG)

The remaining ten qualitative symbols associated with
cultural codes are defined as:

Q(CEM) malitative Coda Empathic - the capacity to derive
meaning through sensitivity to the feelings of
others: ability to put yOurself in another person's
place and see things from that person's point of
view.

mess) Qialitativa Code Esthetic — capacity to enjoy the
beauty of an object or an idea. Beauty in
surroundings or a well-turned phrase are appreciated
by a person possessing a major strength in this area.
QlCET) Qualitative Coda Ethic - commitment to a set of

values, a group of principles, obligations and/or
duties. This commitment need not imply morality.
80th a priest and a criminal may be committed to
a at of values although the “values" may be
decidedly different.

93

QlCH) (hialitative Code Histrionic - capacrty to exhibit a
deliberate behawor, or play a role to produce some
particular effect on other persons. This type of
person knows how to fulfill role expectations.
Qialitatlve Coda Kinetics - capacnty to understand,
and to communicate by, non-lingUistic functions
such as facial expressions and motions of the body
(e.g., smiles and gestures).

Qualitative Code Kinesthetic - capacity to perform
motor skills, or effect muscular coercination
according to a recommended, or acceptable, form
(e.g., bowling according to form, or golfing).
Qualitative Code Proxemics - capacity to judge the
physical and social distance that the other person
wOuld permit, between oneself and that other
person.

Qialitative Code mnnoetica - capacity to have
personal knowledge of oneself.
Qialitative Code Transactional —
maintain a positive communicative interaction
which significantly influences the goals of the
persons involved in that interaction.

Qualitative Code Temporal - capaCity to respond or
behave according to time expectations imposed on
an activity by members in the role-set assocmed
with that activity.

Q(CK)

QlCKH)

Q(CP)

Q(CS)

QlCT) capacity to

QiCTM)

ll. CULTURAL DETERMINANTS

There are three cultural determinants of the meaning of
symbols: 1) individuality (l). 2) associates (A). and 3) family
(F), It is thr0ugh these ”determinants" that cultural
influences are brought to bear by the individual on the
meanings of symbols. The ”individuality“ influence is
freQuentIy reflected by the individual's need to quote
definitions, or explain situations, in his own words. The
”associates" influence is frequently evidenced by an
individual who understands that which is under
consideration, but explains or discusses these matters mainly
in the words of his associates who may be involved with him
in the situation. The "family" determinant is frequently
portrayed by the individual possessing it through examples
one may use in explaining a situation or solving a problem
(e.g., either parents, children, wife, husband, sibling, causin,
close friend, etc., are used to illustrate a situation analogous to
the one under consideration).

Ill. MODALITIES OF INFERENCE

The third set of the Cartesian product indicating cognitive
style includes elements which indicate the individual‘s
modality of inference, i.e., the form of inference one tends to
use:

M Magnitude - a form of "categorical reasoning" that
utilizes norms or categorical classifications as the basis
for accepting or rejecting an advanced hypothesis.
Persons who need to define things in order to
understand them reflect this modality.

0 Difference - This pattern suggests a tendency to
reason in terms of one-toone contrasts or comparisons
of alected characteristics or measurements. Artists
often posses this modality as do creative writers and
musicians.

R Relationship - this modality indicates the ability to
synthesize a number of dimensions or incidents into a
unified meaning, or through analysis of a situation to
discover its c0mponent parts. Psychiatrists frequently
employ the modality of relationship in the process of
psychoanalyzing a client.

L Appraisal — is the modality of inference employed by
an individual who uses all three of the modalities
noted above (M, D, and Pi), giving equal weight to
each in his reasoning process. individuals who employ
this modality tend to analyze, question, or, in effect.
appraise that which is under consideration in the
process of drawing a probability conclusion.

K Deductive - indicates deductive reasoning, or the form
of logical proof used in geometry or that employed in
syllogistic reasoning.

IV. EDUCATIONAL MEMORY

Educational memory is a Cartesian product of three sets of
information pertaining to: l) the memory function, 2)
concern components (persons, processes, properties), and 3)
conditions. The elements of the condition set of information
are: Assimilation (AS), Accommodation (AC), Attendance
(AT). and Repression (BS).

The Piagetian conditions of: 1) Assimilation, i.e., acquiring
"new“ meanings through one's Currently existing elements of
cognitive style; 2) Accommodation, i.e., interiorizing in terms
of the new meanings directly (e.g., understanding a fOreign
language without first needing to translate it into one's own
language): 3) Repression, i.e., repressing or dampening
perseverations interfering with the interiorization processes
(mimiiation, accommodation); and 4) Attendance, i.e.,
concentration of attention on the meanings being acquired.
Assimilation and Accommodation combine with those of
Repression and Attendance. to form the elements, in major
and minor orientations, that comprise information of the
"conditions“ set of educational memory. Assimilation is one
of two processes of interiorization outlined by Piaget.
Accommodation is the other condition of Piagetian
interiorization. The processes of Repression and Attendance
are the other two elements included in the condition set.

Educational memory is an essential aspect of an individual's
cognitive style. Recent work by biochemists and
psychobiologists provides information by which the memory
function can be expressed in terms of selected biochemical
elements and the electrophysiological measurements of alpha
(a). beta (3). theta (6), and delta (6), waves,
respectively. The concern components of Persons (PN).
Processes (PS), and Properties (PT), respectively, are
considered to contribute to the biochemical elements
produced by memory activity and conditions reflected in the
electrophysiological measurements, i.e., a, ﬂ , 6 ,
and 6 . For example, some individuals find it easier to
remember persons (PN), thereby expending less ener9V (a
major orientation indicating a condition of potential energy,
or “easy" memory) in the memory activity than they wOuld
for, say, remembering processes. (PS). Situations in which
individuals witness difficulty in exercising the process of
memory are indicated by a negligible orientation (i.e..the
element is not shown in the map) in either one or a
combination of the processes of recognition, retention, recall
and association. The minor orientation is used to indicate a

94

condition of "neutral energy expenditure" in one, or in a
combination of the faur processes of memory, when
specimens of body fluids show an average count of residuals of
biochemical elements considered to be at work in
memory-concern activity.

Recent work by biochemists and psychobioiogists
differentiates between short-term and long-term memory.
Short-term memory must be present, however, before
long-term memory can occur. Short-term memory may
become long-term memory With the production of proteins
and an increase in enzymatic activity levels in the brain cells.
Short-term memory is currently thought to be the result of
short~|ived processes. -

Recent experiments with animals have shown that injection
of stimulators into the central nervous system can have an
affect on both short-term and long-term memory,
respectively. Differential effects on membry resulting from
chemical injections have also been observed between human
subjects. implications for education in the future might well
lie in the use of immediate memory stimulators and other
chemicals to increase the attention span and decrease protein
elements which inhibit the memory-concem function.

V. EDUCATIONAL COGNITIVE STYLE

The Educational Science of Cog-iitive Style combines the
information included in the first four "sciences," by means
of a Cartesian product of these faur sets, to provide a picture
of the profiles distributed over the four sets that an
individual employs in seeking meaning. These profiles reflect
the cognitive style "strengths" of the individual, and are
vehicles for determining educational prescriptions to help
him in the educative process.

At the present time, individuals are being tested and
inventoried for elements included in the first three sets only,
i.e., symbols and their meanings, Cultural determinants, and
modalities of inference. Instruments for collecting
information relative to the Educational Memory set are
currently under construction.

VI. COUNSELING,ADMINISTRATIVE,
TEACHING AND STUDENT STYLES (CATS)

Each of these three styles is represented bya Cartesian product
of three sets of information pertaining to: l) Demeanor. 2)
Emphasis. and 3) Symbolic Modes of Presentation, or
Communication.

Demeanor x Emphasis is Symbolic Mode
Elements in the emphasis set and the symbolic modes set,
respectively, are common to each of the three styles.
Differentiation between an individual‘s teaching style, his
munseiing style and his administrative style in the:
dimensions ("emphasis" and ”mode") is affected thrOugh the
change in orientations (major and minor) that might occur
with each style. For example, an individual may show a
major orientation in processes (P5) in his teaching style
while indicating a major orientation in persons (PM) in his
administrative style.

Counseling Style

The cognitive style of indivrduals involved in counseling
situations, as in the case of teaching and administrative
styles, is important but does not prowde a total explanation
of the behaVior of counselors. The demeanor elements of
counseling style expressed in terms of major and minor
orientations involving: a) Directive (V,v). b) Situational (U,u),
or c) Nondirective (0,0) are determined on the basis of the
counselor's attitude toward who shOuld set the goals and
determine the approaches to the goals in the coonseling
situation. The caunselor who reflects "my goals my way,"
rqardless of the counseling situation, is given a major
orientation in the directive element in the demeanor set.
Counselors who are at times directive and at other times
nondirective, depending upon the situation, are accorded
major orientations in the situational element. Caunselors who
tend not to direct behawor, regardless of the counseling
situation, are accorded major orientations in the nondirective
element. The total counseling style of an individual is
expressed in terms of profiles showing major and minor
orientations distributed over the three sets of demeanor,
emphasis and "symbolic mode." An example of counseiing
style is shown below:

{viii-xiii.)

Administrative Style

Major and minor orientations in four elements of demeanor:
1) Dominant (Np). 2) Adjustive NJ), 3) Cooperative lC.cl and
4) Passive Custodial (Xx); major and minor orientations
combined in the "emphasis elements": Persons (PM), Processes
"’25). and Properties (PT): along with major and minor
orientations in the elements of Symbolic Mode lOP, RP, TP).
are profiles that portray the administrative style of an
individual. The dominant (N) administrator reflects a ”my
goals my way” approach, the adjustive (J) type reflects “my
goals yOur way, or yOur goals my way" approaches; the
cooperative (C) employs a demeanor of "our goals our way“;
while the passive custodial demeanor is one resulting from a
"your goals y0ur way" approach to administration by the
individual. An example of administrative style is shown

is) in ii: }

Teaching Style

The demeanor set of teaching style includes three elements: 1)
Hedominant (P. l; 2) Adjustive or ”Switcher" (83 p.) and 3)
Flexible (8”,)1Phese three demeanor classifications can occur
as either a major orientation in one with minor Orientations in
the other two, or two major orientations with a minor in the
remaining element. Each of these elements is subscripted as
authoritarian la) or permissive in). An authoritarian type is an
individual who respects the wishes and decrsions of persons in
superordinate positions relative to his own, and expects his
wishes and decisions to be respected when he assumes the
superordinate role. A permissive individual is one who does
not exercise this "respect," and does not expect it to be
exercised by others regarding his role. The orientations in the

9S

demeanor set are combined with those of the emphasis and the
“symbolic mode" set (OP-Qualitative Predominant;
PIP—Reciprocity; TP-Theoreticel Predominant) to form
profiles indicating the teaching style of an individual. An
example of a teaching style represented by a Cartesian product
is shown below:

in {2;} ii»)

STUDENT STYLE

Student style is described as a Cartesian product of the three
sets of: demeanor, emphasis, and symbolic mode of
presentation. The elements comprising the latter two sets,
emphasis and symbolic mode, are as previously described in
connection with ocunseling, administrative, and teaching
styles, respectively. The elements included in the demeanor set
of student style are: l) lnnovator llN), that student demeanor
in which the individual will employ any means to attain the
goal (understanding); 2) Retreatist lRRl, that student
demeanor portrayed by the individual who is indifferent to the
means of instruction employed, and is also indifferent to the
goal, i.e., understanding that which is being taught: 3) Ritualist
(Bl), that student demeanor in which the individual
participates thoroughly in the “ritual" (instructional
approach) in order to receive a good grade, but does not truly
accept the goal, i.e., to understand that which is being taught;
and 4) Rebel (R8), that student demeanor in which the
individual alternately accepts, rejects, accepts and rejects both
the means and the goal of instruction. An example of student
style is shown below:

{WNW}

Vll. SYSTEMIC ANALYSIS DECISION-MAKING

A system is a defined collection of elements with their
interconnections considered over a period of time. Any
aspect of education may be considered as a system.

The basic purpose of systemic analysis is decision-making
resulting in a choice of options available to the
decision-maker. Analysis of a system is conducted in terms
of determining how well the goals of a system are being met
within the constraints of the inputs of the system, combined
with considerations of its mission and the main functions
(design criteria) around which the system is designed.

Performance goals must be stated in terms of the tasks to be
accomplished, the conditions surrounding the tasks, and the
minimum performance needed for successful accomplishment
of the tasks. Any system may be defined, and analyzed, by
means of the analogue model shown on next page.

For example, an educational program can be defined as a
social system of the three generic elements: persons,
processes and properties, and their interconnections
considered ever a period of time. This system can be defined
by composing a mission statement for it, stating its desigi

m

9

 

 

HUMAN F EEDBACK Cl RCUITRY

ANALOGUE MODEL FOR SYSTEMS ANALYSIS

 

[MISSION STATEMENT (STRUCTURES AND FUNCTIONS)]

 

J,

 

 

GENERAL OBJECTIVES OF PROGRAMS

 

 

 

E'iii‘liiii" H‘O DESIGN

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SUMMARY OF THE EDUCATIONAL SCIENCES

Educational Sciences are summarized in the diagram shown

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criteria, structuring performance goals for each criterion, and
determining the inputs (persons ani properties) necessary for
achieving the tasks stated in the performance goals of the
system.

The Output: of a system are measurements of performances
of persons, processes, and properties Within the system as
support functions (support variables), and as measurements
and products resulting from the performance of these three
elements toward fulfilling the mission of the system (impact
variables).

ThrOughom the period of operation of the system
infermation is placed in the human feedback Circuitry
eIement, through meetings and conversations, in Order to
make decisions regarding possible modifications of elements
and/or their interconnections to keep the system adiusted to
its internal and external environments. The ultimate
objective of systemic analysis is that of deriving optimal
decisions, i.e., deCisions that are "best” for all elements
included in the decision. It should be noted that Optimal
decisions are not always "perfect" for each of the elements
affected by the system.

PERSONALIZED EDUCATION

A student's cognitive map presents a picture of the variety of
profiles one uses in his education, i.e., that one uses in the
search for meaning. Mapping an individual’s cognitive style
enables the educator to consider the individual in terms that
wrthOut the map he or she might not have employed. The
diagnosis of an individual's cognitive style and the modes of
understanding required by an educational task can be used to
match the student to the task. Through this approach it is
possible to prescribe educational actiwties that previde a
better probability of successful accomplishment by the
individual than otherwrse might be possmle.

97

98

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

WITH . 33‘3"“
“:5 2;..-) Flow Chart of Personalized Educationai Progam (PEP) IIIustrating Student Progress
I. «r. l = From Diagnostic Testing ThrougII Successful Completion of an Instructional Unit.
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PE RSONALIZI NG E DUCATIONAL PROG RAMS

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UTILIZING COGNITIVE STYLE MAPPING

 

mama 0R. JOSEPH E. HILL, PRESIDENT
$ﬁggg‘m’ 0R. DEREK N. NUNNEY, VICE PRESIDENT

COPYRIGHT, FEBRUARY, 1971

 

 

 

 

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APPENDIX B

TWELVE COGNITIVE STYLE MODELS

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APPENDIX C

EDUCATIONAL COGNITIVE STYLE INTEREST INVENTORY

106

DRIVER EDUCATION STUDY

EDUCATIONAL COGNITIVE STYLE
INTEREST INVENTORY

used with permission of

Dr. Joseph Hill
Oakland Community College

DIRECTIONS

Use pencil, not pen.

Fill in your Social Security number under STUDENT
NUMBER (if you have one).

Each item is to be answered usually (U), sometimes
(S), or rarely (R) on the answer sheet provided.
Read the first question on page 1.

Decide if this statement is like you usually,
sometimes, or rarely.

Darken U or g or R for question 1. Be
careful to cover the letter (9, S, or R) and
to stay inside of the brackets. — _

Read and make decisions rapidly - consider your
first answer to each question to be correct.

You may now begin (CAUTION! Frequently check
the number of the question you are reading with
the number on the answer sheet).

 

 

107

10.

23M:

After I write a letter, I ask
someone to read it aloud to me
so that I know how it sounds.

When taking courses in
mathematics, I find it easy
to "talk in formulas" with
my classmates and teacher.

I score high on achievement
tests which depend upon
reading comprehension.

When I am in a group of people
trying to solve a written
problem involving numbers, I
am among the first to reach
the correct solution.

My written explanations are
more understandable than
my spoken ones.

People say I speak more
understandably than I write.

I prefer classes which rely
heavily on textbooks for
information.

I use a written budget to
account for money for which
I am responsible.

I prefer the traditional lecture
type classes.

I can make more sense out of
what a person means when he
speaks to me rather than if
he writes to me.

II II II

Usually
Sometimes
Rarely

ll.

12.

l3.

l4.

l5.

l6.

l7.

l8.

I9.

20.

108

I prefer maps to verbal
directions when I am going
to a strange place.

I do better on a test if it
is about information I have
heard rather than read.

If I were buying a bicycle, I
would ask the salesman to
write out the cost, service,
and what comes with it.

I understand the daily news
better if I hear it on the radio
rather than if I read it in the
newspaper.

I discuss "sale" prices with
others before I go shopping.

I can remember a telephone
number once I have heard it.

I find it necessary to write
down a telephone number as
soon as I hear it in order
to remember it.

I communicate with friends

and colleagues by telephone
rather than by writing messages
to them.

I prefer to read a newspaper
myself rather than have some-
one read it aloud to me.

I prefer to to follow verbal
directions rather than
written directions.

2].

22.

23.

24.

25.

26.

27.

28.

29.

30.

I prefer to read directions
rather than have someone
interpret them to me.

Verbal mathematics tests are
easier for me than written
mathematics tests.

When I go shopping, I read
the price of each item and
keep a running total in my
head.

I quote statistical data to others
in order to prove my point in
an argument.

I find it comfortable to add
spoken or dictated numbers
mentally.

I understand more easily
when I read information rather
than when I hear it.

I achieve best on written
mathematics tests.

After I tell someone how to
do something, I read their
notes to be certain they are
correct.

It is easy for me to remember
the numbers and formulas I
have heard during a conversation.

I keep written records of the money
I get and the way I spend it.

109

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

If I were buying a bike I
would discuss cost, service,
and what comes with it with
the salesman or a friend.

I solve mathematical problems
more rapidly if they are
written.

I can identify music well
enough to recognize a "tune"
the next time I hear it.

I can tell "what's for dinner"
by the smell when I enter
the house.

When I tune a musical
instrument, I use the piano
or another source for the
correct pitch.

My "suffering" in the dentist's
chair is alleviated if he uses
pleasant tasting materials in
my mouth.

I can feel the difference
between leather and metal.

A narrative is easier to under-
stand in a movie than in a
book.

I can tell if something is
wrong with an engine by
listening to it run.

Any unpleasant smell is more
disturbing to me than to others.

41.

42.

43.

44.

45.

46.

47.

48.

49.

50.

When I ride a bike, I look ahead
rather than at the handlebars.

I can recognize who is on the
phone just by listening to the
voice for a few moments.

I prefer furniture that I enjoy
running my hand over.

I prefer to read articles
which are illustrated by
pictures or drawings.

I enjoy trying new foods in
order to find new tastes that
I may like or wish to learn
to like.

The tone or inflection of a
speaker's voice gives additional
meaning to his words.

I tune the radio by sounds not
by the numbers on the dial.

I can write legibly as another
person dictates to me.

The "smell" is an important
component of the pleasure
connected with a new car.

In selecting a beverage, my
choice is based on taste.

110

SI.

52.

53.

54.

55.

56.

57.

58.

59.

60.

I can catch a ball that has
been struck or thrown.

I return to a restaurant
because of the taste of the
food served there.

I can play ping pong well
enough to enjoy it.

Random sounds interfere with
my ability to concentrate on
a conversation or on reading.

The taste of food is more
important than its appearance.

I am certain that the customary
smell of a store influences its
sales volume.

I pick up and feel vegetables
and fruits in the store before
buying them.

When I tune a radio I use the
numbers on the dial.

I can tell the difference between
two closely pitched sounds.

Blindfolded, I can taste the
difference between chocolate
and coffee ice cream.

61.

62.

63.

64.

65.

66.

67.

68.

69.

70.

7l.

I decide that my hair needs
washing by the way it feels
when I touch it.

I have been told that I am
a good dancer.

I enjoy looking at art work.

I am considered to be a
"good” amateur athlete.

I prefer to write with a pen
that "fits" my fingers.

I can distinguish fresh fruit
from stale fruit by the smell.

I use my fingers to supplement
my eyes to determine the
quality of the finish on wood.

I am able to tell which
instruments are playing at
various times during a
concert.

When eating, I use different
spices until the food tastes
"right".

I choose clothes for the way
they look on me.

I can distinguish a nickel
from a dime in my pocket
with my fingers.

Ill

72.

73.

74.

75.

76.

77.

78.

79.

80.

BI.

I can distinguish between
several varieties of flowers
by smelling their blooms.

When there are gas fumes in
the car or the house, I notice
them sooner than others do.

I can tell if milk is sour
by tasting it.

I understand a teacher.
better if I can look at him
as he talks.

The aromas in a room determine
for me whether it is a pleasant
or an unpleasant place.

I "think" in pictures and
graphic models rather than
in words and phrases.

I can button my coat in the
dark.

When I walk downstairs, I
look ahead rather than at my
feet.

I feel better acquainted with
some one if I see a picture
of him rather than if I read
about him.

I laugh with the person who laughs
when he stubs his toe because I
know it hurts yet he is too old
to cry when he is clumsy.

82.

83.

84.

85.

86.

87.

88.

89.

90.

91.

92.

93.

Utility and efficiency are important

but they should not be emphasized
to the exclusion of beauty.

I work just as hard whether or
not my teacher or parents are
there.

I am a good actor in plays.

I shrug my shoulders when saying
"I don't know”.

I try not to say things which hurt
the feelings of others.

I enjoy the sight of people dancing.

I would stop for a "STOP” sign any
time even if there were no other
person in sight.

When someone is frightened, I can
be patient and calm rather than
reply in anger.

I blush in situations where many
others do not.

I can give the impression that I
am happy and comfortable even

though I am angry and uncomfortable.

I am able to offer criticism
without offending others.

I greet a late arriving guest
enthusiastically.

112

94.

95.

96.

97.

98.

99.

100.

lOl.

l02.

103.

l04.

l05.

The values of our society are
good for everyone.

I require beauty in my
surroundings outside as well
as inside buildings.

I am able to "play a role"
anywhere if I agree to.

I direct my life according to
moral values.

I can pretend to be attentive
and interested even though
bored when listening to a
teacher or supervisor.

I would not agree to cheat if
I were offered a bribe.

My friends tell me that I am
understanding.

I can act friendly and accepting
in order to acquire favors.

I enjoy the author's writing style
as much as the story he tells.

Eye movements are important
supplements to my conversation.

I “feel" the emotions of others
as they do.

I can successfully adjust my
behavior (formal or informal)
according to the situations.

106.

107.

108.

109.

110.

111.

112.

113.

114.

115.

116.

117.

I use facial expressions to
communicate emotions.

I would give up something I want
to do now rather than sacrifice
one of my values.

I do not permit personal affairs
to interfere with completing an
assignment.

I "talk with my hands” more
than others do.

I enjoy listening to music when
the quality of its sound is good.

Walking with a spring in your
step gives the impression that
you are happy.

I understand how a person feels
when he is being punished.

I can give the impression that I
am calm and comfortable even though
I am angry and uncomfortable.

I would go out of my way to
see beautiful scenery.

When I shake hands with someone,
the handshake tells me how
sincere the person is.

I enjoy the beauty of a well-
designed structure.

I enjoy telling jokes and stories
at a party.

113

118.

119.
120.
121.
122.
123.
124.,
125.

126.

127.

128.

129.

Poetry is beautiful because of its
concepts as well as its words
and rhythm.

I interpret a person's mood by
the way they sit or stand.

I believe that a promise should
be kept.

When I engage in sports, I
practice or warm-up first.

If I attempted to kiss someone,
I would not be slapped.

I can predict my responses in
many situations.

I can bring a group to some

- agreement.

I can tell when I am just
about to blow my cool.

To become a good typist, I
would practice correct finger
movements.

I can predict accurately how
successful I will be in a new
situation.

Sales people find the merchandise
that I am asking for.

I have practiced handwriting skills
so that I write legible now.

130.

131.

132.

133.

134.

135.

136.

137.

138.

139.

I am better coordinated than
most people.

I predict accurately if I will
be able to get my work done.

When learning a new dance,

I am willing to practice the
steps until I can do them
perfectly.

In social situations I am able
to verbally stop arguments
involving others before they
go too far.

When it is necessary, I can
repair objects without watching
my hands.

I wait for an invitation to be
seated in making a call on a
supervisor in his office.

I prefer to ask favors of close

friends rather than from teachers.

Peers involve me in resolving
problems.

Learning to throw a ball the
right way is important.

I complete my assignments because
I don't "bite off more than I
can chew".

114

140.

141.

142.

143.

144.

145.

146.

147.

148.

149.

150.

I have enjoyed acquiring good
motor skills so that I compete
successfully in sports.

I accept criticism without feeling
resentful.

I request permission before taking
a seat near a stranger.

In group discussions, I assume
the leadership to move the
group to reach a decision.

I would wait to be introduced
to a famous person rather
than introduce myself.

First names are good if the
other person prefers first names.

I know my strengths and
weaknesses.

I am able to persuade people
involved in disagreement to
strive for agreement.

I know the physical energy that
a particular task will require
for me to complete it.

I do not borrow money from strangers.

I can convince others to willingly
do the things that I would like
them to do.

151.

152.

153.

154.

155.

156.

157.

158.

159.

160.

161.

162.

163.

Unless spoken to first, I do
not speak to a teacher.

I am able to put people at
ease in tense situations.

I make it a point not to let my
work interfere with family plans.

I enjoy activity more if my

friends participate in it with me.

When given a job to do, I
prefer to do it myself.

When shopping for clothes, I
prefer having a friend along
to help me make choices.

I make my own political choices.

I consult with my immediate
family before making decisions.

After gathering data from many
sources, I make decisions alone.

Family values should have
lasting effects on each of us.

I like to share ideas with
friends and associates.

I enjoy outdoor activities
when I am with my family.

One's religion is purely a
personal decision.

115

164.

165.

166.

167.

168.

169.

170.

171.

172.

173.

174.

175.

I make personal decisions
after discussing them with
my friends.

I talk with my family before
doing anything that might
affect them.

Before taking a new job, I
would discuss it with my
friends.

When given a problem to
solve, I find the answer
myself.

I prefer to study on my own.

I find it important to talk
things over with my family.

I am influenced by my friends
political opinions.

I understand events better
after discussing them with
my family.

I do not need others to help
me make decisions.

I would join a religious group
if my friends belonged to it.

I learn a subject better when
I can discuss it with my
associates.

Before voting in an election
I review the candidates with
my family.

176.

177.

178.

179.

180.

181.

182.

183.

184.

185.

186.

I would rather do things my
way even if this does not
conform to the expectations
of my family and friends.

I can use jokes and humorous
remarks to change the focus
in many situations.

I find myself in the position
of having to make a decision
before I know enough about
the situation.

I do not change my mind on a
subject once I identify the
rule which applies.

I work best in an organized
or structured situation.

I like to see several examples
before starting a new project.

I understand geometric theorems.

I understand a topic better if
I analyze it to learn how it
differs from other topics.

The more information you collect
about a problem, the better your
solution will be.

I have no sympathy for people
who break the law.

Characteristics for successful
people are not the same as those
for unsuccessful people.

116

187.

188.

189.

190.

191.

192.

193.

194.

195.

196.

197.

Knowledge flows logically
from given premises.

I would find it interesting to
discover how people behave

by evaluating things which
make people tick (e.g.,
physiological, sociological,
and psychological).

I choose music that contrasts
with my mood in order to
control my feelings.

Holidays are different from
other days of the year.

Life is simple if you go by
the rules.

The more I know about a problem,
the more I want to know about it.

I like essay questions on
examinations.

When shopping for clothes, I
buy without further comparison
if I find the article I had in
mind.

I prefer to be offered more than
one choice.

In recreation as well as work and
life in general, I find it essential
to "play by the rules".

I "play the devil's advocate"
with people to force them to
look at another point of view.

198.

199.

200.

201.

202.

203.

204.

205.

206.

207.

I try to understand why
people break rules.

A person can never know
enough about the universe.

I find it easier to win an
argument when I state a
premise and give a con-
clusion that must be true.
(This is a circle so the 2
formula for the area is 'ITr

).

In evaluating the performances
of others, I find it helpful
to determine how this perform-
ance differed from a previous
performance.

There is always a reason
for a person's behavior.

I find the type of reasoning
demanded by the rules of
mathematics suits my mode
of thinking.

I prefer working in situations
where standards and rules
are stated explicitly.

In evaluating the performances
of others, I find it important
to determine the standards
which were set for them.

I enjoy the way math makes
me think.

I take longer than others in
coming to a conclusions because
I want to know more about an

issue than most other people do.

117

208.

209.

210.

211.

212.

213.

214.

215.

216.

I enjoy games or puzzles in
which the solution is deduced
from information contained

in the rules.

In my choice of clothing, I
wear contrasting colors.

When looking at something
constructed by someone else
(a painting, a building,
furniture) I like to figure
out why the person created
it as he did.

Information should be analyzed
in a number of ways before a
conclusion is reached.

I like the kinds of problems
that have definite answers.

One cannot appreciate a problem
unless he knows as much about
it as possible.

I have no difficulty in under-
standing how to put puzzles
together.

When I attack a problem, I
approach if from as many
aspects as possible.

I find reasoning like this
statement helps me to
clarify my thought:

I'All men are mortal;
Socrates is a man;
Therefore, Socrates
is mortal."

217.

218.

219.

220.

221.

222.

223.

224.

118

I recognize the appropriate
time to end a telephone
conversation.

My friends can depend upon me to do
something on the agreed upon time.

I know when to offer my opinion during
a group discussion.

I can judge which hostess will appreciate
guests who arrive late.

I hand in my homework on time.

I can select the time when a group will
welcome my joining them.

I finish tests in the allotted time.

I meet agreed upon deadlines.

APPENDIX D

SAMPLE COMPUTER PRINTED

COGNITIVE STYLE MAPS

119

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APPENDIX E

DISSERTATIONS DIRECTLY RELATED

TO THE EDUCATIONAL SCIENCES

122

APPENDIX E
DISSERTATIONS DIRECTLY RELATED TO THE

EDUCATIONAL SCIENCES

Baecher, Richard E. "An Exploratory Study to Determine
Levels of Educational Development, Reading Levels,
and the Cognitive Style of Mexican American and
Puerto Rican American Students in Michigan." 1974.

Bartch, Dale E. "An Examination of the Implementation of
a Program Planning Budgeting System in a
Community College." 1970.

Bartman, Leroy R. "An Empirical Analysis of a Standardized
Inventory of Vocational Maturity in Terms of
Educational Cognitive Style." 1974.

Basco, Claire Y. "An Exploratory Study Employing the
Educational Sciences of Cognitive Style for
Students with Impaired Decoding Skills." 1974.

Bass, Ronald K. "An Exploratory Study of Procedures for
Measuring and Mapping Qualitative Symbolic

Orientations." 19721

Beleutz, John A. "Cognitive Style as an Indicator of
Possible Success in Mastering Computer Programming."
1975.

Berke, George B. "Cognitive Style as a Teaching Aid."
1976.

Berman, Bennett H. "A Study of the Self—Actualizing
Characteristics in Cognitive Style of Participants
in a Substance Abuse Rehabilitation Program."

Blanzy, James. "Cognitive Style as an Input to Mathe-
matics Curriculum Systems and Exploratory Studies
in the Educational Sciences." 1970.

Blosser, Charles R. "A Pilot Study to Explore the Rela-

tionships between Cognitive Style, Need Achievement,
and Academic Achievement Motivation." 1971.

123

124

Brodbeck, Ned A. "Influence of the Degree of Match
between Counselee and Counselor in Terms of
Educational Cognitive Style and Counseling Style
on the Objectives of the Educational Counseling
Situation." 1974.

Carter, Margery C. "Exploratory Assessment of 'Average'
Students in Selected English Classes in the
Detroit Public School System." 1966.

Chiakmakis, Ernest J. "A Proposed Model for a Conference
and Institute System in a Community College.“
1971.

Ciccoretti, Emil A. "Developing Personalized Educational

Prescriptions for Fourth Grade Reading Groups
Employing Analysis of Educational Cognitive
Styles." 1976.

Comer, John C. "A Diagnostic Work Sample Instrument for
Assessing Automotive Trade Competence." 1970.

Cotter, Jude T. "The Affects of Educational Science of
Cultural Determinants of the Meanings of Symbols
on Curricular Choice." 1970.

Covello, Leonard V. "Embodiment of Feeling: A Non-
Experimental Study of the Equivalence between
Selected Forms of Affect and Educational Cognitive
Style." 1976.

Crowe, Kathleen P. "A Comparative Analysis of Selected
Vocational and Educational Programs in Terms of
Educational Cognitive Style, to Determine if Sex
Bias Exists." 1974.

DeLoach, Joseph F. "An Analysis of Cognitive Style
Disparity as an Antecedent of Coqnitive Dissonance
in Instructional Evaluation: An Exploratory Study
in the Educational Sciences." 1969.

DeNike, Lee. "An Exploratory Study of Cognitive Style as
a Predictor of Learning from Simulation Games."
1973.

Donahue, Larry P. "A Comparison of Three Methods of
Matching Students in Learning Cells." 1975.

Dworkin, Leo. "A Systems Theory Approach toward the
Reconceptualization of Curriculum." 1969.

125

Eaton, Judith S. "A Model for Educational Cognitive Style
Based upon a Paradigm for Psycho—historical Inquiry,
with Emphasis on Educational Memory." 1975.

Eisenman, Charles D. "An Exploratory Study of Conflicts in
Role Expectations in Administrative Role-Sets
Based upon Cognitive and Administrative Styles."
1973.

Ervin, Thomas D. "The Human Element in the Establishment
and Operation of a PPBS in an Educational Setting
using Role-Sets based on Cognitive and Administra—
tive Styles." 1974.

Fernandez, Richard P. "A Unified Model of Abstract
Thinking in Mathematics and its Corresponding
Model(s) in the "Educational Science of Cognitive
Style." 1974.

Fragale, Marvin. "A Pilot Study of Cognitive Styles of
Selected Faculty Members and Students in a
Community College Setting." 1969.

Frever, William E. "An Exploratory Study of Prescriptive
Instruction in Social Sciences Employing Educa-
tional Cognitive Styles and Systemic Analysis."
1975.

Furse, David H. "An Exploratory Investigation of Audience
Segmentation in Advertising Based on Cognitive
Style." 1974.

Graber, Jim M. “The Use of Cognitive Style for Classroom
Placement of Primary School Students." 1975.

Grasser, Albert A. "A Multivariate Analysis of Cognitive
Style Elements as they Relate to Aptitude and
Achievement Factors in Elementary Algebra." 1973.

Gray, Larry Rex. "An Exploratory Study for Determining
the Ability of an Individual to Select a Television
Learning Environment Appropriate to his Educational
Cognitive Style." 1976.

Greyson, Mark E. "A Comparison of Counseling Using the
Cognitive Style Map of the Educational Sciences and
the Traditional Approach in the Educational Set-
ting." 1971.

Griffin, Thomas E. "A Comparison of the Cognitive Styles
of Deaf Students with the Cognitive Styles of
Hearing Students." 1976.

126

Gural, James R. "A Cognitive Style Approach to the
Reconceptualization of a Curriculum for Vocational
Guidance and Counseling." 1972.

Hand, James D. "Matching Programmed Instruction Packages
and an Instructional Setting to Students, in Terms
of Cognitive Style: An Exploratory Study." 1972.

Hoogasian, Vaughn. "An Examination of Cognitive Style
Profiles as Indicators of Performance Associated
with a Selected Discipline." 1970.

Korin, Uri. "An Investigation in the Educational Sciences
to Determine the Administrative Style of Successful
Principals and Graduate Students in Educational

Administration." 1974.

Krupa, Thomas J. "The Influence of Educational Cognitive
Style on Selected Elements of General Semantics."
1974.

Lange, Crystal Marie. "A Study of the Effects on Learning
of Matching the Cognitive Styles of Students and
Instructors in Nursing Education."_ 1972.

Lipson, Paul Erwin. "Influence of Educational Cognitive
Style and Teaching Style on Grading Practices in
a Junior High School." 1974.

Manilla, S. James. "A History of Oakland Community College
with Emphasis on Multi-Campus Administration,
Systems Approach to Instruction, and the
'Educational Sciences.'" 1971.

Mann, Theodore H. "Fundamentals of Piano: A Programmed
Approach." 1972.

McAdam, Glenn F. "Personalizing Instruction through the
Educational Sciences of Cognitive Style and
Teaching Style." 1971.

McIntire, Cecil Leroy. "Employing the Memory Set of Educa-
tional Style to Improve Prediction of Student
Performance." 1976.

Mueller, Joseph F. "Exploratory Study of the Psychological
Ecology of a Directed Lesson in a Nursery School
Setting." 1968.

127

Mustachio, James A. "The Influence of Specific Counseling
and Classroom Applications of Educational Cognitive
Style on Community College Students' Self-Concepts
and Grade Achievements." 1976.

Niles, Thomas R., II. "A Comparison of Cognitive Styles
between the Most Successful Michigan Directors
of Community Education and other Michigan Directors
of Comm8nity Education." 1974.

Nishioka, Richard T. "An Evaluation of a Systems Analysis
Operation in a Community College." 1970.

Ort, Barbara. "An Examination of Relationships between
the Measurable Cognitive Characteristics of a
French I Teacher and the Student's Success in
that Course." 1971.

Perry, Harold T. "Matching Cognitive, Actual, and Pre-
ferred Teaching Styles of Innercity Elementary
Teachers and Para-Professionals." 1975.

Rasof, Elvin I. "Approach to Optimal Decision-Making in
Selected Areas of Education." 1965.

Retzke, Ronald E. "The Effect of an Experimental Treatment
using Cognitive Styles on the Motivation of
Students in a Junior High Setting." 1976.

Ribley, Thomas J. "The Educational Science of Cognitive
Style and its Relationship to the Success or Non-
Success of Community College Students Enrolled in
General Statistics." 1976.

Rice, Marion M. "An Exploration of Educational Cognitive
Styles as a Vehicle for Determining Potential
Success of Community College Students within
Selected Occupational Curricula." 1973.

Robinson, Richard L. "A Descriptive Study of Specific
Achievements and Aptitudes of the "High Risk"
Students in Oakland University's Higher Oppor-
tunities Program in Education." 1969.

Rundio, Paul. "An Exploratory Study of Educational
Cognitive Style as a Means of Obtaining Clues for
Personalizing the Instruction of Ninth Grade
Students in Biology." 1973.

128

Stencel, Carol F. "Effects of Educational Cognitive Style
on Beginning Shorthand Performance." 1974.

Stringfellow, Hart R. "Cognitive Style Differences Among
Dental Students and Achievement in Oral Diagnosis
Using Computer Assisted Instruction--An Experi-
mental Study." 1975.

Strother, Seldon D. "An Analysis of Selected Cognitive
Style Elements as Predictors of Achievement from
a Didactic Film." 1973.

Stuart, William. "A Study of the Process of Conflict
Resolution Associated with Collective Bargaining
in a Community College Setting." 1976.

Summers, Irvin B. "Exploratory Study: Comparison of
Cognitive Styles to Employee Evaluation and
Employee Satisfaction." 1971.

Terrell, William R. "An Exploratory Study of the Modifi—
cation of Student Anxiety Levels Utilizing Cogni-
tive Style Matching)‘ 1974.

Thompson, Paul V., Jr. "The Deve10pment of Instructional
Strategies Based upon the Cognitive Styles of
Polk Community College and Florida Southern
College Students." 1975.

Truckey, George R. "A Study Directed Toward Development
of a Procedure for Analyzing and Improving Com-
munication Processes within School Districts."
1963.

Volk, Thomas. "The Typical Cognitive Profile of the
Entering Student of Nursing who Succeeds in the
Two-Year Nursing Program at a Selected Community
College: An Exploratory Study." 1975.

Wangler, John A. "Personalizing Education by Means of the
Burst Configuration Utilizing the Educational
Sciences in the Study of Social Science." 1974.

Warner, James L. ”An Analysis of the Cognitive Styles of
Community College Freshmen Enrolled in a Life
Science Course. 1970.

Wasser, Laurence. "An Investigation into Cognitive Style
as a Facet of Teachers' Systems of Student
Appraisal." 1969.

129

Salowich, LeRoy. "Some Biochemical Products Associated
wtih Memory in the Cognitive Style of an Individual:
An Exploratory Study in the Educational Sciences."
1971.

Scarbrough, Anne L. "A Study of the Relationship between
Student and Teacher Cognitive Styles and Grades
in Physical Education." 1976.

Schipper, Frederick A. "Comparative Study of Two Methods
of Arithmetic Instruction in an Inner- -City Jr.
High School. " 1964.

Schroeder, Arlen V. "A Study of the Relationship between
Student and Teacher Cognitive Styles and Student-
Derived Teacher Evaluations." 1970.

Setz, Betty D. "Models for Meaning: A Paradigm of
Academic Achievement Motivation Based Upon a
Defined Model of Value Formation." 1975.

Sharpe, Aaron J. "A Model for Training Development
Directors in Institutions of Higher Education."
1969.

Shuert, Keith L. "A Study to Determine Whether a Selected
Type of Cognitive Style Predisposes One to do Well
in Mathematics." 1970.

Sigren, Vincent G. "An Exploratory Study Employing the
Educational Sciences of Cognitive Style as a
Predictor of Group Leadership within an Orientation
Program." 1973.

Smith, Joan F. "Assessing the Cognitive Style of Students
in the Nursing Care of Patients having Retinal
Detachments." 1974.

Smith, Roger A. P. "An Exploratory Study of Cognitive
Learning Style Components for Achievement Using
Computer Simulation Games." 1974.

Smithers, James E. P. "An Investigation into the Effect
of Culture and Acculturation on the Formation of
Cognitive Style." 1974.

Spitler, Gail. "An Investigation of Various Cognitive
' Styles and the Implications for Mathematics
Education." 1970.

130

Waters, Thomas F. "A Report of an Internal Evaluation
System for an Experimental Educational Institute
in an Urban Area." 1970.

Woodworth, Paul. "An Investigation of the Dynamics of
the Learning Cell." 1975.

Woughter, Gerald. "Cognitive Style and Qualitative
Proprioceptiveness in Musical Performance." 1974.

Wyett, Jerry L. "A Pilot Study to Aanlyze Cognitive Style
and Teacing Style with Reference to Selected Strata
of the Defined Educational Sciences." 1967.'

Yasaitis, Virginia D. "An Exploratory Study of Group
Guidance Procedures with Underachievers in Grades
7-8-9 in a Selected Junior High School." 1971.

Zapinski, Roger A. "Enabling Characteristics of Financial
Aids Students at a Community College." 1973.

Zussman, Steven. "A Pilot Study Exploration of Cognitive
Style and Administrative Style as Defined in the
Educational Sciences." 1968.

APPENDIX F

DRIVER PERFORMANCE MEASUREMENT

RECORDING FORM

131

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APPENDIX G

THE STEPWISE PROCEDURE

137

APPENDIX G
111
THE STEPWISE PROCEDURE

The STEPWISE procedure can apply any of five tech-
niques to find which variables of a collection of independ-
ent variables should most likely be included in a regres-
sion model. The techniques can be useful for data
screening-~for promoting insight into the relative
strengths of the relationships between proposed independ-
ent variables and a dependent variable. None of the
techniques, however, is guaranteed to produce the "best"
model (or even the model with the largest R2 statistic),
and of course no model developed by such means can be
guaranteed to represent real-world processes accurately.

A MODEL statement identifies a collection of
independent variables and the dependent variable or
variables to be regressed on them. Any number of depend-
ent variables may be included in a MODEL statement; any
number of MODEL statements may accompany the PROCEDURE
STEPWISE statement. STEPWISE will perform calculations
separately for each MODEL statement. All the variables
must be numeric.

Given a dependent variable and a collection of
independent variables, STEPWISE can apply one or more of

the following five techniques:

138

139

1. Forward Selection. This technique finds first
the single-variable model which produces the largest R2
statistic. R2 is the square of the multiple correlation
coefficient; it can also be expressed as the ratio of
the regression sum of squares to the (corrected) total
sum of squares. For each of the other independent
variables, STEPWISE calculates an F-statistic reflecting
that variable's contribution to the model were it to be
included. If the F-statistic for one or more variables
has a significance probability greater than the specified
"significance level for entry," then the variable with
the largest F-statistic is included in the model. F-
statistics are again calculated for the variables still
remaining outside the model, and the evaluation process
is repeated. Variables are thus added one by one to the
model until no variable produces a significant F-statistic.

2. Backward Elimination. In this technique,
calculations are first performed for a model including
all the independent variables. Then variables are deleted
one by one until all the variables remaining in the model
produce "partial" F-statistics significant at the Specified
significance level for staying in (at each step, the
variable showing the smallest Contribution to the model
is the one deleted).

3. Stepwise. This technique is a modification of

the forward selection technique. As in the forward

140

selection technique, variables may be added one by one to
the model. A variable to be added must meet the same
conditions as in the forward selection technique. After
a variable is added, however, STEPWISE looks at all the
variables already included in the model. Any variable
not producing a partial F-statistic significant at the
specified significance level for staying in is then.
deleted from the model. Only after this check is made
and any required deletions accomplished can another
variable be added to the model. The process terminates
when no variable meets the conditions for inclusion in
the model or when the variable to be added to the model
is one just deleted from it.

4., Maximum R2 Improvement. This technique was
developed by James H. Goodnight; he considers it superior
to the stepwise technique and almost as good as calculat-
ing regressions on all possible subsets of the independent
variables. Unlike the three techniques above, this tech-
nique does not settle on a single model. Instead it
looks for the "best" one-variable model, the "best" two-
variable model, and so forth. It finds first the one-
variable model producing the highest R2 statistic. Then
another variable, the one which would yield the greatest
increase in R2, is added. ~Once this two-variable model
is obtained, each of the variables in the model is compared

to each variable not in the model. For each comparison,

141

the procedure determines if removing the variable in the
model and replacing it with the presently excluded
variable would increase R2. After all the possible
comparisons have been made, the switch which produces
the largest increase in R2 is made. Comparisons are made
again, and the process continues until the procedure finds
that no switch could increase R2. The two-variable model
thus settled on is considered the "best" two-variable
model the technique can find. The technique then adds
a third variable to the model, according to the criteria
used in adding the second variable. The comparing-and-
switching process is repeated, the "best" three-variable
model is discovered, and so forth. This technique differs
from the STEPWISE technique in that here all switches are
evaluated before any switch is made. In the STEPWISE
technique, removal of the "worst" variable may be accom—
plished without consideration of what adding the "best"
remaining variable would accomplish.

5. Minimum R2 Improvement. This technique closely
resembles the one just described. Here, though, when a

switch is to be made, the switch which produces the smallest

 

increase in R2 is the one actually performed. For a given
number of variables in the model, the maximum R2 improvement
technique and the minimum R2 improvement technique will

usually produce the same "best" model. More models of a

142

given size will be considered when the latter technique

is applied.

Output

For every model for which computations are done,
STEPWISE prints any analysis of variance table, regression
coefficients, and related statistics of it.

The table involves three sources of variation;
REGRESSION (i.e., variation possibly attributable to the
independent variables in the model); ERROR (residual
variation, not accounted for by the dependent variable's
relationship to the independent variables); and TOTAL
(corrected for the mean of X if an intercept is included
in the model and uncorrected if that term is excluded).
Statistics in the table include degrees of freedom ("DF");
sums of squares; mean squares; an "F value," the ratio
of the REGRESSION mean square to the ERROR mean square;
"PROB F," the significance probability of that F value;
and "R-SQUARE," the square of the multiple correlation
coefficient.

Below the table are printed the names of the
independent variables included in that model; their
corresponding estimated regression coefficients ("b-
values"); the partial sums of squares (a partial sum of
squares for a variable is its sum of squares adjusted

for all other independent variables in the model); and

143

the F-values and significance probabilities associated

with the partial sums of squares.

 

* 1
Used with permission of Dr. James H. Goodnight
(obtained July 12, 1978).

APPENDIX H

MAXIMUM R SQUARE IMPROVEMENT

STUDY DATA

144

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co—

APPENDIX I

COGNITIVE MAP INSTRUMENT DEVELOPED BY

DR. JOSEPH BOSCO

152

APPENDIX I

COGNITIVE MAP INSTRUMENT
DEVELOPED BY *
DR. JOSEPH BOSCO

Always
Usually
Sometimes
Seldom
Never

 

”.0

Whaian‘hqxntantrmwssnrmylugmens,lilﬂqato
hear about it on the radio rather than read it
hithermwmxxnr.

I write things down I want to remember.

wmail‘Uﬂaianathtzst]:lﬂeatolwweije
teaﬂunrremithecnm5tﬂmu;tormL

WhenzkwﬁngxnmtersItvouhiraﬂmnrwriuathan
onquem'ﬂmmxadd‘drmlinrmrhead.

I<xn1teLlty'axxusonusxmdcexmiu:he
:nﬁﬂlyrmans.

I‘mmmdlysmell13dngslxibnelieatiiem.

I can tell what is in my food by tasting it.
I lﬂmatO‘uImh'dungs.
Theanrthhrﬁ;lodcis:hmorhmﬁ:tormL

I.tqgnot1x)sayiiﬁngswﬂﬁchlnmt<mier
;pa$ﬂe%5feethgs.

I enjoy listening to beautiful music.
I2ﬁhﬁsh‘mrnzl sunk»
I<xu1actlikezmmmhergersmn

Iczmxmmermmekfunﬂasbmﬁlwiﬂmmtlxﬂng
vxmds.

Iiomidowwﬂlzhmspmﬁsitfliwmﬁzto.

I usually wait for people to “make the
ﬂhstrmweﬂ‘

I know myself well enough to know how well
I will do in a new activity.

153

154

 

 

 

m
0)
>4 E
m H H e
>. H .u o H
m as a: rc3 a)
3 :3 E H >
H m o m 0)
<3 D m (D Z
R. I can be counted on to bring group discussion
to some agreerrent. _____
S. I like to talk about my ideas with my friends. _____
T. I don't let anything interfere with family
plans. _____
U. When given a problem to solve, I can cone
to the best solution by myself, without
advice from others. _____
V. I notice changes and differences right away. _____
W. I like to make lists of how I budget my
tine, things I own, people I meet. _____
X. When I'm trying to understand something, I
like examples. _____
Y. The rules of math are easy to understand. _____
A. I would rather listen to the writer than
read his book. _____
B. I would rather read a book than hear
soneone talk about it. _____
C. When talking to someone, I like to use
numbers if they will help me prove a point. _____
D. If I have mney to spend, I like to write
down the amounts I will spend for each item. _____
E. I can tell who is on the phone by hearing
their voice. _____
F. The way things srrell is important to Ire. _____
G. I like to eat many different kinds 'of foods. _____
H. The way things feel when I touch them is
inportant to Ire. _____
I. I would rather see a movie than read the story. _____
J. Other people's feelings are important to me. _____
K. I notice when things are made well.

155

I
l

 

 

m
a)
>‘ E
m H «4 E
>. H u o H
to «3 cu 'o a)
3 :3 E H >
H m o a) a)
n: D a) m z
L. I get my work done on time. _____
M. I am able to be a good actor. _____
N. Iusemyhandswhenltalk. _____
O. I have athletic abilities. _____
P. I ask personal favors only fran close friends. _____
Q. I make plans based on my own interests and
what I can do. _____
R. I am able to influence others to join me
in doing something. _____
S. I like to do things with my friends. _____
T. Thinking about how my family would solve
a problem helps me solve my own problem. _____
U. If I have something important to decide, I
would rather think about it myself than
talk it over with my family. _____
V. I like to argue. _____
W. There is a right way and a wrong way to
do things. _____
X. In solving problems, I know there is something
else that ought to be considered. _____
Y. I like to figure out what's going to happen
next. _____
A. I enjoy talking with peOple. _____
B. I do well on the reading and English tests. _____
C. When I took classes in math I found it easy
to use numbers when talking with other
people in the class. _____
D. I get a good grade on written tests of

mathematics.

156

 

Always
Usually
Sometimes
Seldom
Never

 

I can tell if something is wrong with a
motor by listening to the sound of it.
(Lﬂm3a<xun eadngrmwhbmu)

I can tell "what's for dinner" by the smell.
The way things taste is important to me.

I choose food to eat by the way it feels in
my mouth as well as the way it tastes.

I choose clothes for the way they look.

I can understand how another person being
punished would feel.

I enjoy beautiful things like art, music,
films.

I keep my promises.
I can make a joke interesting.

People can tell how I feel by the sound of
my voice.

I work well with my hands doing such things
as woodworking , typing or sewing .

I use first names only with peOple I know
quite well.

I know myself pretty well.

I can make other people believe that my
ideas are right.

I seen to understand my problems better when
I talk with close friends.

I talk to my family before doing anything
which might affect them.

My best decisions seen to be the ones I make
alone.

I enjoy meeting all different kinds of people.
I like to keep everything in its place.

——~_—

_—~——

157

w
m
>1E
(DH-HE
$732388
3DEH>
Hmowcu
enmmz

 

I like to find out how things fit together.

When solving problems, I like to proceed in a
very logical pattern.

 

I understand an idea better if someone
explains it to me than if I read it myself.

I find that I understand new things easily
by reading about then. ‘

I find it easier to remember numbers which I
hear.

I can use written numbers easily.

If I have heard a musical instrument before,
I will recognize its sound on a record
when I hear it.

I notice the smell of people's perfume and
after shave lotion.

I am choosy about the food I eat.

I can tell what an object is just by touching
it.

I can put things together just by looking
at them.

I can understand how other people feel.

I go out of my way to see beautiful things.
I have many strong beliefs.

I am good at pretending.

People can tell hm I feel by looking at
my face.

My bodyworks well when I try todo things.

I do not like to meet a person unless I feel
he would like to meet me.

In games I have played, I can tell how well
I will do.

158

 

 

m
a)
>4 E
m H -H E
>. H u o H
to as w o a)
3 :3 E H :>
H m 0 cu m
a: :3 m m z
R. I am able to get people who are arguing to
reach agreement. _____
S. I am able to do something better when I can
discuss it with my friends. _____
T. If I have something important to decide I
would rather talk it over with my family
than my friends. _____
U. If I want something done right, I do it
myself. _____
V.’ When I explain something I show how it is
different from something else. (For example,
a Cadillac and Volkswagon.) _____
W. I like to do things when I know exactly what
to do. _____
X. I like a lot of information when I'm making
up my mind. _____
Y. I think ahead. _____
A. I like to listen to sareone speaking. _____
B. I enjoy reading magazines. _____
C. In solving math problems, I would rather
tell someone how to do the problem than
write it down. _____
D. When I work with numbers, I like to write
them on paper. _____
E. I can identify things by their sound. _____
F. I can tell different places by their smell. _____
G. I can tell most food just by tasting it. _____
B. When walking in a store, I like to touch
things. - _____
I. I would rather read things which have

pictures or drawings .

159

 

U)

m

>1E

'mH-HE

>1H4JOH
common)
3DEH>
Hmocum
<ommz

 

J. I can tell how a person is feeling even if he
doesn't tell me.

K. I enjoy seeing furniture that is nicely
placed in a room.

L. Doing what I think is right is important.
M. I can imitate someone else.

—.—m-——

N. I shake my head when saying no.

0. I can keep my balance well enough to walk
a straight line.

P. I do not discuss personal things with people
who would be embarrassed by them.

Q. I can tell how well I will do sarething
before I do it.

R. Icangetotherstodothethingslthink
theyshoulddo.

S. If I have something important to decide, I
would rather talk it over with my friends
than decide myself.

T. I like to do things with my family.

U. I like to do things my way even if it is not
approved by my friends or family.

V. I like to see people in many different styles
of clothing.

W. I believe people should follow the rules.

X. If I had to, I could take something apart
and put it back together. (Like a puzzle,
dress, motor.)

Y. I try to figure out how a game works without
reading the rules.

~”_*—

——_——

w~———

 

* ' .
Used with permission of Dr. Bosco (obtained July 12 , 1978) .

APPENDIX J

LETTER FROM C. BRUCE MARTIN,
DIRECTOR OF ACADEMIC AND MANAGEMENT
INFORMATION SYSTEMS,

OAKLAND COMMUNITY COLLEGE

160

161

 

Q5133

OAKLAND COMMUNITY COLLEGE
GEORGE A. DEE ADMINISTRATIVE CENTER 2480 OPDYKE ROAD .LDDMFIELD HILLS. MICHIGAN 46013 313-647-6200

October 17, I977

 

Mr. Paul Specht

Department of Safety

Humphreys Building

Central Missouri State University
Warrensburg, Missouri 64093

' Dear Paul:

I have enclosed the computer printout with several regression models run. Do not let the
volume frighten you. The statiscal package which I used was written by Anthony J. Barr,
James H. Goodnight, John P. Sail and Jane T. Helwig, of SAS Institute Inc. I ran all
five modeling approaches for your four dependent variables, Yl through Y4. Dr. Hill
always preferred the method maximum R2 improvement. I have enclosed two pages from
the SAS Manual which explains briefly the five techniques.

An arbitrary choice of .05 signifiance level for entry into the FORWARD selections and
STEPWISE techniques was made.

Oakland Community College does not have a program which does composite maps. It is

a manual process whereby you look at each element of the Cognitive Style map and count
the number of times it occurs in the group of maps. Any element which occurs 70% of the
time is considered to be representative of that group. I have included the frequency dis-
tribution to help you in this regard.

I am sure that you will have some questions, please do not hesitate to call.
Sincerely,
. ~ ' 7 .‘
(.ﬂL-ms/lcyrttr-
C. Bruce Martin, Director of

Academic & Management
Information Systems

CBM/mac
Attachments

 

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