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This is to certify that the

dissertation entitled

USE OF TECHNOLOGY BY NURSING STUDENTS:
LEARNING STYLES: AGE, AND EXPERIENCE

presented by
Denise L. Hoisington

has been accepted towards fulﬁllment
of the requirements for

Ph . D . degree in HA] .F.

 

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USE OF TECHNOLOGY BY NURSING STUDENTS:

LEARNING STYLES, AGE, AND EXPERIENCE
By

Denise L. Hoisington

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Educational Administration

2000

Tr
there is a
eXperien:
using the
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ABSTRACT
USE OF TECHNOLOGY BY NURSING STUDENTS:
LEARNING STYLES, AGE, AND EXPERIENCE
By

Denise L. Hoisington

The researchers primary purpose in this study was to determine whether
there is a relationship between the learning styles, computer/Intemet
experience, and age of selected nursing students, and those students’ comfort in
using the IntemethWW in a traditional course in Nursing Pharmacology. The
researcher also sought to determine what the students perceived as factors that
frustrated them or made them. uncomfortable when they completed course
assignments on the lntemet/WWW. An additional purpose was to determine
whether any suggestions could be made for teaching and Ieaming.

The study involved a convenience sample of 41 students enrolled in a
program leading to an associate degree in nursing. Students were in the ﬁrst
semester in the nursing program and enrolled in a one-credit course in
pharmacology. The study was qualitative and quantitative; it was considered

correlational, descriptive, and exploratory.

 

 

I
student
InventOI

No stati:
the comf
relations?
experienc
relationsh
The

the extra ti
and Ieam II
data Indica:

'mDIIcations

Were dISCus:

Denise L. Hoisington

A comfort scale developed by the researcher was used to measure
students’ comfort using the Internet and computers. The Canﬁeld Learning Style
Inventory and Gregorc Style Delineation were used to measure learning styles.
No statistically signiﬁcant relationship was found between students’ results on
the comfort instrument and their learning styles. A statistically signiﬁcant
relationship was found (alpha = .05) between students’ comfort and their
experience using the lntemet and computers. No statistically signiﬁcant
relationship was found between students’ comfort and their age.

The qualitative data indicated that students perceived comfort in terms of
the extra time it took to access the lntemet, deal with technological problems,
and team to use the computer software and browsers. Additional qualitative
data indicated that students gave only marginal responses over the lntemet.
Implications for further research, and for teaching and learning on the lntemet,

were discussed.

ACKNOWLEDGMENTS

I wish to thank those who provided support and encouragement through
the long days of completing this project. I particularly want to thank my doctoral
committee—Drs. Marvin Grandstaff (chair), John Dirkx, Ann Austin, and Walter
Hapkiewicz-for their contributions.

I also want to thank Dr. Sally Johnson for help with grammar, Dr. Fred
Swartz and Amy in Testing Services for assistance in data analysis and
instrument development, Dr. Mike Cooper for support in data analysis, Mary
Roehrig for assistance in instrument analysis, and all the faculty in the
Department of Nursing who provided support and encouragement. Special
thanks to all the students who agreed to participate in the study and those who

helped critique the lntemet assignments and the Comfort Instrument.

 

LIST OF TA

Chapter

In

TABLE OF CONTENTS

Page
LIST OF TABLES ............................................... vii
Chapter
I. THE PROBLEM ....................................... 1
Introduction and Background of the Problem ................ 1
Statement of the Problem ............................... 5
Purpose of the Study .................................. 10
Research Questions .................................. 11
Hypotheses ......................................... 12
Deﬁnition of Terms ................................... 12
Overview ........................................... 15
II. REVIEW OF LITERATURE ............................. 16
Introduction ......................................... 16
Deﬁnitions of Learning Style ............................ 17
Theoretical Framework for Understanding Learning
Style Theories ..................................... 21
Selected Theorists and Their Theories .................... 24
Personality Models of Learning Style ................... 27
Information-Processing Models ........................ 32
Social-Interaction Models ............................ 36
Instructional-Preference Models ....................... 40
A Combined Model ................................. 44
Conclusion ....................................... 46
Application of Learning Style Theory to the Classroom ....... 48
Research on Learning Styles of Nursing Students ........... 55
Research on Learning Styles of Students in Disciplines
Other Than Nursing ................................ 62
Technology, the lntemet/WWW, and Learning Styles ........ 68
Conclusion ......................................... 73
Hypothesis Generation, Conceptual Framework, and
Assumptions ...................................... 74

Page

III. DESIGN AND METHODOLOGY ......................... 82
Introduction ......................................... 82
Research Design ..................................... 83
Research Questions and Hypotheses ..................... 84
Subjects ........................................... 86

Sample Selection .................................. 86
Protection of Subjects’ Rights ......................... 88
Instrumentation ...................................... 89
The Canﬁeld Learning Style Inventory .................. 89
The Gregorc Style Delineator ......................... 92
The Comfort Instrument and Demographic Items .......... 95
Procedures ........................................ 101
Pilot Testing of Web Assignments and Syllabus .......... 101
Informed Consent ................................. 101
Data Collection ................................... 102

IV. RESULTS OF THE DATA ANALYSIS .................... 106
Introduction ........................................ 106
Descriptive-Statistics Findings ......................... 107
Results of Hypothesis Testing ......................... 110

Hypothesis 1 ..................................... 110
Hypothesis 2 ..................................... 116
Hypothesis 3 ..................................... 118
Results of the Qualitative Data Analysis .................. 119
Summary .......................................... 122

V. DISCUSSION, LIMITATIONS, RECOMMENDATIONS,
REFLECTIONS, AND CONCLUSION .................... 123
Discussion ......................................... 123
Limitations ......................................... 124
Recommendations for Further Research and for

Teaching and Learning ............................. 125
Reﬂections ........................................ 128
Conclusion ........................................ 132
APPENDICES
A Descriptive Statistics for the Sample ..................... 136
B. Informed Consent and Letter of Permission From the

University Committee on Research Involving Human
Subjects (UCRIHS) .................................. 141

vi

 

D.

E.

F.
REFEREM

Page

C Supplementary Information on the Canﬁeld LSI ............ 144
D. Administration and Scoring of the Gregorc Style Delineator . . . 154
E The Comfort Instrument .............................. 159
F. Web Assignments ................................... 161
REFERENCES ................................................ 169

vii

10.

11.

12.

13.

14.

LIST OF TABLES

Page
Deﬁnitions of lntemet/WWW Terminology ....................... 3
Subjects’ Age and Experience Using the lntemet and Computers . . . . 88
Distribution of Subjects by Gender and TraditionallNontraditional
Age .................................................... 88
Correlations of Items in the Comfort Instrument .................. 98
Reliability Coefﬁcients of the Comfort Instrument: Scale Alphas . . . . 100
Total for All Students on Each of the Four Channels of the Gregorc
Style Delineator .......................................... 107
Total Scores for All Students, by Scale, on the Canﬁeld LSI ........ 108
Descriptive Statistics for the Comfort Instrument ................. 109
Correlations Between 21 Canﬁeld LSI Scales and Total Scores on
the Comfort Instrument .................................... 1 11
Correlations Between the Four Channels of the Gregorc Style
Delineator and the Total Score on the Comfort Instrument ......... 112
Regression Between the Dependent Variable, Total Comfort
Score, and the Independent Variables, Canﬁeld LSI Preferred
Mode of Learning ......................................... 113
Regression Between the Four Gregorc Channels (AS, CS, CR,
AR) and the Total Score on the Comfort Instrument .............. 114
Regression Between the Four Gregorc Channels (AS, CS, CR,
AR) and the Web Assignment Form: Frustration ................. 115
Correlation of Total Score on the Comfort Instrument and
Experience Using Computers and the lntemet .................. 117

viii

A1.

A3.
A4.
A5.
A6.
A7.
A8.
CI .
C2.
C3.

Breakdown of the Sample by Age ............................ 137
Subjects’ Experience Using the Computer ...................... 138
Subjects’ Experience Using the Web/lntemet ................... 138
Subjects’ Educational Level/Background ....................... 1 39
Subjects Who Had Taken Previous Courses on the Web .......... 139
Subjects Who Considered Themselves Computer Literate ......... 139
Subjects’ Comfort Using the Web ............................ 140
Subjects Who Had a Computer at Home ....................... 140
Description of Scales on the Canﬁeld LSI ...................... 145
Item Analysis, Canﬁeld LSI, Form A .......................... 147
Split-Half Scale Reliabilities, Canﬁeld LSI, Form A ............... 149

SI

CHAPTER I
THE PROBLEM

Introduction and Background of the Problem
The World Wide Web (WW) and the Internet have increased
enormously in popularity over the past ﬁve years. With this popular technology
have come new ways to perform ﬁnancial transactions, conduct research, ﬁnd

.-V

information, market products, ﬁnd clients or customers to purchase services and
\Fr,

products, and communicate with others. The W has become a household
word to the youngest of children, many of whose parents have yet to master the
computer. For these people, new Internet hardware systems have been
developed that connect to the family television without the need for a computer.

As this technological phenomenon grows, the Justice Department and Internet

software developers have become embroiled ip a legal battle to prevent a

I OBNSJW' ?DHI”5:J§!“) U bbihc GENE“; 6 5w?”

lucrative monopoly over this 'eﬂéllfﬂg technology
Along with the beneﬁts of the Internet have come public concerns for
limiting children’s access to potentially harmful Web sites. Others have voiced
the need for government regulation of the lntemet to prohibit the transmission
Is’r‘mm

and publication of various types of material, such as child pornography. As a

result, the Internet and Internet providers are caught between social concerns

 

and the I
importan
worldwide
and contr
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suppliers.
and acces:
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Proli
institutions I
Computer so
of the WW
1996): unifcr
markup Iangu
(See Table 1 1
UIIIl/ersjty SIUd
Camplete their.

With pfOfessors

and the constitutional amendment guaranteeing freedom of speech. This is an
important issue, especially when one considers that the W is exactly that,
worldwide, and thus leads to the question of whether anyone can try to legislate
and control this medium that crosses oceans and international boundaries. This
medium does not have just one source or even limited sources of producers,
suppliers, publishers, and consumers (Halpern, 1994). Anyone with a modem
and access to the Internet can publish information on the lntemet, making
control difﬁcult. H

Proliferation of the W has made it mandatory that graduatesof

institutions of higher education not only be proﬁcient In the use of computers and

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computer software, but also be able to navigate the often-confusing Web. Users

u‘m.

M—

of the WWW must learn the new terminology of surﬁng the Web (Wlliams,
1996): uniform resource locators (URLs), navigation bars, hyperlinks, hypertext
markup language (HTML), browsers, servers, and ﬁle transfer protocol (FTP).

(See Table 1 for definitions of Internet/WWW terminology.) College and

I
university Students are called on to use the lntemet to ﬁnd information to
complete their course work, to create and publish Web pages, to communicate
with professors and peers, and to register for classes. Some even take entire

i, courses over the lntemet outside of traditional classroom settings with
instructors in attendance. '

Higher education institutions have met this new wave of technology with

varying degrees of acceptance (Atkins & Rehn, 1996; Halpern, 1994; Simonson,

Hays, & Hall, 1966; Williams, 1996). Most colleges and universities have

2

Table 1: Deﬁnitions of IntemetIWWW terminology.

 

Electronic ma_i| Le-maiI)—Service for sending messages over a computer
network.

File transfer protocol tFTP)—The lntemet service that transfers ﬁles from one
computer to another over standard telephone lines.

Home page-The starting point for a Web site. It is the page that is retrieved
and displayed by default when a user visits the Web site.

Hypertext markup language (HTML)—The standard language for describing the
contents and appearance of pages on the WWW.

Hypertext tra_nsport protocol (HTTPi—The Internet protocol that allows WWW
browsers to retrieve information from servers.

Hyperlink-A pointer from text or from an image map to a page or other type of
ﬁle on the WWW. On Web pages, hyperlinks are the primary way to navigate
between pages and among Web sites.

lntemet—The global computer network, composed of thousands of wide area
networks (WANs) and local area networks (LANS), that uses transmission
control protocol (TCP)/Internet protocol (IP) to provide worldwide
communication to homes, schools, businesses, and governments. The W
runs on the Internet.

lntemet protocol (lP)—Intemet software that divides data into packets for
transmission over the lntemet. Computers must run IP to communicate across
the Internet.

T_ra_nsmission control protocol tTCP)—lntemet networking software that
controls the transmission of packets of data over the lntemet. Computers
must run TCP to communicate with Web servers.

Uniform Resource Locator (URL)—A string that supplies the Internet address of
a Web site or resource on the WWW, along with the protocol by which the site
or resource is accessed. The most common URL type is http:/l, which gives
the Internet address of a Web page.

Web Browser-A client application that fetches and displays Web pages and
other WWW resources for the user.

World Wide Web (W). The graphical Internet hypertext service that uses
the HTTP protocol to retrieve Web pages and other resources from Web
servers. Pages on the WWW usually contain hyperlinks to other pages,
documents, and ﬁles.

 

 

 

Note. From Getting Started With Microsoft FrontPage 98 (pp. 279-306), 1997,
Redmond, WA' Microsoft.

computer access to the lntemet and the WVWV; A, Anyone with a computer and:
access to the Web can reach these institutions’ home pages from personal
computers, connect to library services, locate descriptions of programs and
degrees, and read the institutions’ philosophy and mission statements. I Students

can access their own records and syllabi for courses, e-mail instructors,

we-

participate in chat and discussion groups, and even ﬁle papers electronically
(Terry, 1996). However, use of the lntemet in academics varies within
departments and programs across the campus for several reasons. Resources
for computers, release time for development of Web pages and assignments,
maintenance and frequent updating of hardware and software, faculty and staff
training (Terry, 1996), and acceptance of this different way of teaching and
learning all have led to the disparity among units when it comes to adoption and
use of the Internet across and within academic departments.

One reason for the hesitance of some academicians to adopt the lntemet
for their course work, besides the time and resources needed to develop Web
sites, is the complexity of developing Web pages (Williams, 1996). In the past,
Web pages have had to be developed using HTML (Terry, 1996), which entails
learning an entirely new computer language and spending time typing in
computer language to produce interesting and appealing Web sites. However,
new Software is emerging that allows people to construct Web pages using
familiar computer environments and techniques to circumvent many of the
confusing and cumbersome HTML functions, thereby allowing quicker

development of Web sites without a knowledge of HTML. The increasing ease

4

of Web-page development will enhance the use of the W as a medium for
course development and for offering entire degrees via the lntemet, as colleges
and universities compete for a potentially new student market.

In conclusion, the WW and lntemet are revolutionizing the way

colleges and universities reach students, provide services, and enhance

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teaching and learning. However, this technology presents many challenges for
students‘aﬂrtgfa;ltywho are not experienced in using this medium and are
unaware of its effects on teaching and Ieaming. As with any new technology,
many questions about instmction via the Web and lntemet will be raised and

answered over time and through trial and error. Thus, research is essential to

determine the best ways to teach and learn via the WWW.

Statement of the Problem
The proliferation and popularity of the lntemet and W are raising

questions about how this technology can be used to aid in teaching the diverse
types of students enrolled in colleges and universities. Students come to higher
education institutions with a wide array of knowledge and experience in using
not only computers but also the lntemet. Some students come from resource-
rich secondary school systems in which computers and access to the lntemet
are available and are used in many courses. Others come from schools where
computer access was limited or even unavailable. Although numerous students
have computers at home, just as many cannot afford home personal computers

(PCs). Also, many students who do have home PCs might not have affordable

access from home to the lntemet (Terry, 1996), such as those living in rural
areas, where long-distance telephone charges for lntemgtaccess.can limit their
time online. In some of these areas, public facilities to access the W are
also limited, if available at all.

The use of the lntemet in traditional college courses has other
implications, as well. Some students come to higher education directly from
secondary schools, whereas others enter after having been out of school for
many years. Still others return to school after having successful careers, to
update their skills or to venture into a new career. For many of these students,
traditional classroom lectures dominated their secondary and postsecondary
educational experiences. To take courses on the W or just to complete
Web-based assignments can be overwhelming, not onlytothese students but
also to faculty who may not understand the implications the lntemet has for
teaching and Ieaming. M

The lntemet has thus become a new way to teach and to learn (Terry,
1996). Yet, little advice and few resources are available for faculty to learn how
to develop programs and courses to be offered on the W. A search of the
literature yielded little guidance in how to use the W to aid in teaching and
Ieaming, what types of learning occur, and whether the lntemet provides the
same quality of programs and Ieaming as traditional classrooms and course

work. Minimal research has been conducted on what should be done to provide

quality lntemet courses and assignments, and what types of students learn best

by using the WW and the lntemet. Again, the literature provides little or no
guidance in these areas.

Ample literature is available on Ieaming through the use of computers,
computer-assisted instruction (CAI), use of hypermedia, and other modalities.
Yet, information on how use of the lntemet and the WWW relates to Ieaming
and teaching is lacking. Eggers and McGonigle (1996) found that use of lntemet
communication (both synchronous and asynchronous) with students did not elicit
the quality or quantity of student responses that was deemed appropriate. They
stated that the quality of electronic communication can be a problem. Thus,
Eggers and McGonigle advised that instructors should be aware of the
importance of synchronous and asynchronous communication and suggested
setting up electronic ofﬁce hours.

The question has been raised whether there is a difference in quality
between lntemet and traditional classroom settings. Communication using the
Web might lack quality because it is such a new medium through which to
present courses and course work, and many people are unfamiliar with the
technology. Yet, courses are now being taught exclusively on the WW, and
traditional courses include assignments that necessitate using the Web for
course completion.

Fischer, Fischer, and Hayes (1996) and Thurston and Sebastian (1996)
viewed the lntemet as a viable option in distance education, which can link
learners in rural areas to major colleges and universities. They stated that e-

mail, list-serves, discussion groups, and access to instant information all provide

a forum far superior to the traditional classroom. An Intemebbased
course/classroom management system has been established at the State
University of New York (Graziadei, Gallagher, Brown, & Sasiadek, 1997). It is
designed to assist faculty in developing courses on the Web and providing a
better synchronous and asynchronous Ieaming environment.

( Even if the W is not included in their course work, students need to
understand how to use the Web as a rich source of information. They need to
be able not only to ﬁnd information but also to distinguish between good
information and that which is of questionable value (Fischer et al., 1996; Kazor &
Jacobson, 1996). Also, students and faculty still are feeling their way with the
use of computers and software programs (Partridge, 1993) and determining their
place in teaching and learning. Now, the lntemet has been added to the
growing technology, and students and faculty are unsure how to use this
medium to maximize its potential in teaching and Ieaming (Williams, 1996).

A literature review did bring to light some articles about how to use HTML
to develop Web pages, what types of fonts to use, and other aspects of
preparing a Web site. Monographs were found describing what various
universities have done to provide lntemet courses and faculty development in
their use. Studies were found on the use of computers in instruction. However,
only a few articles were found on using the W or its relationship to teaching
and Ieaming. When authors did address topics of teaching and Ieaming, they
concentrated on how to help students ﬁnd information on the WWW, students’

need to use critical thinking to ﬁnd information on the Web, and differences in

students’ use of the lntemet in comparison to other Ieaming techniques
(VVIIIiams, 1996).

st ,,_7 Nowhere is the use of the lntemet more important than in healthcare
programs in higher education, more speciﬁcally, in the nursing profession.
Technology is changing so fast in healthcare, and nurses must keep current on
new drugs, innovative medical devices, and healthcare issues. The lntemet is
an important way to access such information in a timely manner. It enables
individuals to network with other nurses through list-serves, chat rooms, and e-
mail (Farquhar et al., 1996). Yet, the new technology is not used by many
nurses, partly because little use is made of the lntemet in nursing education.

Mill et al. (1997) found that, in some institutions, nursing faculty and
students felt comfortable using computers. They used computers to play games,
do word processing, and conduct database searches. However, in their study of
one university, only 25% of students and 40% of faculty thought they used the
lntemet effectively. In the same survey, 100% of students and faculty said they
would like to have an opportunity to learn more about the lntemet.

The information and technology explosion may be leaving many nurses
behind, and if nurses are unable to use the lntemet effectively, they will remain
behind. Mill, Piper, and Tucker (1997) stated that few nurses use medical
devices and computers effectively in acute-care settings. Healthcare providers
cannot afford to employ nurses who are unable to function in ever-changing
healthcare settings. Functioning effectively includes use of computers and the

lntemet because informatics is becoming ever more important in nurses’ work.

Mill et al. (1997) discussed this situation, stating that nurses who can effectively
use just computers realize an average of 15% more in earnings than those who
cannot use computers.

Nursing programs in higher education have student populations similar to
those of other disciplines. Like other disciplines in higher education, nursing
education depends on the use of information found in textbooks and journals,
which quickly becomes outdated. The lntemet is a source of almost inﬁnite
information and communication and can remain more up to date and timely than
published materials. Therefore, students must have access to and be given
opportunities to learn to use this technology, in order to complete course
assignments while they are in school and to remain current in their ﬁelds after

graduation.

Eprpose of the Study

The researchers primary purpose in this study was to determine whether
there is a relationship between the Ieaming styles, computer/lntemet
experience, and age of selected nursing students, and those students’ comfort in
using the lntemet/WWW in a traditional course in Nursing Pharmacology. The
researcher also sought to determine what the students perceived as factors that
frustrated them or made them uncomfortable when they completed course
assignments on the Internet/WWW. An additional purpose was to determine

whether any suggestions could be made for teaching and Ieaming.

10

To accomplish this purpose, the researcher collected data from a
convenience sample of 41 students enrolled in a program leading to an

associate degree in nursing at a midwestem university.

Reseapch Questions

The following questions were posed to guide the collection of data for the
quantitative portion of this study:

1. IS there a relationship between the Ieaming styles (independent
variable) of nursing students enrolled in a traditionally taught course in Nursing
Pharmacology and those students’ comfort in using the lntemet/WWW
(dependent variable)?

2. Is there a relationship between nursing students’ personal experience
in using computers and the lntemet (independent variable) and those students’
comfort in using the lntemet/WWW (dependent variable)?

3. Is there a relationship between nursing students’ age (independent
variable) and those students’ comfort in using the lntemet/WWW (dependent
variable)?

Creswell (1994) stated that research questions also should be used to
guide the collection of data in qualitative studies. Thus, two exploratory
questions were posed for the qualitative portion of the study:

4. What do students perceive as factors that were frustrating or made
them uncomfortable when they completed course assignments on the
lntemet/WWW?

5. Can suggestions be made for teaching and Ieaming?

11

Hypotheses

Null hypotheses were formulated to test the data gathered to answer the
ﬁrst three research questions. They are as follows:

Ho 1: There is no relationship between nursing students’ Ieaming styles
and their comfort in using the Internet/WWW.

ﬂ9_2_:_ There is no relationship between nursing students’ personal

experience in using computers and the lntemet and their comfort in using

the lntemet/WWW.

L193; There is no relationship between nursing students’ age and their

comfort in using the lntemet/WWW.

Deﬁnition of Terms

The following terms are deﬁned in the context in which they are used in
this dissertation:

Adaptation: “A process of responding positively to environmental
changes in such a way as to decrease responses necessary to cope with the
stimuli and increase sensitivity to respond to other stimuli” (Johnson-Lutjens,
1991,p.34)

Asynchronous communication: Communication that takes place when two
or more people are online at the same time and responding to one another
instantaneously. Examples are teleconferences and chat rooms.

QM: Self-reported feelings of students as to their experience using
the lntemet/Web for course assignments, as measured by the Comfort
Instrument.

Comfort Instrument: Researcher—developed instrument using bipolar

terms developed to elicit degree of comfort responses from subjects.

12

939mg: ‘Routine, accustomed patterns of behavior to deal with daily
situations, as well as the production of new ways of behaving when drastic
changes defy the familiar responses” (Johnson-Lutjens, 1991, p. 36).

Coping mechanisms: “Innate or acquired ways of responding to the
changing environment. Innate coping mechanisms are genetically determined or
common to a species. Acquired coping mechanisms are developed through
processes such as learning” (Johnson-Lutjens, 1991, p. 36).

Discussion group: A site on the Web where Pharmacology 151 students
posted their responses to questions or comments from the instructor. After the
message or comment was posted, it was left for other students to read.

Learning style: “The affective component of educational experience,
which motivates a student to choose, attend to and perform well in a course or
training exercise” (Canﬁeld, 1992, p. 1).

Learning style preference: “The way individuals concentrate on, absorb,
and retain new or difﬁcult information or skills” (Dunn, 1983, p. 496). Learning
style is a “combination of environmental, emotional, sociological, psychosocial
and psychological elements that permit individuals to receive, store, and use
knowledge or abilities” (pp. 496-497).

Nursing student: A student who was enrolled in Pharmacology 151, was
involved in obtaining an associate degree in nursing, and had no previous
educational background in nursing. Nursing students in this study were at least
sophomores and were involved in both classroom and clinical settings in

hospitals as part of their educational program.

13

Pharmacolpgy Web page: A Web site developed by the researcher and
placed on a local server. The site contained all materials and assignments
needed to complete the course. It contained hyperlinks to pharmacological sites
that students might ﬁnd useful, as well as directions to complete Web
assignments developed for the course. The site could be accessed from
anywhere with the proper computer software and access to the lntemet.

Synchronous communication: Communication that involves one person
leaving a message or other communication for another individual. The second
person receives the message at a later time when accessing the information.
Types of synchronous communication on the WWW include sending e-mail,
posting a message, and responding to a question or comment in a discussion
group.

Threaded messages: Messages or comments that are saved and can be
viewed again after another message or comment has been sent. An example is
e-mail messages to which the receiver responds, leaving the original message
attached. Another example is posting messages to a discussion group, whereby
a person can read all messages that have already been posted and then leave a
new message that will be added to the list of messages for subsequent visitors
to read. Messages or comments can be threaded so that the newest comment is
placed at the top of the list or saved under the last one that was sent or posted.
In discussion groups, threaded messages allow others to see and respond to all

posted comments.

14

Web assignments: Four assignments that were a part of Pharmacology
151. Each assignment included performance of one activity on the Web. The

Web assignments were part of the course.

Dye—Meir.

Chapter I contained an introduction to the study and the background of
the problem, as well as a statement of the problem. The purpose of the study
was set forth, and the research questions and hypotheses were stated.
Deﬁnitions of key terms were provided. Chapter II is a review of literature and
research on Ieaming styles and other topics pertinent to the study. The
methodology used in conducting the study is discussed in Chapter III, and the
ﬁndings are presented in Chapter IV. Chapter V contains conclusions drawn
from the ﬁndings, limitations, and recommendations for practice and for further

research.

15

 

CHAPTER II
REVIEW OF LITERATURE

Introduction

Literature on Ieaming styles abounds. Exploration of the literature on
Ieaming styles revealed a number of theories about and measures of Ieaming
styles. Also, much research has been conducted pertaining to Ieaming styles of
students across all age groups and disciplines. This chapter begins with
deﬁnitions of Ieaming styles and continues with an in—depth review of Ieaming
style theory and a discussion of Ieaming style inventories. Research on Ieaming
styles in general and the Ieaming styles of nursing students in particular also is
reviewed. Next is a discussion of the literature on learning styles and Ieaming
with computers and the W.

The review of research on Ieaming styles ends with the researcher
developing assumptions and a conceptual framework for use in connecting the
literature review on Ieaming styles to Ieaming on the lntemet. The conceptual
framework and assumptions are intended to give the reader a better
understanding of how the purpose was formed and the hypotheses generated,
why the instruments were chosen, and the researchers expectation of data

analysis.

16

Deﬁnitions of Leamin Is

In the literature, writers have used the terms learning style, cognitive style,
and Ieaming strategies. Hence, it is important to consider how these various
terms relate to each other, not only to understand what the term Ieaming style
means, but also to understand why there are so many different theories and
inventories purporting to describe and measure individual Ieaming styles. In this
section, an attempt is made to deﬁne the term learning style by comparing it to
the concepts of cognitive style and learning strategies.

One reason for the multiplicity of terms is that Ieaming style theorists
have been unable to arrive at a common deﬁnition of Ieaming style. This is
partly because of a lack of knowledge of how the brain processes information,
and partly because it is difﬁcult to assess characteristics used in measuring
Ieaming style. Other reasons are that students learn in many ways, individuals
encounter multiple Ieaming situations, and different theorists and researchers
consider various Ieaming phenomena to be most important in the process of
Ieaming. Further, most of the research on cognitive style has been done on
children, and it is not clear how generalizable the results are to adults.

Merriam and Caffarella (1991) stated that cognitive styles are consistent
ways persons perceive, remember, think, and problem solve. They deﬁned
cognitive style as the way people interpret their environments. They believed
that people tend to be either global or speciﬁc in their approach to problem

solving. Global problem-solvers look at problems in terms of the overall aspect

17

of which the problems are a part. Speciﬁc problem-solvers like facts and ﬁgures
and consider individual pieces of the problem.

Merriam and Caffarella (1991) stated that Ieaming style and cognitive
style refer to different things, even though some authors use the terms
interchangeably. They cited numerous writers who have attempted to deﬁne the
two terms and concluded that the difference between the terms cognitive style
and Ieaming style lies in the Ieaming situation itself. Cognitive style is used to
describe how individuals generally “perceive, organize, and process
information,” whereas Ieaming style is used to “emphasize both the learner and
the Ieaming environment” (p. 177). Therefore, cognitive style refers to the way
the individual has learned to process stimuli he or she encounters, and Ieaming
style is how the learner uses the environment to obtain information for
processing. Learning strategies are the tactics (reading, lecture, movies, hands-
on) the learner uses to take in the information from the environment and then to
process (cognitive style) that information into some form of usable information
for further Ieaming.

Robinson (1979) deﬁned learning style as “distinctive behaviors which
serve as indicators of how a person leams from and adapts to his environment.
It also gives clues as to how a person’s mind operates” (p. 49). In contrast,
Underwood (1987) deﬁned Ieaming style as “an attribute, characteristic or
quality within an individual that interacts with instructional circumstances in such
a way as to produce differential Ieaming achievement” (p. 7). She identiﬁed four

ways to evaluate Ieaming styles: (a) determining variations in modes of

18

perceiving, remembering, and thinking; (b) identifying avenues by which people
“apprehend, store, transform and utilize information”; (c) identifying conditions
under which students are likely to learn; and (d) determining “the amount of
structure” persons need in order to achieve (p. 7).

According to Tennant (1991 ), cognitive style and Ieaming Style “are
related terms which refer to an individual’s characteristic and consistent
approach to organizing and processing information” (p. 89). Tennant described
Ieaming style as an egalitarian concept because, instead of being thought of as
good or bad, learners are simply considered different. The prevailing principle
of the egalitarian concept is that all learners learn differently. Therefore, no way
of Ieaming is viewed as a good or a bad way to learn.

Gregorc (1994) used the word style to describe Ieaming approaches and
deﬁned style as being ”based on Mediation Ability Channels through which [one]
receives and expresses information most efﬁciently and effectively. The power,
capacity, and dexterity to utilize these channels are collectively termed
mediation abilities. The outward appearance of an individual’s mediation
abilities is what is popularly termed style” (p. 5). Thus, Gregorc deﬁned style as
the behaviors exhibited by individuals in using channels after they encounter
stimuli. Channels refer to the speciﬁc way individuals take in information and
route it for processing. Style is therefore the behavior others observe of the
individual when he or she is in a Ieaming situation.

Pintrich and Johnson (1990) distinguished between Ieaming styles and

Ieaming strategies. Learning styles, they said, are “based on the assumption

19

that individuals can be described by certain psychological characteristics, traits
or styles that inﬂuence the way they perceive, organize, and react to different
environmental stimuli” (p. 84). Learning styles are stable across time and
different situations, are difﬁcult to change, and are not under conscious control
of the learner. In comparison, Ieaming strategies are those techniques that
people use regardless of their Ieaming styles, even though people with similar
Ieaming styles use similar Ieaming strategies.

Unlike Ieaming styles, Ieaming strategies can be learned and changed
(Pintrich & Johnson, 1990). Learning strategy theory “emphasizes (a) the
changing nature of strategies and motivation due to situational demands and (b)
the assumption that the use of different Ieaming strategies can be controlled by
the learner” (p. 85). Many times, however, students have knowledge of only a
few Ieaming strategies and use them in inappropriate ways.

Students can learn new strategies when they are presented. Pintrich and
Johnson (1990) stated that students engage in Ieaming through a variety of
situations, such as attending lectures and discussions, taking notes, writing
papers, taking multiple-choice examinations, writing essays, and reading. The
Ieaming strategies that are used in taking comprehensive essay examinations
are not appropriate to use when taking factual-recall or multiple-choice exams.
Thus, students need a wide range of Ieaming strategies to succeed in the varied
situations they encounter.

From the foregoing discussion, one can see that the terms cognitive style,

Ieaming style, and Ieaming strategy are difﬁcult to separate because they all

20

pertain to how the dynamic process of Ieaming takes place. The process starts
with the person’s ﬁrst encountering many forms of stimuli and then progresses to
mentally processing and sorting the information. The person then makes sense
of the information by incorporating it with what he or she already knows, and
then recalling the information in order to apply it in new situations or to provide
answers on evaluation tools such as exams. The above—mentioned terms are an
attempt to deﬁne the concept of Ieaming, a concept that has yet to be deﬁned
and thoroughly understood.

No consensus has been reached as to what Ieaming is, how it takes
place, or how to measure it in diverse learners and in the numerous Ieaming
situations that people encounter, not only in organized higher education settings
but also in work and daily life situations. Therefore, it is useful to view Ieaming
style theories and inventories within a conceptual framework in order to
understand the multiple perspectives that have been used in deﬁning,

explaining, and measuring Ieaming styles.

Theoretical Fra_mework for Understanding
Learning Syle Theories

Because of the number and diversity of Ieaming style theories described
in the literature, it is useful to examine the various theories and theorists in terms
of a conceptual framework that allows one to view the concept of Ieaming styles
based on the particular aspect of Ieaming style theory they purport to measure.
Curry’s framework, as used by Claxton and Murrell (1987, p. 7), was used as a

model to arrange and understand the various Ieaming style theories. Following

21

 

this explanation, selected Ieaming style theorists are discussed, along with their
measures of Ieaming style.

When discussing Ieaming styles, Claxton and Murrell (1987) used Curry’s
typology, which has four levels for classifying different Ieaming style theories.
The authors used the metaphor of an onion to conceptualize the different
models, or theories, of Ieaming style. They wrote,

At the core of the onion is style in the sense of basic characteristics of

personality. Information processing models, describing how persons tend

to take in and process information, are the second layer. Social-
interaction models, dealing with how students tend to interact and behave
in the classroom, make up the third; and Ieaming environment and

instructional preferences constitute the fourth. (p. 7)

Personality models are at the core of the metaphorical onion. Claxton
and Murrell identiﬁed personality models as the ﬁeld dependence and
independence work of Witkin and the Myers-Briggs Type. Indicator (MBTI) based
on Jungian theory. Also included are the theories of reﬂection versus
impulsivity, the Omnibus Personality Inventory, and the Holland typology of
personality, which attempts to describe Ieaming in light of individual
environmental preferences in the workplace.

The second layer, surrounding the core of the onion, is the information-
processing level. This level includes the work of Pask, who described Ieaming
strategies as holistic (global) or serialist (sequential). A second information-
processing theory is Kolb’s experiential Ieaming, which focuses on individual

development. A third infonnation-processing model was developed by Gregorc

and is similar to that of Kolb. Gregorc described information processing by

22

 

 

 

(I)

learners as being a combination of random or sequential and abstract or
concrete.

The next layer out from the core is the social-interaction level (Claxton &
Murrell, 1987). This level includes the Grasha and Reichmann theory, which
describes learners in terms of their response styles. Students are described as
independent, dependent avoidant, participant, competitive, and collaborative.
The Mann theory views students in terms of clusters, based on their responses
in the classroom. A third model, by F uhrmann and Jacobs, describes three
styles of student responses: dependent, collaborative, and independent. The
model classiﬁes students as Ieaming oriented or grade oriented. The Eison
model identiﬁes Ieaming style in terms of students’ attitudes pertaining to
grading and Ieaming.

The outer layer of the Ieaming-style onion contains Hill and Canﬁeld’s
instructional-preference models, which are used to evaluate the teaching
methods students prefer. Canﬁeld’s theory is based on MasloWs hierarchy of
needs and research on achievement motivation. His Learning Style Inventory
(LSI) encompasses four areas: conditions of Ieaming, content preferences,
instruction-mode preference, and grade expectations of students.

The above-described typology and framework provided by Claxton and
Murrell (1987) was used to organize Ieaming style theories in this study, in an
attempt to understand the various theories and the aspect of Ieaming style each

was devised to explain and measure. Using this framework, a review of the

23

literature on Ieaming style theories was undertaken to explain how the theories

vary.

Selected Theorists and Their Theories

There exist a wide variety of theories and approaches to understanding
Ieaming styles. Tennant (1991) asserted that Ieaming style theories “should not
be seen as mutually exclusive, rather they support the reasonable expectation
that people differ in their learning styles in a number of ways” (p. 89). Messick
(as cited in Tennant, 1991) identiﬁed 19 types of Ieaming styles, and Smith
identiﬁed 17 Ieaming style inventories aimed at diagnosing individual Ieaming
styles.

Tennant (1991) and Merriam and Caffarella (1991) stated that most
inventories identify Ieaming styles on bipolar scales using such terms as ﬁeld
dependent versus independent, reﬂective or impulsive, serialist or holistic, and
diverger versus converger. Tennant discussed the controversy surrounding the
belief of some Ieaming theorists that Ieaming potential involves a single
dimension such as intelligence quotient (IQ) and the notion that Ieaming style
can be measured by or adequately described with bipolar scales. However, a
single dimension and a bipolar scale cannot take into account the complexity of
the Ieaming process, multiple Ieaming situations, and the diversity of learners.

The debate surrounding the diversity of learners and Ieaming situations
has focused on the fact that, because there are so many situations and leamers,

an incomplete picture of Ieaming styles is obtained when they are measured on

24

such limited scales. Most of the LSls use paper-and-pencil questionnaires,
which limit the information gathered. Qualitative information, which would be a
richer source of data on individual Ieaming styles, is not gathered with the
inventories reviewed for this study. LSls, however, can be used with large
groups of students, and the ensuing data analyses are quicker and more cost
effective than analyses of interview responses and other qualitative data. This is
an important consideration when limited time and resources are available to
diagnose the Ieaming styles of large groups of students, such as those in
college classrooms.

Thompson and Crutchlow (1993) stated that much confusion about
Ieaming styles has resulted from the small samples used in most studies. Most
research efforts have been very limited and focused, have used one survey,
have employed limited research designs, and have not followed the same
students over time in order to understand how Ieaming styles may or may not
change.

Each Ieaming style, according to Fry and Kolb (as cited in Tennant,

1991 ), is incomplete by itself. Further, each learning style has its own
weaknesses and strengths. Thus, if a person is locked into one Ieaming style,
he or she is an incomplete learner. In contrast, the complete Ieamer is able to
distinguish each Ieaming style, know the boundaries of each one, and recognize
how to use each style effectively. Fry and Kolb “proceeded to link the notion of
the complete Ieamer with a model of human development whereby a long period

of accentuating one’s dominant Ieaming style is followed by a capacity for

25

integration. . . . It is not a model which is worked out in detail and there is no
evidence offered in its support” (Tennant, 1991, p. 102). Tennant criticized the
term complete Ieamer used by Kolb and Fry as being a “utopian conception of
psychological development" (p. 102).

To better understand the differences in Ieaming style theories and what
they mean, it is important to consider a sampling of those theories. By doing so,
educators who use Ieaming styles may gain a better understanding of what each
theory emphasizes and is intended to measure. The Ieaming style theories
presented here are only a sample and are presented in accordance with the
framework of Claxton and Murrell described above, starting at the center, or
core, of the onion. A review of these theories and their inventories provides the
context for each of the related studies and allows a better understanding of the
implications and conclusions from those studies.

Of the four levels of models included in Claxton and Murrell’s (1984)
framework, the third level, the one just beneath the outer layer, is social-
interaction theories. In the literature on nursing students, no studies were found
that speciﬁcally ﬁt this level, so the models discussed in that section are not
evident in the ensuing review of research articles. However, two models are
reviewed under the social-interaction level that illustrate what theorists in that
category have sought to understand when attempting to explain Ieaming styles.

A ﬁfth level was added for the purposes of this study. It contains the
Productivity Environmental Preference Survey (PEPS) developed by Price,

Dunn, and Dunn (1991), a model of Ieaming styles that does not seem to ﬁt into

26

any of the other four levels of Claxton and Murrell’s (1984) typology of Ieaming
styles. The PEPS appears to be more global and incorporates aspects of the

other four levels in various degrees. Therefore, it is included and discussed as

a separate level of the metaphorical onion.

Personali Models of Leamin t le

Field dependence/indegndence. Witkin discussed Ieaming styles in
terms of ﬁeld dependence and ﬁeld independence (T ennant, 1991; Witkin &
Goodenough, 1981 ). From studying how people make decisions, Witkin came to
believe that some people’s perceptual judgments are based on the context of the
situation. He related this to the cognitive function of decision making, but found
evidence that ﬁeld-independent learners perform better than ﬁeld dependents on
cognitive tasks. Witkin’s classiﬁcation of people as ﬁeld independent and
dependent has been broadened from just a narrow view of perception to an
understanding of how people in each of these categories view the world.

Field dependents are bounded by a social framework and reﬂect this
preference for social interaction in the activities they engage in and the work
area they select. Tennant (1991) described ﬁeld dependents as follows:

Field dependents rely on a social frame of reference to formulate their

beliefs, attitudes and feelings, and self-concept; . . . they make few self-

references in their speech; . . . they adapt their rate of speech to the rate
of the person to whom they are communicating; . . . they are more
sensitive to social cues; . . . they like to be with people; . . . they are better

liked; . . . they prefer to be physically closer to others, and so forth. (p. 92)

The following is a description of how ﬁeld-dependent students learn and how

such teachers teach:

27

Field dependent learners rely on externally provided structure, therefore
need assistance with unorganized material; tend to focus on salient cues
only, but their strategy can be altered with instruction; are better at
Ieaming and remembering social material; and external reinforcement
should be more salient. Teachers who are ﬁeld dependent prefer
discussion method and situations which allow interactions with students;
avoid negative feedback and evaluation; and prefer rapport, participation,
a warm and personal environment. Field dependents prefer interpersonal
domains which require social skills such as elementary school teaching,
social sciences, rehabilitation counseling, welfare; favor specializations
with a people emphasis, e.g., clinical psychology, psychiatric nursing,
social studies teacher; are more undecided about occupational choice
and less committed to their choice, and shift their college majors away
from impersonal and cognitive domains. (Tennant, 1991, pp. 93-94)

 

In contrast, ﬁeld independents are more autonomous and have been
taught throughout life to be independent. Therefore, they view the world from a
viewpoint of “self,” referring less to self in the context of others and using ”I”
when talking about the self. Field independents are less apt to feel comfortable
when involved in close work with others and function better in activities in which
they are allowed to function at the pace and course they set themselves. This is
not to say that ﬁeld independents cannot work with others and are antisocial;
rather, they prefer and have a higher level of comfort when they are able to work
independently and think as one. They have difﬁculty putting the world in a social
context; therefore, their actions are better suited to functions that allow them to
think and work outside the conﬁning context that society can bring. In this way,
they can focus on their internal motivation.

Field-independent learners Ieam more under conditions of intrinsic or
internal motivation, are more likely to structure ambiguous material, tend to

sample the entire array of cues (hypothesis-testing approach), and need

28

 

assistance in focusing on social material. They prefer analytic and impersonal

 

‘ domains in such areas as physical and biological sciences, mathematics,
engineering, and technical and mechanical activities. Such learners favor
specializations that are impersonal and require cognitive skills, such as
experimental psychology, surgical nursing, natural science, and teaching, which
are concerned with occupational planning; have more specialized vocational
interests; and shift their college majors away from personal and social domains.
Field-independent teachers prefer lectures, discovery methods, and situations
that are more impersonal and cognitive; emphasize the need to correct errors
and provide negative evaluations where appropriate; and show strength in
organizing and guiding student Ieaming.

The Myers-Briggs typology. The second personality model of Ieaming
style is the Myers-Briggs typology. This typology is based on the general
personality model and is not related to cognitive functioning used by college
students in normal classroom settings (Pintrich & Johnson, 1990). In the
Jungian-derived Myers-Briggs typology, students are categorized along four
dimensions. These dimensions are based on whether people use sensing or
intuition to perceive the world, and whether they employ thinking or feeling to
make judgments and decisions. People prefer one alternative from each of the
two categories. Along with preferences for sensing or intuition and thinking or
feeling, people have a propensity, or preference, for either introversion or

extroversion, and to be either judging or perceptive. These “preferences for

29

interacting with information and other people are related to how students Ieam in
all courses all the time” (Pintrich & Johnson, 1990, p. 84).

The Myers-Briggs Type Indicator (MBTI) measures variations in
individuals by means of dichotomous scales that assess (a) Extroversion versus
lntroversion (E-l), (b) Sensing versus Intuition (S-N), (c) Thinking versus Feeling
(T-F), and (d) Judging versus Perception (J-P). Research using the MBTI has
indicated that students tend to use consistent strategies to take in information
and make decisions regardless of the situation or material presented, based on
the four dichotomous scales.

Claxton and Murrell ( 1987) provided the following description of the four
scales of the MBTI. The El scale measures individuals’ tendency to be
extroverted (E), focusing on other people, actions, and ideas, or to be introverted
(l), focusing more on inner ideas and concepts. The S-N scale assesses
whether people act based on what they directly sense (S) from the concrete
environment or make inferences to give meaning to what is experienced (N).

T-F, the third scale on the MBTI, is used to explain how people make
individual judgments. These judgments may be made either through logical,
decision-making steps (T), or through decisions people make based on their
priorities and values (F). The ﬁnal scale, J-P, measures whether people judge
situations and react proactively based on planned actions (J) or react more
spontaneously to events without planning or controlling what is happening (P).

Implications of the Myers-Briggs theory have been researched and

demonstrated in teaching-Ieaming situations. Matching teaching and Ieaming

30

l
types on the four scales brings about better results than occur when teachers’
and learners’ types do not correspond to each other. The MBTI also has been
used to demonstrate that people Ieam better when course content, modes of
Ieaming, and so on, are matched with their Ieaming types, as determined by the
MBTI. Claxton and Murrell (1987) explained this by saying that

intuitive types consistently score higher on aptitude measures based on
reading and writing . . . because they convert symbols into meaning, thus
grasping concepts and ideas faster from written words and developing
greater skills in reading. Sensing types have less natural interest in
reading, take more time to read for details, and are less motivated to Ieam
to read unless they can see a practical use for reading. (p. 15)
McCaulley (1990) stated that the MBTI is useful not only with regard to
individuals but also to the relationships between individuals involved in groups.
In conclusion, researchers on ﬁeld-independent and ﬁeld-dependent
learners and the MBTI has attempted to describe individuals and how they think;
each theory is an attempt to classify students according to their unchanging
personalities. Claxton and Murrell (1987) also stated that these theories
measure personality attributes that are not changeable and are stable across
situations and time. In light of this, it is necessary to look at whether the Ieamer
and teacher are matched or mismatched because matching of the teacher-
student dyad is important for student Ieaming. If there is a mismatch, student
Ieaming and achievement will be hampered because it is difﬁcult for both
teacher and Ieamer to change to meet the needs of the other. This situation has

implications for faculty and student development ofﬁces, which will need to plan

courses and provide resources aimed at helping both faculty and students

31

understand the teacher-Ieamer situation. Instructors and students need help in
Ieaming how to work at optimal levels, whether matched or mismatched, how to
identify when there is a mismatch, and skill in decreasing the effects of a

mismatch.

Information-Processing Models

lnfonnation-processing models focus on how people process information
when they receive it. These models explain how students use past experiences
and knowledge to select information from the environment and incorporate it into
what they already know. The following examples comprise the second level of
Curry’s Ieaming-style “onion.”

Experiential Ieaming. Kolb and Fry related their theory of Ieaming style to
the experiential Ieaming model. In this model (Kolb, 1984), the Ieamer has a
concrete experience, makes observations and reﬂections based on the
experience, and then forms abstract concepts and generalizations from that
experience. The cycle is completed when the person tests the implications of
the concepts in new situations. When the cycle is completed, the Ieamer is
ready for another concrete experience based on a new frame of reference
developed from the last experiential process.

Kolb and Fry developed an LSI to measure a ”person’s relative position
on the concrete experience vs. the abstract conceptualization dimension,
and active experimentation vs. the reﬂective observation dimension”

(Tennant, 1991, p. 103). The LSI lists a number of words, which respondents

32

put in rank order according to preference. Researchers have linked LSI results
to such things as vocational choices, professional socialization, choice of
undergraduate majors, and preference for various teaching methods. This
theory is very prescriptive and has implications for career counseling of
students.

The terminology of this model is complex, so a more in-depth explanation
of the model, using direct quotations, is given here. The four Ieaming styles
characterized by Kolb and Fry (as cited in Tennant, 1991) are as follows:

1. Converger = Abstract Conceptualization + Active Experimentation:
These are the characteristics of many engineers. Convergers are strong
in the practical application of ideas, perform well when there is a single
correct answer such as on IQ tests, can focus hypothetical-deductive
reasoning on speciﬁc problems, are unemotional, prefer to deal with
things rather than people, and have narrow interests and choose to
specialize in the physical sciences.

2. Diverger = Concrete Experience + Reﬂective Observation:

These are characteristics of people with humanities and liberal arts
backgrounds. Divergers are strong in imaginative ability, are good at
generating ideas and seeing things from different perspectives, are
interested in people, have broad cultural interests, and specialize in the
arts.

3. Assimilator = Abstract Conceptualization + Reﬂective Observation:
Assimilators often work in research and planning departments. They
have a strong ability to create theoretical models, excel in inductive
reasoning, are concerned with abstract concepts rather than people, are
not too concerned with the practical use of theories, and are attracted to
basic sciences and mathematics.

4. Accommodator = Concrete Experience + Active Experimentation:
Accommodators are often found in action-oriented jobs such as marketing
and sales. Their greatest strength is in doing things, are risk takers,
perform well when required to quickly adapt to immediate circumstances,
solve problems intuitively, and rely on others for information. (p. 103)

33

 

Comwell and Manfredo (1994) found Kolb’s model to be valid, giving
credence to the need to match Ieaming styles with Ieaming experiences to
determine how students will master new skills. Geiger, Boyle, and Pinto (1992)
stated that the construct validity of the instrument still needs to be reviewed and
studied.

Style Delineator-Gregorc. This model also uses a bipolar scale ranging
from the abstract to the concrete (Gregorc, 1994; Robinson, 1979). Gregorc
juxtaposed this with an additional random-to-sequential scale similar to that of
Kolb. The ﬁrst Ieaming style described by Gregorc is the Concrete Sequential
(CS) Ieamer. In this style, Ieaming takes place based on hands-on concrete
experience that is ordered and logically sequenced with extensive direction. CS
teachers use a variety of teaching methods that are well organized and
instructor directed. Abstract Random (AR) Ieamers capture the teacher’s verbal
messages as well as nonverbal messages as a single concept in an
unstructured, free learning environment. AR teachers use varied teaching
methods but prefer peer Ieaming and peer interaction.

Abstract Sequential (AS) Ieamers do well at conceptualizing what they
learn and rely on reading and listening skills. AS teachers use reading as well
as written and oral assignments in which students can convey how they
conceptualize their ideas and thoughts. Concrete Random (CR) Ieamers excel
in problem solving, exploration, and experimentation based on independent,

individual, or small-group activity in which they can take detours from

34

assignments. CR teachers provide Ieaming experiences that give students only
the basic intention and let them develop and solve the problem.

Learning style models at the information processing level, such as those
of Kolb and Gregorc, attempt to explain how individuals process information and
highlight the role that development plays in Ieaming styles. They emphasized
the role that active Ieaming plays in Ieaming. Implications of these models
include offering courses based on the Ieamers’ development and using learners’
experiences as a way of relating new information to student Ieaming. This level
also emphasizes the relatively stable way in which people process information,
an approach that may be difﬁcult, if not impossible, to change. Implications for
the use of the Kolb and Gregorc models are found in the opportunity for
counselors and instructors to test students so they can be placed in courses and
career tracks that complement their learning styles. This implies that faculty
should also be aware of their own Ieaming styles. By knowing their own styles,
faculty will be better able to develop course lectures and modes of instruction
that provide a variety of avenues to accommodate different types of Ieaming, as
well as their own style.

According to these theories, Ieaming should include concrete, hands-on
experiences that students use as a base for Ieaming. This initial Ieaming is then
used when it is incorporated into future Ieaming. As learning takes place, it is
melded into past Ieaming and provides a new, broader base for additional future

Ieaming. This is considered a continuous cycle that includes not only classroom

35

experiences and Ieaming, but also application of Ieaming in situations
encountered in everyday life.

Unlike personality models, infonnation-processing models involve an
evolution of Ieaming or knowledge. Personality models describe how Ieamers
best take in information and process that information. Information-processing
models, on the other hand, describe Ieaming as dynamic, a transformation of
information from basic skills and knowledge to an increasing, more sophisticated
knowledge—knowledge that is not static but changes when new Ieaming takes

place.

Social-Interaction Models

The two models used as examples at the social-interaction level are those
based on the works of Grasha and Reichman and of Eison. These models
evaluate how students relate to others in the classroom and their individual
attitudes about course work and grades. These models are found in the layer
next to the outer layer of the metaphorical onion.

Grasha and Reichman’s Stgdgntﬂning Stvle Sgalg. Grasha and
Reichmann (as cited in Claxton & Murrell, 1987) developed the Grasha-
Reichmann Student Learning Style Scale (GRSLSS), which identiﬁes six
categories of student response styles. The six categories are described in the

following paragraphs:

1. Independent students work individually and are conﬁdent about their
own abilities. They learn what they need to know through their own abilities and
self-reliance.

2. Dependent students Ieam only what they need to know to pass the
course and to get by. They rely heavily on teachers to lead them. They need
direction in Ieaming and demand that the Ieaming process be laid out so that
they can move from point A to B to C, eventually Ieaming the material and
passing the course.

3. Collaborative students Ieam with and through others. They enjoy the
interaction involved in working with others. Learning is important, but social
contact adds motivation and enjoyment to the Ieaming process.

4. Competitive students strive to receive rewards, and the ultimate
reward is to be the best in the class. It is not that Ieaming is unimportant, but
Ieaming is secondary to the need to be the best.

5. Participant students enjoy the course work and want to Ieam and
retain high self-responsibility.

6. Avoidant students not only participate little, but they avoid doing any
more than absolutely necessary to pass the course or perform at the minimum
level.

Grasha and Reichmann’s Ieaming style model has been used to structure
courses for each of the different categories of students. For example,
Dependent students can use all teaching strategies, but they remain centered on

the teacher to lead their Ieaming. These students rely completely on the

37

teacher, not only to lead them but also to provide Ieaming situations in a highly
structured manner. Independent students, on the other hand, enjoy developing
their own Ieaming or unstructured Ieaming. Competitive students do well
leading peer groups, whereas collaborative students prefer lectures and small-
group activities. Participant students like opportunities to apply what they Ieam
and situations that allow them to analyze what they Ieam. Avoidant students see
no real value or beneﬁt in any situation involving the classroom; they do not care
for any classroom activity or content.

The GRSLSS, then, deﬁnes learning style as the way students like to
interact, or not interact, with the teacher, content, and others in the Ieaming
situation. According to the GRSLSS, Ieaming is maximized when students are
allowed to be in situations that reﬂect their social-emotional needs. Hence
Ieaming situations should reﬂect and fulﬁll the multiple needs of diverse
students.

The GRSLSS has demonstrated differences between traditional- and
nontraditional-age college students. The nontraditional-age groups were more
competitive, wanted less responsibility for Ieaming, wanted teacher control, and
had lower levels of interest in course work.

Eison’s LOGO II. The second social-interaction model was developed by
Eison (as cited in Claxton & Murrell, 1987), who studied student attitudes that
manifest themselves as observed behaviors toward grades and Ieaming. LOGO
II is the instrument Eison used to measure students’ attitudes in these situations.

He identiﬁed students according to Learning Orientation (L0) and Grade

38

EE-

Orientation (GO), hence the name LOGO II. Eison did not use these two
orientations alone, but used a combination of the behaviors to describe four
scenarios reﬂecting varying degrees of L0 and GO: (a) high L0 and high
GO—students are highly motivated to Ieam and achieve good grades; (b) high
L0 and low GO—these students’ primary concern is to Ieam. Grades do not
have great signiﬁcance or motivation in their Ieaming; (c) low L0 and high
GO—students seek grades irrespective of what they Ieam; and (d) low L0 and
low GO—students pursue neither grades nor Ieaming through attending college,
but rather seek other things such as job avoidance or social contact with peers.
Like the GRSLSS, LOGO II has been used in studies comparing
traditional- and nontraditional-age (adult) college students (Claxton & Murrell,
1987). Nontraditional groups scored higher on LOGO ll, indicating they had a
higher preference for Ieaming than did traditional-age students and that the two
groups need different evaluation criteria. Older, nontraditional students did not
care how grades were determined but enjoyed Ieaming assignments that were
not evaluated for grading purposes. Traditional-aged students’ concerns
revolved around quizzes, exams, and other graded assignments that were used
to measure their achievement or Ieaming. These students also requested extra-
credit assignments to raise their grades, thus indicating that letter or number
grades were very important to them. Implications of this study suggest that,
when working with traditional-age college students, courses should be organized

based on clear objectives, course work should be based less on individual

39

student responsibility, and there should be more graded assignments. Work
assignments should capitalize on the competitive nature of this group.

Social-interaction models of Ieaming style emphasize the social nature of
Ieaming and how students interact with peers and teachers and view grades and
content. According to Claxton and Murrell (1987), the two models presented
here have been useful in demonstrating the differences between traditional- and
nontraditional-age college students by assessing the motivation of
students-grades or personal improvement-and determining what aspects of the
social situation motivate, or do not serve to motivate, students in Ieaming
sﬁuaﬁons.

Compared to personality models and information—processing models, the
main aim of social-interaction models is to discover what makes students
perform in the classroom. Personality models and information-processing
models look at how information is acquired and what is the best way for
individual students to acquire that information. In information-processing
models, there is also a focus on how that information is taken in, what is done
with it, and how it relates to future Ieaming. In contrast, social-interaction
models describe what motivates students to excel or not to excel in the
classroom. These models are aimed more at discovering why students Ieam,

not how they acquire, process, and use information.

40

Instructional-Preference Models

Proceeding to the outer layer of the metaphorical onion, one comes to the
fourth level or instructional-preference models, exempliﬁed by the work of
Canﬁeld. Instructional-preference models appear to incorporate characteristics
of the social-interaction model with the type of content presented in the
classroom, instructional methods, and how students deal with the complexities of
the total Ieaming situation in the classroom environment.

Canﬁeld’s Learning Style Inventory. Canﬁeld’s Learning Style Inventory
(LSI) (as cited in Claxton & Murrell, 1987) is based on Maslow’s hierarchy of
needs and the achievement motivation theory developed by McClelland. This
inventory includes four scales: conditions of Ieaming, content preferences,
Ieaming mode preference, and expectations of students as to grade
achievement, which may or may not be a motivating factor determining how
students achieve.

The ﬁrst scale, conditions of Ieaming, describes how Ieamers deal with,
and interact in, different Ieaming situations. This scale includes aﬂ‘iliation—how
students interact with and handle others in the particular situation in which they
ﬁnd themselves. Structure measures learners’ need for organization and detail
in the Ieaming situation. Achievement is a measurement of how well students
set goals, and whether they work better independently or depend on others for
their Ieaming. Eminence concerns how students deal with authority and

competition in the classroom.

41

The second scale measures students’ content preferences in the
Ieaming situation. Canﬁeld classiﬁed course content into numerics (numbers),
qualitative (language), inanimate (working in areas of building or repairing), and
people (interviewing and sales).

The third scale assesses preferred modes of Ieaming and includes
listening, reading, iconic, and direct experience.

The fourth scale measures grades and the effect that students’
expectations of grades have on Ieaming. Expectation of a grade is viewed as a
motivational factor that inﬂuences how students perform in a course. Grades
can be highly motivating to some students who work hard to achieve expected
grades. Others, for whom grades are not a highly motivating factor, place less
emphasis on grade expectations. Thus, students who expect low grades may
realize a self-fulﬁlling prophecy and achieve low grades irrelevant to their actual
learning.

Together, the four scales on the LSI are used to assess how students
Ieam. Canﬁeld used this inventory to test college students. There is evidence
from use of Canﬁeld’s LSI in research that students enrolled in courses whose
content, conditions of Ieaming, and modes of Ieaming are similar to their own
will feel more comfortable and exhibit higher achievement in those courses. This
conclusion is true of each Ieaming style model in the other three levels of the
metaphorical onion, even though each focuses, deﬁnes, and measures Ieaming
styles in different terms. However, Canﬁeld’s instructional—preference model

seems to have a heightened focus on the importance of the instructor and

42

instructional methods used in the classroom, as well as the need for on-going
evaluation and improvement of courses and programs.

Instructional-preference models, such as that of Canﬁeld, pertain
speciﬁcally to the classroom and instructional methods. The implications are
greater than just diagnosing Ieaming styles in order to provide instruction that
meets students’ individual needs. If individual students’ needs are identiﬁed and
faculty are sensitized to these needs, faculty can better refer students for
assistance and develop classroom strategies that enhance students’ chances of
success. By identifying individual Ieaming styles using models in the fourth
level, administrators and faculty alike can develop a consciousness of the
importance of individual differences and can work to develop programs and
courses to meet more students’ needs. To do this, administrators and faculty
would participate in continual evaluation and improvement of programs and
classroom instruction.

Unlike the models in the other three levels of Ieaming styles, the
instructional-preference models divert the focus from the student as being solely
responsible for Ieaming and recognize the role the classroom environment,
instructional methods, and instructor play in student Ieaming and achievement.
These models shift the focus from student—centered information processing,
social interactions, and motivation to a complex network of different students,
multiple motivations and interactions, and diverse content, Ieaming activities,

instructional styles, and classroom environments. This emphasizes the need for

43

faculty to seek and implement new instructional strategies to meet the needs of
students with varying Ieaming styles.

An important aspect not present in models at the other three levels is that
Canﬁeld’s model places some responsibility for student Ieaming and
achievement on instructors by recognizing the complex issues involved in
Ieaming styles. Instructors are moved to refer students to other resources, such
as individual tutoring or assistance in identifying their Ieaming styles, so the
students can seek situations that maximize their strengths and work on their

weaknesses.

A ombined Model

A ﬁfth level of Ieaming style model is included here, constituting the
outermost layer of the symbolic onion. This model is similar to level four, which
recognizes the complexity of Ieamers and Ieaming situations. However, it
emphasizes the Ieaming that takes place in everyday life. It is not focused
solely on the structured Ieaming situations often found in the classroom, but
rather on Ieaming as it also occurs in the day-to—day activities of individuals in
work and life situations. It therefore takes the emphasis from Ieaming in an
educational setting, recognizing that Ieaming takes place every day in many
situations and environments. It is not that the other models exclude Ieaming that
takes place outside of the classroom, but they do not emphasize the more global

Ieaming that individuals experience. In this combined model, the word

preference is used to denote that people favor certain Ieaming factors, which
does not preclude their having just one Ieaming style.

Productivity Environmental Preference Survey. Price et al. (1991)
developed the Productivity Environmental Preference Survey (PEPS). The
underlying theory behind the PEPS is that individuals’ preferences for Ieaming
situations apply not only to the classroom, but also to work situations. Like
Canﬁeld’s instrument, the PEPS is comprehensive and attempts to measure
numerous items involved in working and Ieaming. The theory and instrument
include many of the areas assessed in the models described above. Instead of
having just one or two scales that measure particular aspects of Ieaming style
phenomena, the PEPS incorporates many scales to measure several aspects or
stimuli that students encounter in the Ieaming situation. It does not use a strictly
bipolar scale.

Dunn (1983) stated that diagnosing Ieaming styles involves considering
ﬁve stimuli: environmental, emotional, sociological, physical, and psychological.
Environmental stimuli contain the elements of sound, light, temperature, and
physical design. Emotional elements include motivation, persistence,
responsibility, and structure. Stimuli classiﬁed as sociological involve peers, the
self, pairings, teams, adults, and various others. Physical stimuli are the
components of time, mobility, perceptions, and intake. The ﬁnal stimulus is
psychological, which includes the elements of cerebral dominance, analytic

versus global, and impulsive versus reﬂective.

45

The above-mentioned 21 elements of Ieaming style identiﬁed by Price et
al. (1982) aid individuals in determining their Ieaming styles. No person is
affected by all 21 elements, but most people strongly agree to or disagree with
between 6 and 14 of them. If a single element is important to a person, the
response to that element will be a strong like or a strong dislike. If someone
ﬁnds an element unimportant, he or she will not respond knowledgeably when
questioned about that element. By determining which preferences regarding
each of these elements are strong, students and teachers can determine
Ieaming preferences and provide educational opportunities that promote
achievement. This highlights the importance of others, as well as the individual
student, in Ieaming and achievement.

Price et al. (1982) developed the PEPS based on the elements they
thought were important to Ieaming. The 22-item survey identiﬁes how adults
prefer to “function, Ieam, concentrate and perform in their occupational or
educational activities” (p. 3). After students complete the survey, analysis of the
responses reveals personal characteristics that represent how they prefer to
Ieam and work. This survey also takes into account that there is a difference in
how adults prefer to Ieam; this is a component of the other models discussed,

but it is emphasized in the PEPS.

9.9m
In summary, the Ieaming style theorists discussed above all emphasized

different aspects of learning and what is important in the Ieaming process.

45.

 

Witkin described Ieaming style in terms of ﬁeld dependence and ﬁeld
independence, whereas Kolb and Fry highlighted the experiential Ieaming model
as the basis for their Ieaming style (T ennant, 1991). Price et al. (1982)
developed the PEPS, which goes beyond cognitive functioning alone and
identiﬁes environmental factors that the authors thought were involved in
Ieaming. The Myers-Briggs typology is based on personality types. Each model
reﬂects some aspect of the Ieaming process and some characteristics of
Ieamers that are thought to be measurable, are worthwhile to know, and play an
important role in Ieaming. By knowing these characteristics, students and
faculty can manipulate the environment to improve Ieaming, thereby increasing
student achievement.

However, from the theories discussed above, it can be seen that the
concept of Ieaming style is complicated and is based on what a particular
individual believes it to be. It is suggested, therefore, that no one Ieaming style
instrument or theory should be used when attempting to measure Ieaming style.
It is also suggested that students be provided opportunities to identify the ways
they prefer to Ieam so they can better understand the situations in which they
learn best and concentrate on strengthening their ability to Ieam in the situations
they like the least.

Learning style theorists disagree as to whether Ieaming styles are stable
over time, or whether certain aspects of Ieaming style can be changed or
learned and unleamed. Some students seem to be able to adapt their Ieaming

styles in situations in which their preferred style of Ieaming is not useful. For

47

 

ll

example, a student prefers to Ieam alone but is constantly put in collaborative

Ieaming situations. Does or can that student still Ieam effectively? Through

 

time and exposure to collaborative Ieaming, the student might adopt this
strategy and perform well, but still feel most comfortable Ieaming through solitary
endeavors. Can or will the student replace his or her previous preference for
solitary Ieaming with collaborative Ieaming? These questions indicate that

further clariﬁcation is needed about Ieaming style as it relates to the classroom.

lication of Leamin S le Theo to the lassroom

Application of Ieaming style theory to the classroom has led to varied
conclusions regarding the utility of employing a knowledge of Ieaming styles in
an attempt to enhance student achievement and satisfaction in the classroom.
Claxton and Murrell (1987) stated that knowledge of Ieaming styles should be
used not only by students, but also by faculty and administrators to emphasize.
the Ieaming process and the importance Ieaming has in the institution. By being
sensitized to Ieaming styles and the different Ieaming style theories,
administrators and faculty will become more aware of the diversity of Ieaming
styles and their inﬂuence on student Ieaming and achievement. This awareness
will lead to continual evaluation and improvement of instructional settings in
order to meet learners’ needs.

The theories discussed above underscore the need to match Ieamer and
teacher characteristics in order to provide the best Ieaming environment

possible for the student. They highlight the learning styles of students so that

48

V!-

students themselves consciously consider how they think; this enables them
constantly to evaluate situations and make adjustments to aid in Ieaming.
Students may not be able to change the way they Ieam, but by knowing how
they think and process information, students will be aware of their strengths and
weaknesses and seek out help if necessary.

The theories also highlight the need of administrators and faculty to ﬁnd
ways, through research, to improve the Ieaming process so that students are
given the best chance to achieve and excel in the classroom. However, because
there is no common deﬁnition of Ieaming or learning style, the many theories
and measurement tools, the multiple Ieaming situations and students, and the
conﬂicting results of research on Ieaming style have made it difﬁcult to
determine what instructional methods are best used in the classroom.

According to Ieaming style theorists, institutions should provide Ieaming
opportunities based on students’ different Ieaming styles. By knowing students’
Ieaming styles, administrators and faculty can better adapt scarce resources and
curricula to meet those students’ needs. When students and instructors are
aware of individual Ieaming preferences, those strengths can be used to provide
the environment most conducive to academic achievement (Claxton & Murrell,

1 987).

Pintrich and Johnson (1990) stated that “lack of knowledge about
appropriate Ieaming strategies—and lack of motivation to use them—plague many
college students and hinder their learning” (p. 83). The best Ieaming

environments are those that promote optimal Ieaming and teaching situations for

49

both faculty and students (Merriam & Caffarella, 1991). Knowledge of the

Ieaming styles of students and teaching styles of faculty will produce an

 

environment that is more conducive to students’ employing the Ieaming
strategies they ﬁnd most effective.

According to Welbom (1986), Ieaming style alone may not be the ﬁnal
solution to enhancing academic achievement. “The leamer’s ﬁnal success in the
educational setting may be dependent upon the appropriateness of the Ieaming
strategy utilized by the teacher” (p. 14). Teaching style has a strong inﬂuence
on student achievement. Instruction that supports students’ Ieaming styles is
the most effective. Therefore, instructors must be provided with resources to
expand their variety of teaching styles to accommodate students’ Ieaming
preferences. Today this can be observed in the increasing focus on faculty
development services in many institutions and the emphasis on teaching and
Ieaming.

Dunn (1983) stated that individuals’ Ieaming needs vary, regardless of IQ
or achievement. Learning needs depend on “a combination of environmental,
emotional, sociological, physical and psychological elements that permit
individuals-to receive, store, and use knowledge or abilities” (Dunn, 1988, pp.
496-497). When students are taught using resources and strategies that focus
on their Ieaming needs, their achievement is enhanced (Dunn & Bruno, 1985).
Price et al. (1982) stated that, by identifying their own preferences for Ieaming,
both students and teachers can create Ieaming environments that are conducive

to academic achievement.

50

 

‘

(I,

Teachers provide instruction to students based on their own personal
"Ieaming styles. Students are more successful when their Ieaming styles match
those of the teacher. When teachers’ and students’ Ieaming styles are
dissimilar, students will need to work harder so as not to miss some of the
material presented in the classroom. For this reason, teachers should vary their
teaching methods to match the wide array of student Ieaming styles. However,
Claxton and Murrell (1987) stated that, because there are numerous
combinations of students and Ieaming situations, it is not realistic to think that
instructors could possibly adapt their teaching and classroom techniques to ﬁt
the Ieaming styles of all students in a classroom.

Dunn and Bruno (1985) stated that achievement is signiﬁcantly increased
when the instructor's teaching style complements the student’s Ieaming style.
When students identify their own Ieaming preferences and are able to use the
identiﬁed strengths, they can seek out experiences that increase their Ieaming.
According to Dunn (1983), “Students’ preferences, when matched and
mismatched with complementary environments, consistently revealed better test
performances in the congruent conditions and there can be no doubt that
students with strong Ieaming style preferences should be taught in ways that
complement them” (p. 11).

In contrast, Claxton and Murrell (1987) claimed that a mismatch between
teaching and Ieaming styles also can serve a useful purpose in the classroom.
When teaching and Ieaming styles are mismatched, students should be taught

how to use different strategies to overcome the problems they encounter in such

51

a situation. Faculty and administrators should develop programs and instnrction
that help students develop new approaches to use when there is a mismatched
teaching-Ieaming situation. In this way, students can Ieam to overcome
problems and have new strategies to compensate for a mismatch. These new
strategies strengthen student Ieaming, not only enhancing achievement in the
immediate situation but giving additional tactics for students to use in future
Ieaming situations.

Thompson and Crutchlow (1993) countered the thought that students’
Ieaming styles should be matched to the instructor’s teaching style by claiming
that students need a degree of stress to optimize Ieaming—a cognitive
dissonance or disequilibrium. If the student-teacher dyad is matched, then the
stress level may be reduced to such a degree that Ieaming may not be
optimized. Therefore, trying to achieve a perfect match in the teacher-student
dyad may not be the best action to take. Some degree of mismatch is needed,
but there is no indication of the level at which a mismatch becomes a hindrance
to Ieaming.

Thompson and Crutchlow (1993) discussed the match and mismatch
between student and instructor in different terms. Students may experience
different outcomes, not necessarily related to Ieaming styles per se, when there
is a mismatch in instruction and Ieaming styles. For example, if a student and
instructor match in terms of Ieaming-teaching style, the student may feel a
satisfaction that manifests itself in a positive attitude and motivation that

enhances Ieaming. This attitude may have nothing to do with Ieaming style, but

52

 

still can increase student achievement and Ieaming. The authors also
questioned whether students use different styles of Ieaming depending on the
submissiveness of the instructor, and whether Ieaming styles become more
sophisticated through years of study with many different types of instructors.
This sophistication could possibly be the result of an increased ﬂexibility in
students’ Ieaming styles, which allows students to adapt and adjust better to
different teaching and Ieaming situations. Thompson and Cthchlow concluded
that students must be taught to be ﬂexible to accommodate the many teaching-
leaming situations they will encounter.

Merriam and Caffarella (1991) stated that numerous LSls are available,
each of which measures different things. Any particular inventory is inﬂuenced
by how the researcher who developed it conceptualized and deﬁned the term
Ieaming style. What is important, however, is that both faculty and students
should use LSIs. By being aware of their own Ieaming styles, faculty and
students alike may use their strengths and minimize their weaknesses in the
Ieaming situation. LSls are important because they are an avenue for students
to evaluate themselves as Ieamers. This, in turn, allows them to capitalize on
their Ieaming environments or situations.

In concluding this discussion of different Ieaming style theories and types
of measures, it is important to recognize that many faculty and administrators are
confused about and fail to take into account students’ Ieaming styles. If used
correctly, these tools can assist in evaluating teaching practices with the express

intention of improving instruction. Some of the confusion about Ieaming styles

53

 

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exists because there is not just one deﬁnition of Ieaming, and as a result it is
difﬁcult to measure such a concept. The broad range of inventories and the
multitude of students and Ieaming situations make it difﬁcult to measure
students’ Ieaming styles with just one scale.

Faculty must be aware of the complexity of the issue and the multiple
implications of each Ieaming style model. Many faculty resist using such
inventories because no one inventory can or does measure all the attributes
present in the classroom. By understanding the background of LSls, faculty and
administrators can make more informed decisions about which, if any, of the
inventories meet their individual program and classroom needs. Faculty and
administrators may even recognize a need to do their own research to develop
theories and evaluation tools that more adequately reﬂect what they need to
know when diagnosing Ieaming styles of students in their classrooms.

Next the focus turns to research concerning nursing students, college
students in general, and college students’ use of technology, especially
computers and the lntemet! W. This is by no means a comprehensive
review of all studies on Ieaming styles of nursing and other college students, but
a sampling that is intended to demonstrate the difﬁculty of drawing conclusions
because of the inconsistent results and the different instruments used. This
review is intended to give an overall background on how research on Ieaming
style theory has been used in higher education. It also highlights recent studies
that provide insight into Ieaming styles and what they mean to classroom

instruction.

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Research on Learning Sgles of Nursing Students

This review of research on learning styles of nursing students reﬂects the
same confusion found in the literature on learning style theories and inventories.
Multiple tools have been used to measure Ieaming styles, depending on what
particular researchers thought was an important aspect of the classroom or
Ieamer. The Myers-Briggs, Kolb, and Canﬁeld LSls seem to be the instruments
used predominantly. However, even studies using the same measurement
instrument have had conﬂicting ﬁndings and conclusions. Nevertheless, the
ensuing review provides insight into what educators in nursing programs believe
is important and should be measured as a part of Ieaming. It also provides an
idea of how nursing students might react to inclusion of assignments using the
lntemet/WWW in their courses.

King (1986) studied differences between generic nursing students and .
registered nurse (RN) students. Each group aspired to different goals. For the
RNs, participation in school was a means to the ultimate goal-career
advancement. Generic nursing students perceived their education as a means
to an end-to become an RN. The differences in life and Ieaming experiences
had given the RNs greater knowledge about how they learned best. King also
distinguished between generic nursing and RN students in terms of adult
responsibilities and “various dimensions of adult development” (p. 370), using
three of Levinson’s stages of adult development: early adult transition, age-3O

transition, and midlife transition. These stages were described as follows:

55

Early Adult Transition—Separating oneself from the pre-adult world and
beginning to form an adult identity, activities such as questioning one’s
place in the world, and creating an initial adult identity. Students in this
stage focused on the personal issue of “growth and adjustment.”
Individuals in this phase are making and testing preliminary choices for
adult living.

Age 30 Transition—This phase is transitional. Individuals have already

made their choices about love, marriage, family, lifestyles, etc. Many

people focus more on careers and less on their families. The focus was
on becoming “their own person.” Questioning and redeﬁning may come in
the form of life crises such as divorce or death of a signiﬁcant other.

Mid-Life Transition—In this phase the individual realizes that illusionary

dreams of the past are becoming a reality. Neglected parts of the

individual are seeking expression. (King, 1986, pp. 338-340)

King found that the differences between generic and RN nursing students
were not meaningful when comparing life stages of those students, using Kolb’s
LSI. Both groups clustered around Kolb’s Diverger and Accommodator. King
concluded that, because RNs are further into their life cycle, any differences
between students were due to adult development rather than to differences in
Ieaming styles. She stated that the Ieaming styles of the two groups were
similar in some ways because particular professions attract certain types of
Ieamers. This contradicts the belief that Ieaming is purely individualized and
distinct, as Ieaming style theory suggests.

Highﬁeld (1988) also used Kolb’s LSI to compare Ieaming styles of
baccalaureate students in their ﬁrst year of study and in their last year of
college, and of ﬁrst- and fourth-year nursing students. The main Ieaming style

of these student groups was that of Assimilator, which emphasizes a preference

for abstract watching and thinking. This ﬁnding is contrary to that of some

studies in which it was found that nurses tended to be either Accommodators or
Divergers, who deal best with “concrete feeling-oriented situations” (p. 31).
Assimilators are less active in Ieaming and seek assistance to put knowledge
into practice. Highﬁeld attributed the higher percentage of Assimilators in the
two groups to the fact that baccalaureate programs “reward and promote their
students’ reﬂective watching and thinking” (p. 32). The author concluded that
students possibly use more than one Ieaming style, which would explain the
differences between the two groups.

Beeman (1988) cited the need to deﬁne the Ieaming needs of individual
basic and baccalaureate nursing students in order to maintain innovative
programs. “Faculty support and commitment to the unique Ieaming needs of
adults can spell success or failure for a basic baccalaureate program that admits
RNs” (p. 370). Beeman recognized the individual needs of students in areas of
professionalization and socialization and advised that educational programs
need to accommodate students in all aspects of these areas.

McCabe (1983) studied the Ieaming styles of nursing students and
identiﬁed the need to build on student strengths. To do this, both students and
teacher must know their own teaching and Ieaming preferences. By identifying
preferred Ieaming styles of students, instructors can alter their teaching style to
meet students’ needs and hence facilitate achievement.

Meeting the needs of RN students was the focus of a study in which
satisfaction of RN students was evaluated in a clinical setting (Ryan, 1985).

Ryan evaluated an attempt to “package” individual student needs in order to

57

 

EH

obtain the best clinical experience possible for the students. Results of this
clinical packaging showed high RN satisfaction, as indicated by clinical and
teacher evaluations. Ryan recognized the need of faculty to be ready to try new
ideas such as this, based on the needs of individual students.

Ostrnoe, Van Hoozer, Scheffel, and Crowell (1984) examined the
Ieaming-strategy preferences of baccalaureate students. These students
preferred Ieaming strategies that were directed, organized, and did not involve
student participation. Students in their last nursing course expressed less
preference for nontraditional nursing practices, whereas beginning students
preferred a wider scope of Ieaming strategies. In the beginning group, not one
Ieaming strategy was ”never preferred” (p. 29).

In 1985, Lassen described senior-level nursing students as being capable
of selecting Ieaming situations that were congruent with their individual Ieaming
styles. The author stated that nursing curricula should provide for “sequential
Ieaming, perhaps self-paced, whereby each student may be free to sample a
variety of Ieaming techniques to achieve the stated course objectives” (p. 27).
Using an LSI, Lassen concluded that students Ieam by a variety of methods,
depending on the circumstances of each Ieaming experience.

Merritt (1983) used both the Kolb and Canﬁeld Ieaming style models to
study adult Ieamers. She hypothesized that generic, adult nursing students
would prefer directed Ieaming over self-, goal-directed Ieaming. The opposite
was hypothesized for RN, nontraditional students. Merritt’s ﬁndings did not

support these hypotheses, nor did the preferences of baccalaureate nursing

58

 

students in this study support the ﬁndings from previous research. Merritt
concluded that Ieaming differences between adult RN and adult generic
baccalaureate nursing students could not be determined from her study.
However, based on the study ﬁndings, Merritt proposed six differences between
adult RN and adult generic students.

The ﬁrst proposition was that RN students were more likely than generic
students to dislike traditional Ieaming environments and methods. Second,
nontraditional and traditional Ieamers preferred structured environments with
content presented in a logical and clearly deﬁned manner. The third proposition
concerned the need for both passive and active Ieaming activities combined with
direct contact with course content. Next, Merritt discussed both traditional and
nontraditional students’ lack of preference for goal setting, saying that neither
group aspired to competitive situations with instructor control. Last,
nontraditional Ieamers did not “prefer instruction that uses reading modes, but
compared to traditional adult Ieamers, [were] more positively inclined toward the
reading mode” (p. 372). From these propositions, Merritt concluded that there is
a need for different teaching-Ieaming methods for “younger-aged versus older,
experienced adult Ieamer groups” (p. 373).

Thurber (1988) found more similarities than differences when comparing
RN students in two types of baccalaureate-completion programs. The author
discussed the need to adapt baccalaureate programs to meet students’ Ieaming
needs. Citing the fact that bachelor of science (BS) programs are mere images

of basic RN programs, Thurber cited the need for BS programs to be more

59

ﬂexible and adapted to student needs in order to survive, and to provide nurses
to lead the profession in the future. Nursing educators need to assess the
needs of RN students more accurately and develop programs that are
individualized and focused on meeting those needs. Meeting the needs of RNs
will enhance their satisfaction and achievement.

Cranston and McCort (1985) distinguished between cognitive style and
Ieaming style, saying that cognitive style is concerned with the way a person
“receive[s] information or gain[s] meaning from one’s environment” (p. 136).
Learning style, on the other hand, focuses on an “individual’s attitude toward
peers, instructors, teaching methods and Ieaming” (p. 136). Studying students
in an associate degree program, Cranston and McCort found no significant
differences in achievement between the cognitive style group and the Ieaming
style group when appraising performance. The researchers concluded that both
cognitive style Ieaming style should be determined to better assess the Ieaming
“processes” of students.

In 1995, Rakoczy and Money used Kolb’s measure of Ieaming styles in a
three-year longitudinal study of a diploma-nursing program. They found that the
nursing students in the study were concrete Ieamers and needed concrete
Ieaming experiences about which they could then think and incorporate feelings.
The students in all three years were Assimilators, similar to the results found by
Highﬁeld (1988) but unlike the Accommodators and Divergers found by King
(1986), who liked “doing and watching.” This style changed very little over the

three years. Rakoczy and Money concluded that “teachers should implement

60

teaching strategies that promote inductive reasoning and organize disparate
observation into an integrated explanation” (p. 73).

The preceding discussion highlighted some of the research that has been
done on nursing students. It also demonstrated the conﬂicting ﬁndings from
research on Ieaming styles, perhaps resulting from the use of different
inventories and diverse comparisons to Ieaming styles. This underscores an
important fact to remember when attempting to understand Ieaming styles: that
the Ieaming styles of each group of students will differ, depending on the
classroom situation. Differences exist within and among groups of students,
making it impossible to prescribe particular instructional strategies and making it
necessary to measure the Ieaming style of each group of students entering an
instructor’s classroom and the type of Ieaming situation in that classroom.

If the Ieaming styles of nursing students do vary, how will these students
react to inclusion of assignments using the lntemet/WWW in traditional
programs and courses in nursing? Will their Ieaming styles match this type of
instruction? These two questions have implications for teaching and Ieaming on
the lntemet because nursing students have not only different Ieaming styles, but
also diverse backgrounds in the use of computers and the lntemet. Some are
more comfortable than others in such Ieaming situations, possibly due to comfort

gained from previous use of the technology.

61

Research on Learning Styles of Students in Disciplines
Other Than Nursin

The review of research on Ieaming styles continues with a discussion of
studies on the general population of higher education students. Again, rather
than being a comprehensive review of studies that have been completed, the
focus is on efforts that have gone beyond simply deﬁning the Ieaming styles of a
speciﬁc groups of students at a particular time. Longitudinal studies were found,
concerning how Ieaming styles might change over time. This review also
highlights weaknesses in Ieaming style research; for example, gender, race, and
culture do not seem to have been taken into account in developing LSls. This
raises the question whether measures of learning style, like those of IQ, are
biased with regard to gender, race, and culture.

Farr (1971) studied 72 college students and found it was advantageous
for them to Ieam and be tested in their preferred modality. Farr stated that I
individuals can predict the way in which they will be able to achieve superior
academic performance. It is therefore imperative that educators sanction
alternative Ieaming modalities, allowing students to Ieam in their preferred
mode. This study is not unlike many others that have been done on college
students; however, Farr did generalize “college students” and did not seem to
consider other factors such as racial and cultural diversity.

In a study of 100 college students, Domino (1970) found that students
who were taught in ways in which they believed they leamed better scored

higher on tests, factual knowledge, attitude, and efﬁciency than those taught in a

62

 

manner dissonant with their beliefs; Cafferty (1980) found similar results when

 

comparing student-teacher pairs. The better the match between the student’s
and teacher‘s style, the better the student’s grade point average. Conversely,
when there was a mismatch between the student’s and teacher’s style, the
greater the mismatch was, the worse the student outcome.

In a rare qualitative study, Ven'nunt (1966) found that the students in his
sample exhibited a great variety of Ieaming styles. However, he concluded that

the Ieaming functions that are not carried out by the students are often

perceived by them to be not their responsibility, but as the tasks of
instruction. Mental models of Ieaming and Ieaming orientations inﬂuence
the way students interpret, appraise and use instructional measures. The
effect of external regulation devices, such as questions, assignments,

Ieaming objectives and the like, is dependent on the interpretations and

appraisals students give to them. (p. 45)

Learning styles, then, are dependent on students’ intemal and external
mental models. If students view a Ieaming task as internal, they will take
responsibility for it. However, if students view the assignment or Ieaming as
external, they will expect it to occur as a part of the teacher’s instruction. Thus,
students must be taught to internalize more Ieaming activities so that when
instruction does not include some external Ieaming activities, students will take
responsibility and perform those activities because they have been internalized
(Vermunt, 1996).

Vermunt (1996) said this means that instructiOnal methods should include
those aspects the students view as external to their own Ieaming. According to

Vermunt, students do not like the teaching of rote facts; therefore, he said,

instructors should teach for meaning. However, this can be done only when the

63

teacher knows the Ieaming styles of his or her students. Based on the Ieamers’
needs, then, instruction can be devised that contains activities the Ieamers
consider external. Learners should be taught how to incorporate more external
Ieaming activities so that those activities become internal. Vennunt was not
clear about how this occurs, whether more internal activities are included as
students progress in higher education, or how instructional activities should be
changed as students progress from a more external mental model to a more
internal one. Here, Vennunt challenged the long-held belief that individuals’
Ieaming styles are fairly static and unchangeable. If Ieaming style is actually
dynamic, this may have important implications for student development and
referral for study skills.

In a rare longitudinal study, Pino, Geiger, and Boyle (1994) challenged
the prevalent belief that Ieaming styles are static. Using a longitudinal design,
the researchers tracked students’ Ieaming styles as they progressed through
their years in higher education. They cited numerous studies in which it was
found that, not only did Ieaming styles differ among students and between
disciplines, but also that students’ Ieaming styles changed from the freshman to
senior year in college. This implies that students mature over the four-year
period, necesSitating diverse teaching styles, depending on students’ class level.
However, the researchers found conﬂicting results.

Pinto et al. (1994) concluded that some aspects of Ieaming style may be
fairly stable, whereas others will change. One reason the authors offered for this

inconsistent outcome is that students in this age group (18 to 24 years) have not

64

fully developed their Ieaming style preferences by the time they reach college.
Learning styles, then, metamorphose, but to what extent and how is not known.
This ﬁnding has implications for teaching students, not only in diverse
disciplines, but also in different years in college. For example, if freshmen and
sophomores are given much active experimentation (Kolb), they may not be
ready or able to engage in such activities because they have not matured
enough to work at the “what if” level.

In similar studies cited by Pinto et al. (1994), college students increased
their abilities in abstract experimentation as well as abstract reasoning as they
progressed through their college years. The amount of change that took place
was not speciﬁed, and more research is needed in this area. The effect of
discipline-speciﬁc knowledge on the amount of change in student learning styles
through the years in higher education also is unclear. In conclusion, the
researchers cautioned that it is difﬁcult to apply generalizations to all students in
all disciplines because students in diverse disciplines often exhibit varying
Ieaming styles.

In their study of agricultural students, Torres and Canno (1995) found that
Ieaming style is an important variable in teaching students to think critically.
They found that 9% of the variance in students’ critical thinking was attributable
to their Ieaming styles. The authors went on to state that even though 9% does
not seem like a lot, it actually is a signiﬁcant amount of variance. It is signiﬁcant
because there are multiple variables that affect critical thinking, and for just one

factor to account for 9% of the variance is very meaningful. Therefore, if

65

educators want to instill in students the ability to think critically, they must have a
knowledge of Ieaming styles. This includes identifying teachers’ and leamers’
styles, and incorporating teaching and Ieaming methods that optimize those
styles.

Matthews (1994) investigated Ieaming styles in various disciplines in
higher education and considered gender and cultural inﬂuences on those styles,
inﬂuences that have not been widely discussed in the literature. Matthews
stated that those assessing Ieaming styles must examine the inﬂuence of race
and gender on those styles in order to provide equality in instruction and to
counsel students for placement in particular disciplines. Using the Canﬁeld
measure of Ieaming styles, she found that, in mathematics, women tended to be
more independent in their Ieaming styles. In business, both men and women
were conceptual in style, and in the social sciences and education, women
tended to be more conceptual and independent. Men and women in science or
humanities differed little in Ieaming styles as compared to those in other
disciplines. Matthews’s ﬁndings suggest that there is a difference in Ieaming
styles between men and women. An implication of this ﬁnding is that educators
in disciplines that attract primarily men need to change their teaching techniques
to attract more women to those programs. The same is true for programs that
historically have attracted women. To attract men, teaching styles in those
programs will need to be changed.

When Matthews looked at racial differences within disciplines, she found

that African Americans and Caucasians in mathematics, science, business, and

66

social science differed signiﬁcantly in their Ieaming styles. In mathematics and
science, African Americans had more conceptual styles, whereas Caucasians
favored applied styles. No signiﬁcant differences were found between the races
in humanities or education. An implication of these ﬁndings is that African
Americans might have problems in disciplines that have been composed mainly
of Caucasians.

Matthews’s study demonstrates the need to include gender and racial
aspects in Ieaming style inquiries. Such inclusion will aid in understanding how
Ieaming styles of diverse groups differ and to provide instruction based on those
styles.

Two years later, in a four-phase study of 2,000 college students,
Matthews ( 1996) looked at differences in students’ Ieaming styles using
Canﬁeld’s measure. She found that, in general,

First-year students at colleges and universities preferred social and

conceptual styles of Ieaming to other styles. This ﬁnding varied with

subgroups, however. Young women favored the conceptual styles more
than did young men on the applied to conceptual continuum. On the
other hand, young men preferred the social styles more than did young
women on the social to independent continuum. Blacks chose conceptual
to independent styles more frequently than did Whites. . . . Students with
applied styles performed higher in school and scored higher on the

standardized test (SAT) than did students with other styles. (p. xv)

Matthews (1996) also investigation college retention and Ieaming styles.
She found no relationship between white men’s Ieaming styles and retention, but

she discovered that white females with an independent Ieaming style more

frequently stayed in college. Black females categorized as social/applied on the

67

Canﬁeld LSI and black males with independent and independentlapplied styles
remained in college less frequently than did those with other Ieaming styles.
Matthews (1996) also found that there was an association between social
and family factors and students’ Ieaming styles. In general, more conceptual
Ieamers tended to be from large families. The father’s educational level, but not
the mother’s, also appeared to be associated with Ieaming styles. Speciﬁcally,
students whose fathers did not have a college education tended toward more
conceptual than applied Ieaming styles. Conversely, those whose fathers had a
college education were more applied than conceptual in their style of Ieaming.
Matthews concluded that the ﬁndings from her study indicated that there are
many factors associated with student Ieaming styles and that faculty and
administrators must consider all facets of students when attempting to instruct

them.

Technology. the lntemet/WW and Learning Sgles

The focus of this section is studies of Ieaming styles and the use of
technology (computers, computer-aided instruction—CAI) and the lntemet in
teaching and Ieaming. Computers and CAI are included in the discussion
because students need to use computers when accessing the lntemet. If they
are not comfortable using computers or do not have Ieaming styles that are
suited to using computers or surﬁng the lntemet in different instructional
settings, their Ieaming may be hampered. These students may need extra

assistance, introductory courses in using computers and the InternetIWWW, and

68

more patience and time when using computers and the lntemet as learning
techniques.

Davidson, Savenye, and Orr (1992) used the Gregorc theory as a
measure of Ieaming styles in their research on student Ieaming styles and
instruction in a course in computer programming. Students who were found to
have an Abstract Random (AR) Ieaming style had difﬁculty with the linear and
logical programming and computer logic needed to work with computers during a
project designed to teach BASIC programming. Those classiﬁed as Abstract
Sequential (AS) Ieamers had higher scores than the AR Ieamers. The
researchers said this was probably because AS Ieamers were able to
understand the linear aspect of programming and computer logic. They
concluded, “Both types of Ieaming styles were inﬂuenced by their preferences
for one group, to their detriment. That is, those students who had high
preferences for loosely structured tasks and courses did not fare as well in
performance as did those Ieamers who liked structure” (p. 356). Davidson et al.
recommended that more time be spent on AR students, giving them instruction in
computer logic and linear programming before beginning course work. They
emphasized the need to adapt instruction, teaching styles, and course work to
assist students with various Ieaming styles in any classroom.

Logan (1990) studied the online behavior of people who used MEDLINE
for online searching. Kolb’s LSI, the Remote Associates Test (RAT), and the
Symbolic Reasoning Test (SRT) were used in the study. The sample included

students involved in a graduate program in Library and Information Studies who

69

had minimal exposure to online searching techniques. The largest group of
Ieamers comprised Divergers, whom Kolb (as cited in Logan, 1990) described
as being “creative thinkers, and having as their greatest strength imaginative

ability' (p. 505). Accommodators made up 22% of the sample, Assimilators

24%, and Convergers only 9%. Although the ﬁndings were inconclusive overall,

they did indicate that each type of Ieamer performed online searches in a
different fashion. “Assimilators as a group spent more time online, issued more
commands, keyed more descriptors, completed more cycles and printed more
references than any other group. Accommodators, on the other hand, had the
lowest mean scores on all measures except descriptors” (p. 507). Assimilators
had higher scores on reﬂective observation and abstract conceptualization,
whereas Accommodators were high in concrete experiences and active
experimentation.

Logan (1990) did not draw any conclusions about what these ﬁndings
meant, but they could have implications for students searching both databases
and the WWW, which is also very scattered and nonlinear, does not appear in
logical order, and requires active experimentation. Learning on the lntemet is
unlike computer programming, which is linear and logical. Assimilators may
have skills that are better suited to such abstract activities, thus making online
searching of databases and the WWW more suited to their Ieaming styles.

Clariana (1997) studied three cohorts from 13 to 21 years of age. Using
Kolb’s LSI, the researcher found that when CAI was used over time, students’

Ieaming styles did change. There was a shift from abstract conceptualization

7O

and active experimentation to concrete experience and more abstract
experimentation. The change in Ieaming style when students are exposed to
CAI over time may be to a style counter to what is needed in traditional
classrooms. But again, there is evidence that students need skills or styles
different from those required in traditional Ieaming situations when they employ
this new technology.

Using Gregorc’s model of Ieaming styles, Ester (1994) found in a study of
CAI that abstract Ieamers achieved better in lecture situations, whereas
concrete Ieamers preferred to use computers and simulations. This ﬁnding was
similar to Davidson et al.’s observations of students in computer programming
and logic. However, Davidson et al. found a distinction, not so much between
concrete and abstract Ieamers in computer programming and logic, but between
the sequential and random nature of assignments. In contrast, in Ester’s study
on CAI, a difference was found between concrete and abstract Ieamers. This
demonstrates that, not only do students’ Ieaming styles make a difference, but
also what is being studied. Different students will perform differently in various
Ieaming situations (i.e., computer programming versus CAI).

Further, Ester (1994) found that concrete Ieamers did just as well in
lecture as in CAI. On the other hand, abstract Ieamers performed well only in
lecture situations. The implication was that if students could identify concrete
Ieamers, who did well on CAI, they could then concentrate on assisting abstract

Ieamers in using CAI.

71

Discussed thus far have been studies that focused on Ieaming style and
use of computers or the WWW, employing the similar theories of Kolb and
Gregorc. In Kaczor and Jacobson’s (1996) survey of lntemet users, some
questions arose that have implications for conducting research on Ieaming
styles and use of the lntemet. Kaczor and Jacobson found that, when students
learned on the lntemet, they did so in a solitary environment, unlike a traditional
classroom setting. Does this solitary aspect of working with the lntemet make it
difﬁcult for students who prefer more cooperative and collaborative Ieaming
environments to use this medium for Ieaming? This aspect of Ieaming on the
lntemet and WW would reﬂect instructional and classroom factors such as
those measured with Canﬁeld’s LSI and Price et al.’s PEPS.

Kaczor and Jacobson (1996) also concluded that, when instructors
include lntemet assignments in course work, other aspects of student Ieaming
must be taken into account. Some students may need instruction before being
given lntemet assignments, to Ieam not only how to navigate around the Web,
access the Web, or use Web browsers, but also how to discriminate between
good and bad information that is found on the Web, according to their individual
learning strategies.

From this review of studies on the use of technology and the lntemet, it is
evident that students with varying Ieaming styles do have different experiences
using such technology. Therefore, when instruction and Ieaming are provided
on the lntemet, students’ Ieaming styles must be taken into account. Using

these technologies has both random and sequential aspects, abstract and

72

concrete qualities, and the aspect of Ieaming alone versus Ieaming with others,
which may be contrary to traditional classroom settings. Learning styles that are
effective in traditional classrooms might not be effective in using the lntemet,

computers, and computer applications.

9W

Studies have indicated a signiﬁcant increase in academic achievement
when students’ individual Ieaming traits are matched with complementary
teaching styles, resources, and environments. Likewise, research in nursing
education has shown that curricula and teaching techniques should complement
individual students’ Ieaming styles. Thus, when working with generic and RN
nursing students, nursing educators should identify differences in students’
motivation and Ieaming preferences so as to provide curricula and teaching
techniques that complement the many Ieaming preferences of their students.

Consensus does not exist with regard to the stability of Ieaming styles.
Recent studies have indicated that some aspects of Ieaming styles may indeed
change as students progress through higher education (Pinto et al., 1994).
However, because there are so many different teaching styles and Ieaming
environments, students cannot change their Ieaming styles to correspond to
every situation that might arise. Claxton and Murrell (1987) did not agree that
Ieaming styles can be changed, but they claimed that, by being aware of their

own Ieaming styles, students can maximize their strengths and work on their

weaknesses.

73

Each Ieaming style theory discussed in this review focused on a different
aspect of Ieaming style. The lack of a single theory of Ieaming style makes it
difﬁcult to compare results from various studies. Only a few studies, such as
longitudinal efforts, controlled for cohort differences to determine whether
students’ Ieaming style did in fact change as they advanced through nursing
programs. Most of the studies, however, were one-time cross—sectional studies
of groups of students of various ages, with a variety of backgrounds and
experiences.

The literature on Ieaming styles has provided little information on how
students’ Ieaming styles relate to their evaluation of Ieaming, and whether
students with particular Ieaming styles prefer to use technology such as the
lntemet. This appears to be a serious gap in the literature on Ieaming styles,

not only of the general population but also of nursing students.

Hypothesis Generation, Conceptual Framework,
and Assumptions

Based on the review of literature, information on Ieaming styles, Ieaming
style instruments, and experience of the researcher, the purpose and
subsequent hypotheses for this study were generated. Assumptions that guided
hypothesis generation were based on the ambiguity and abstractness of using
the lntemet, experience working with students for 13 years, the conﬂicting
results of Ieaming style research, the many levels and complexities of Ieaming
styles and their inventory measures, and the technical nature of using the

lntemet and computers. Therefore, the researcher developed assumptions that

74

guided the study. First, the researcher developed assumptions about Ieaming
styles guided by the review of literature and personal experience. For this study,
it is believed that Ieaming styles do exist.

It is also believed that Ieaming is multidimensional, as are Ieamers, and
cannot be measured or assessed by any one of the existing Ieaming style
inventories alone. So any study should include measures on more than one
level of the Ieaming style onion (Claxton & Murrell, 1987). Use of the lntemet is
considered a Ieaming/instructional method as those discussed in the
instructional-preference and combined models of Canﬁeld (1994) and Price et al.
(1991). However, the use of the lntemet was also documented in the review of
literature as containing both concrete and abstract aspects, aspects measured at
the infonnation-processing level in the Ieaming style inventories of Gregorc
(1994) and Kolb (1984). In addition, the issue of random/sequential lends itself
to the Gregorc model, which measures both Random versus Sequential and
Concrete versus Abstract aspects of Ieaming styles.

The review of literature did indicate that the abstract nature of the lntemet
posed problems to some students who did searches on the lntemet or used CAI
(Davidson et al., 1992). Use of computers also posed problems for students in
computer courses where there was course work that was more sequential, and
problems for others if the work was more random in nature (Ester, 1994).
Therefore, the researcher assumed that this same abstractness and ambiguity
would differ among students, depending on their Ieaming styles when using the

lntemet as part of a traditionally taught course. For example, students who are

75

Concrete and Sequential (Gregorc, 1994) could ﬁnd the abstract and random
nature of the lntemet difﬁcult to understand and have feelings of getting lost in a
maze of Web sites and multiple Web pages. Therefore, the Gregorc Style
Delineator and the Canﬁeld LSI were used to measure the construct of Ieaming
styles for the study.

Another assumption guiding the research is that Ieaming has an aspect
that can cause negative feelings when new instructional techniques are
introduced that are not in the leamer’s preferred way of Ieaming. This has been
documented by several researchers who cited the need to closely match
Ieaming and instructional methods to the Ieaming styles of students (Claxton &
Murrell, 1987; Price et al., 1991; Tennant, 1991; Thompson & Cnrtchlow, 1993).
This was noted by the researcher when students had a problem using computers
while using computer-assisted testing (CAT). Some students felt angered. They
thought they would do better on a test if it was given on paper because they
were better able to ﬂip back and forth to compare similar or related questions.
They were comfortable doing a pencil-and-paper test. The presentation of the
same type of test on a computer decreased their comfort level. This appeared to
interferewith their taking the test, causing enough stress to bring out very
emotional reactions. Whether it was real or imagined, students thought they did
worse on a test because it was on the computer, and this caused negative
feelings and emotions.

Literature on stress and anxiety (Roy, 1984; Selye, 1974) would explain

the feeling students have when performing something new, like taking a test on

76

the computer or using the lntemet for course completion. When confronted with
new and unfamiliar stimuli, people tend to develop some types of feelings that
vary in intensity. The stimuli must, however, reach a certain point before a
person experiences uneasiness or feelings that are uncomfortable.

Up to a certain point, the stimulus might not interfere with the person’s
actions and thoughts because the individual has innate coping mechanisms or
has acquired new coping mechanisms through past experiences (Roy, 1984). A
certain level of anxiety is needed for people to perform well. However, when that
stimulus becomes too frequent, becomes too intense, or comes with multiple
stimuli, overload might occur. Intense feelings might arise, making it difﬁcult to
concentrate, function physically, or even perform simple tasks. Learning may be
hampered or even avoided because the person tries to decrease the feeling
through avoidance or even dropping out of the situation.

In studying students using CAI in math courses, O’Neil (1970) found that
as stress increased, performance decreased. Similarly, Spielberger (1970)
found that anxiety was a predictor of performance when students used
computer-assisted Ieaming (CAL). Tatsuoka (1978) studied students in the
military and found that stress of Ieaming led to less favorable achievement in
computer-based technical training.

The above-mentioned ﬁndings could explain why, in situations where
there is a discrepancy between their preferred Ieaming style and the mode of
instruction, students would feel frustrated, angry, and uncomfortable. The

degree of the discrepancy and individual coping skills would determine how the

77

 

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student is likely to cope with and adapt to the new stimuli (Roy, 1984). Other
stressing stimuli occurring simultaneously, such as other course work, family
problems, and so on, might contribute to a student’s inability to cope with the
discrepancy between the preferred way to take a test and the new way involving
a computer. Based on this, the researcher assumed that the mismatch of
Ieaming strategies and the Ieaming style of students can, and will when the
discrepancy (stimulus) is too large or too frequent, develop negative feelings
that can hamper Ieaming and even lead to physical and emotional problems
(Dabney, 1995; Fresno, 1998).

These negative feelings may be minimal or consuming to the student,
depending on how he or she has learned to cope and the degree of mismatch
between the student’s Ieaming style and the test on the computer. Therefore,
there should be some form of correlation between students’ Ieaming style and
their comfort using the lntemet or computers. The greater the mismatch of
Ieaming styles and use of the lntemet/computer, the greater the discomfort
should become.

The ability of students to adapt to or cope with mismatches in their
Ieaming styles and different types of Ieaming/Instructional techniques leads to
another assumption made in this study. Kolb’s Experiential Theory states that,
by being exposed to new material such as the new Ieaming techniques and
strategies involved in using the lntemet and CAI, students will eventually
internalize their new strategies. The once-new skill of CAT will become a part of

their Ieaming strategies, the discrepancy (stimulus) in their Ieaming style that

78

 

 

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lntemet I
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familiar,

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caused the stress will no longer exist, and coping skills will have been acquired
to deal with the stimulus effectively through repeated use. Hubbard (1998).
found a need for ongoing training to decrease anxiety among persons using the
lntemet in course work. Eventually, ongoing training or experience will decrease
stimulus response and will not elicit a negative response bemuse it is now
familiar, internalized, and even performed without conscious thought by the
person (Kolb, 1984).

The researcher assumed that students can, over time, adjust to new
Ieaming situations. So a person who exhibits the concrete-sequential Ieaming
style of Gregorc might not feel the discrepancy between the random/abstract
lntemet because of the role that past experience has played when using the
lntemet at home, at school, or at work. Even though students would rather have
the concrete book, with well-ordered assignments and instructor guidance, past
experience has given them the knowledge and resources they need to cope with
or adapt to the new stimulus. Using the lntemet or CAI now does not cause a
stimulus great enough for them to feel any great discomfort or negative feelings
even though the lntemet does not ﬁt well within their preferred Ieaming style.
This would explain the debate among theorists as to the stability of Ieaming
styles over time. The negative feelings caused by discrepancy between the use
of the lntemet/computers in course instruction and Ieaming styles should
diminish with repeated exposure. Therefore, this researcher sought to measure
the relationship between students’ feelings (comfort) about using the technology

and the amount of experience they had using computers and the lntemet.

79

 

 

 

com;

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his

Experience performing skills causes internalization of the skills (Kolb,
1984). As people age they acquire new coping skills through their experiences
to deal with new stimuli. It is also possible that older students have abilities to
adapt to new situations, including Ieaming situations, that younger, less mature
students have not yet acquired (Clariana, 1997; King, 1986; Pinto et al., 1994).
Conversely, older students might not feel as comfortable using the lntemet and
computers because of the length of time away from the classroom. Their
experiences in school might not have included the use of such technologies;
thus, they have not had the chance to adapt this technology to their Ieaming
styles as younger students have. Edelson (1998) found that adult Ieamers
experienced discontinuity of time, space, and action when using the lntemet.
Anxiety was observed in this discontinuity and in the frustration in dealing with
lntemet providers and equipment limitations.

Cross (1981) also described different motivations and skills of adults that
most younger students have not yet developed. Cross (1981), Merriam and
Caffarella (1991), and King (1986) also highlighted differences between adults
and younger students in the area of adult development, life stages, and maturity.
So it is of interest whether there is a relationship between the age of the student
and comfort using the lntemet and computers. In this study, students were
viewed not only by age, but categorized as traditional (24 years and younger)
and nontraditional (25 years and older). Do these differences in motivation, life

stages, and coping mechanisms help in the use of the lntemet in the classroom?

80

In conclusion, the researcher developed these assumptions based on
personal experience, Ieaming style theory, and a review of the literature. These
assumptions helped determine the direction of the study, instruments used to
measure the concepts, hypotheses, and data-analysis methods. The study
design, methods, and procedures are further delineated in Chapter III for the
reader to gain a better understanding of what was done. Chapter IV contains an
explanation of. how the data were analyzed, as well as the results of hypothesis

testing and the qualitative data analysis.

81

 

CHAPTER III
DESIGN AND METHODOLOGY

W

The researchers primary purpose in this study was to determine whether
there is a relationship between the Ieaming styles, computer/lntemet
experience, and age of selected nursing students, and those students’ comfort in
using the lntemet/WWW in a traditional course in Nursing Pharmacology. The
researcher also sought to determine what the students perceived as factors that
frustrated them or made them uncomfortable when they completed course
assignments on the lntemet/WWW. An additional purpose was to determine
whether any suggestions could be made for teaching and Ieaming.

This chapter begins with an explanation of the research design, followed
by a restatement of the research questions and hypotheses. Next, the
methodology used in carrying out the study is described. Characteristics of the
convenience sample are discussed. The instrumentation and procedures used

in the study are described, as are the Web assignments completed by the

subjects.

82

Research Design

A quantitative and qualitative design was used in carrying out the study.
Information about subject selection, demographics, instruments used,

procedures, and Web assignments is presented in this chapter to better

 

elucidate the research design and methods of the study.

Results of the data analyses are presented in Chapter IV. Quantitative
methods were used for testing the ﬁrst three hypotheses; these methods
included parametric and nonparametric correlation and regression. Data
analysis included the use of correlations between the total score on the Comfort
Instrument and the Canﬁeld LSI and the Gregorc Style Delineator. Hypotheses
2 and 3 were tested using correlations. Student age, experience in using
computers, and experience in using the lntemet were also correlated with the
total score on the Comfort Instrument. Demographic data are presented in the-
form of descriptive statistics (frequencies, means, medians, and standard
deviations).

The answers to an open-ended question found in the Web assignments
form were evaluated as a means of determining what students thought was
uncomfortable for them and to provide a more speciﬁc and personal evaluation
of how students felt using the lntemet for course work. A description of each of

the quantitative statistical methods is provided in the data-analysis section below

each hypothesis.

83

Research uestions and H theses

The following questions were posed to guide the collection of data for the
quantitative portion of this study:

1. Is there a relationship between the Ieaming styles (independent
variable) of nursing students enrolled in a traditionally taught course in Nursing
Pharmacology and those students’ comfort in using the lntemet/WWW
(dependent variable)?

2. Is there a relationship between nursing students’ personal experience
in using computers and the lntemet (independent variable) and those students’
comfort in using the lntemet/WWW (dependent variable)?

3. Is there a relationship between nursing students’ age (independent
variable) and those students’ comfort in using the lntemet/WWW (dependent
variable)?

In addition, two exploratory questions were posed for the qualitative
portion of the study:

4. What do students perceive as factors that were frustrating or made
them uncomfortable when they completed course assignments on the
lntemet/WWW?

5. Can suggestions be made for teaching and Ieaming?

Null hypotheses were formulated to test the data gathered to answer the
ﬁrst three research questions. They are as follows:

Ho 1: There is no relationship between nursing students’ Ieaming styles
and their comfort in using the lntemet/WWW.

 

Ho 2: There is no relationship between nursing students’ personal
experience in using computers and the lntemet and their comfort in using
the lntemet/WWW.

Ho 3: There is no relationship between nursing students’ age and their
comfort in using the lntemet/WWW.

The preceding hypotheses are written with no expected direction of
results. However, given the study assumptions detailed in Chapter II, the review
of literature, and the personal experience of the researcher, certain expectations
of direction can be surmised.

With regard to Hypothesis 1, the researcher expected to ﬁnd that, for the
four Gregorc mediation channels, those students who were more concrete and
sequential would report less comfort when using the lntemet, which can be
random and abstract. From the Canﬁeld LSI it might be expected that those
students who enjoyed more social Ieaming activities, preferred instructor-
involved Ieaming and instructor-directed activities, preferred working with
people, were more dependent, and preferred more concrete activities would
have less comfort when working with computers and the lntemet.

In Hypothesis 2, the researcher surmised that students with less
experience using the lntemet and computers would report a lower comfort level
than those with more experience using the lntemet and computers. Even though
their Ieaming styles might not match those of using computers and the lntemet
for Ieaming, the repeated exposure had given those with more experience the
abilities needed to work with the technology, as well as the resources to adapt

the technology to their learning styles.

85

For Hypothesis 3, there was no expectation of direction. Older students
who are acclimated to more traditional Ieaming settings might experience less
comfort using the technology. However, with many of the older students holding
jobs, this might not be the case. They might have become very used to using
the technology through their work and families because the technology is so
prevalent. Here again, the older students might also have matured, and
developed more diverse Ieaming styles over time. The use of the lntemet and
computers might not produce any less comfort than that experienced by younger

(traditional) students who have been acquainted with this type of Ieaming in high

school.
M
Subject Selection

There was no random selection or assignment of subjects. Rather, a
convenience sample was used, comprising 41 nursing students enrolled in an
associate degree program in nursing at a four-year university in the Midwest.

F orty-three students started the course, but two dropped out early into the
semester, one because of personal and family obligations and the other due to a
change in major. The group was enrolled in the ﬁrst of two courses in
pharmacology (drugs and their actions in the body). Pharmacology 151 is a
one-credit course that is offered during the ﬁrst semester of the nursing program.

It is one of the ﬁrst nursing courses that students take.

Students could not enter the nursing program until they had completed all
prenursing courses with a grade of C or above. Some of the subjects had
completed all of the prerequisites and been on a waiting list for the nursing
program for two to three years. In addition to the pharmacology class, the
subjects were taking one or two other nursing courses at the time of the study.

The subjects in this study took Pharmacology 151 during the summer
semester. They completed the course in four weeks (two hours per day, two
days per week). The researcher taught the course as part of her teaching load
and had taught the course for several years.

To better describe the subjects, demographic data were gathered through
the Web assignments students completed (described under Procedures). Some
of these data also were used in testing the hypotheses and answering the
research questions.

The subjects were primarily Caucasian females. The average age of the
class was 24.4 years, almost 9 years younger than the average age of 33‘. This
makes the group uncharacteristic of nursing students at this university. National
trends are also higher than this and approximate 33 years, on average. This
fact must be taken into account when analyzing the data because the group
appears to be different from students in other nursing programs. Any ﬁndings
must be viewed in light of these data on the sample.

Demographic data regarding age of sample members and their experience using
computers and the lntemet are shown in Table 2. Frequencies and percentages

of males and females, as well as traditional and nontraditional students, in the

87

sample are shown in Table 3. Additional descriptive information may be found in

Appendix A

Table 2: Subjects’ age and experience using the lntemet and computers.

 

 

 

 

 

 

 

 

 

 

 

N Mean Median SQ
Age 41 24.42 22.00 5.50
Years’ experience using computer 41 5.05 5.00 1.75
Hours per week on lntemet 41 2.83 2.00 3.60
Years using the lntemet 41 3.76 4.00 1.60

 

Table 3: Distribution of subjects by gender and traditional/nontraditional age.

 

 

 

 

 

91 Percent
Female 38 92.7
Male 3 7.3
Traditional 27 65.8
Nontraditional 14 34.2

 

 

 

 

 

Protection of Subjects’ Rights

Permission to conduct the study was obtained from the Michigan State
University Committee on Research Involving Human Subjects (UCRIHS-see
Appendix B) and from the host university. To ensure conﬁdentiality, the names
of participating students and the university are not identiﬁed in this study.
Although students’ names were required on the Web assignments and the

instruments so that the results could be correlated, their names were not used in

88

 

the data analysis. At that time, respondents were assigned numbers to protect

their anonymity.

Instrumentation
Three instruments were used to collect data on the subjects in this study.
They are the Canﬁeld LSI, the Gregorc Style Delineator, and the Comfort

Instrument developed by the researcher.

The Qanﬁeld Learning sgle Inventory

The Canﬁeld LSI was used to measure Ieaming styles of the nursing
students in this study, in conjunction with the Gregorc Style Delineator. Canﬁeld
(1992) described the LSI as “a self-report questionnaire that allows students to
describe what features of their educational experiences they most prefer” (p. 1).
Canﬁeld deﬁned Ieaming style as

the affective component of educational experience, which motivates a

student to choose, attend to and perform well in a course or training

exercise. The LSI is a rationally derived and highly structured instrument
that breaks the motivational component into four major categories

(Condition for Learning, Area of Interest, Mode of Learning and

Expectation for Course Grade). (p. 1)

(A brief description of the LSI scales is included in Appendix C.) Of the LSI
scales, the Peer, Organization, Independence, People, and Direct Experience
scales were used in this study to detect possible differences among students

using the lntemet in course assignments. Form A of the LSI was used; it is the

higher education version, having a seventh-grade reading level.

89

 

The LSI takes approximately 30 minutes to administer, following a brief
explanation of the instrument (see Appendix C). Students rated sets of
descriptors and marked their answers on a bubble scoring form. The completed
forms were then sent to Canﬁeld for evaluation. Norms are given for the LSI,
and scores are reported as percentiles and T-scores (mean = 50, _$_D_ = 10).

Similar to the Gregorc Style Delineator, the Canﬁeld LSI ranks student
responses on a scale from 1 to 4. Students rank their perceptions from most
preferred (1) to least preferred (4). (Due to this similarity, the instruments were
not given together, so as to avoid confusion in completing the instruments.)
There are 30 sets of rankings. Respondents complete the ranking and mark
their answers on a bubble form provided, in a column next to each set of ranked
items. Unlike the Gregorc instrument, the Canﬁeld LSI uses sets of phrases and
sentences to be rank ordered by importance. It even uses short scenarios and
asks students to rank how they would feel, act, or Ieam in certain situations.
Subjects also rank tasks they like to do best, how they like to Ieam best, skills
they think teachers should have, their grade expectations, and feelings
concerning evaluations, among other things.

The completed Canﬁeld LSI instruments were sent to WPS for analysis
(see Appendix C). The completed instruments and report forms for all students
were returned to. the researcher. The instrument itself cannot be included here
because of a usage agreement with the author", however, a sample report form is
provided for referral in Appendix C. In the same appendix is an example of the

directions given to the students and a sample question. Scores on each of the

90

ﬂ \

 

21 scales of the Canﬁeld LSI are reported for each student. A horizontal graph
is presented beside each T—score/percentile for each of the scales. The graphs
demonstrate a student’s score relative to the other 20 scales (see Appendix C).

An overall typology is presented to the student, showing how each of the
T-scores on the 21 scales is used to ﬁgure the student’s summary score. The
subsequent overall Ieamer typology for each student is provided in the individual
reports. A grid containing all of the possible typologies is provided to the
student. The student’s typology is identiﬁed on the grid based on calculations
for each of the 21 scales. There are nine typologies, each of which is explained
in Appendix C, following the sample report. These are given to students for
assistance in understanding their own Ieaming styles. A grid containing all of
the responses the student gave is also contained in the report. Appendix C
contains the address from which readers may obtain the instrument and
documentation for further evaluation.

Reliabilities and validities for the LSI are included in the administration
booklet. (See Appendix C for Form A Split-Half Scale Reliabilities [range from
.95 to .99] and Form A Item Analysis [range from .87 to .98]). Reliabilities were
reported by Brainerd and Ommen (as cited in Canﬁeld, 1992, p. 36) on a sample
of 1,397 students.

Canﬁeld (1992) reported validity in the area of student achievement in
use of computers, stating that a study by Davis “provides evidence of concurrent
and discriminant validity” (p. 38). He stated that “over the last decade, however,

a number of researchers have reported evidence of (a) the power of the LSI to

91

 

discriminate meaningful group differences in Ieaming style preferences, and (b)
the value of matching instructional methods to characteristics of individual

student preferences” (p. 38). Canﬁeld also reported that there is solid evidence
that “the preferences discriminated by scales and sets of scales do relate to the

academic and career choices of those tested” (p. 38).

The r are le Delineator

The Gregorc Style Delineator was used in conjunction with Canﬁeld’s LSI
to determine whether there were differences among subjects in random versus
sequential Ieaming, which was evident in the literature when subjects were
working with computer programming and database searching. The Gregorc
Style Delineator

is based on a Mediation Ability Theory, which states that the human mind
has channels through which it receives and expresses information most
efﬁciently and effectively. The power, capacity, and dexterity to utilize
these channels are collectively termed mediation abilities. The outward
appearance of an individual’s mediation abilities is what is popularly
termed “style.” (Gregorc, 1994, p. 5)

Perception and ordering are the two types of mediation identiﬁed by the
delineator.
Perception is the means by which information is “grasped”; this type is
composed of abstractness and concreteness:
Abstractness—This quality enables you to grasp, conceive and mentally
visualize data through the faculty of reason and to emotionally and
intuitively register and deal with inner and subjective thoughts, ideas,
concepts, feelings, drives, desires, and spiritual experiences. This quality

permits you to apprehend and perceive that which is invisible and
forrnless to your physical senses of sight, smell, touch, taste, and hearing.

92

 

Concreteness-This quality enables you to grasp and mentally register
data through the direct use and application of the physical senses. This
quality permits you to apprehend that which is visible in the concrete,
physical world through your physical senses of sight, smell, touch, taste
and hearing. (p. 5)

Ordering is the way in which you “authoritatively arrange, systematize,
reference, and dispose of infonnation' (p. 5). This emerges as two qualities:
sequence and randomness:

Sequence—This quality disposes your mind to grasp and organize
information in a linear, step-by—step, methodical, predetermined order.
Information is assembled by gathering and linking elements of data and
piecing them together in a chain-like fashion. This quality enables you to
naturally sequence, arrange, and categorize discrete pieces of
information. It further encourages you to express yourself in a precise,
progressive, and logically systematic manner.

Randomness-This quality disposes your mind to grasp and organize
information in a nonlinear, galloping, leaping, and multifarious manner.
Large chunks of data can be imprinted on your mind in a fraction of a
second. Information is also held in abeyance and, at any given time,
each piece or chunk has equal opportunity of receiving your attention.
Such information, when brought into order, may not adhere to any prior or
previously agreed upon arrangement. This quality enables you to deal
with numerous, diverse, and independent elements of information and
activities. Multiplex patterns of data can be processed simultaneously
and holistically. This quality encourages you to express yourself in an
active, multifaceted and unconventional manner. (pp. 5-6)

From these two types of mediation abilities come four distinct transaction
ability channels: Concrete/Sequential (CS), Abstract/Sequential (AS),
Abstract/Random (AR), and Concrete/Random (CR). Therefore, the Gregorc
Style Delineator reveals the perception and ordering abilities people use to
transact in and adapt to their everyday environments. People have the ability to

use one, two, three, or even all four channels. However, most are predisposed

93

 

to use only one or two. The proclivity to use certain channels is natural and
determines how people view and perceive the world.

The Style Delineator allows students to self-score the instrument by
providing row totals and then column totals for the 10 ranked sets. A replication
of the instrument, scoring, and interpretation guidelines are provided in
Appendix D (Canﬁeld, 1994) for a better understanding of the instrument. The
address to obtain the full instrument and other materials is also included.

Each row of the instrument is totaled in four columns next to the 10 sets of
words. Next, the four columns are totaled at the bottom. The four column totals
represent the respondent’s scores for the four mediation channels. A high score
(27 to 40) on any one or more of the four channels indicates that “the qualities
[Mediation Ability] are a powerful means of transaction” for the person for that
channel (p. 14). An intermediate score (16 to 26) means that the person has “a
moderate Mediation Ability and capacity to transact in the channel indicated”

(p. 14). A low score (10 to 15) for any channel indicates that that channel is the
least powerful in terms of mediation qualities.

To interpret the scores, a grid is provided to students, describing the
qualities exhibited by each of the four channels used in the Gregorc Style
Delineator. The grid allows students to better understand their preferred
mediation channel(s). The grid also provides a comparison of the four channels
(CS, AS, AR, CR) in the categories of reality of the world, ordering ability, view

of time, thinking processes, validation processes, focus of attention, creativity,

94

 

and so on. The grid is provided in Appendix D for further evaluation by the
reader.

Gregorc (1982) reported the reliability of his Style Delineator in terms of
internal consistency using standardized alphas. Stability was established using
a test-retest correlation coefﬁcient. One hundred ten adults took the Style
Delineator twice. Alphas for the two administrations were .92 and .92 for the CS
sale, .89 and .92 for the AS scale, .93 and .92 for the AR scale, and .91 and .91
for the CR scale. Correlation coefﬁcients between the ﬁrst and second tests
were .85 for the CS scale, .87 for the AS scale, .88 for the AS scale, and .87 for
the CR scale.

Gregorc (1982) assessed construct validity by interviewing 100
individuals, who indicated that virtually all descriptions were accurate. He
assessed predictive validity by computing correlations. Correlations between
Style Delineator scores and ratings of attributes were .68 and .70 for the CS
scale, .68 and .76 for the AS scale, .61 and .60 for the AR scale, and .55 and .68

for the CR scale.

The Comfort Instrument and Dempgraphic Items

The researcher developed the Comfort Instrument to assess students’
comfort in using the lntemet. The instrument was modeled after one used by
Cairy (1998) in a doctoral study. Cairy did not provide information as to the

reliability of the instrument, but said that its validity was ensured through an in-

95

 

 

depth literature review on the subject and administration to seniors in a bachelor
of nursing program.

The Comfort Instrument (Appendix E) used in this study was modiﬁed
from the one used in Cairy’s research and was based on literature pertaining to
the use and development of affective instruments (Gable & Wolf, 1993) and the
use of bipolar terms to obtain construct validity. While developing the Comfort
Instrument, the researcher addressed. content validity by having an expert review
the items and assist in instrument development (M. Roehrig, personal
communication, 1997). Roehrig has had extensive teaching experience and has
been actively involved in development and administration of psychosocial
instruments. She is also a mental health nurse, has taught nursing for more
than 20 years, holds private counseling evaluation sessions, and has taught
statistics and research for many years, in addition to being trained as a
psychologist.

The Comfort Instrument was given to 56 student volunteers who were
graduating from the associate degree program in nursing at the university at
which the study was conducted. The instrument was given in both Likert and
semantic forms for evaluation purposes and to assess comprehension of the
bipolar terms and the instrument form.

These students were asked to comment on any ambiguity of terms and to
indicate which scale (Likert or semantic) they preferred for describing their
perceptions of comfort. The students also were asked to evaluate the bipolar

scales and to make suggestions as to adding to or deleting any of the scales

96

 

LE

relating to their perceptions. This administration of the instrument was also used
in assessing reliability. The instrument was also given for evaluation to faculty
members in the Department of Nursing, as well as to a statistician to review for
content and construct validity.

Reliability was evaluated using the responses of the above-mentioned
student volunteers. Reliability coefﬁcients are shown in Table 4. The reliability
analysis of the Comfort Instrument indicated that the combined scales had a
Cronbach alpha of .9079. An alpha greater than .60 usually is considered to
indicate internal consistency (Mitchell & Malloy, 1999). Each bipolar scale was
broken down to ﬁnd the best reliability of the instrument, using varied
combinations of the bipolar terms. If the Unsure/Conﬁdent bipolar scale was
deleted from the instrument, the next highest alpha was .92. Similar reliability
results were found when analyzing the Likert scale.

Inter-item correlations on the Comfort Instrument indicated that all
correlations were signiﬁcant at the .05 level (see Table 5). Nineteen Pearson
correlation coefﬁcients were signiﬁcant at the .01 level (2-tailed), and the
remaining two correlations were signiﬁcant at the .05 level (2-tailed).

Student volunteers who favored the semantic scale said it gave them
more options to rate the terms. They thought the Likert scale was too conﬁning
and gave them less latitude in expressing and rating their perceptions. Those
who did not like the semantic scale thought it was less concrete than the Likert
scale, and they said they had trouble rating their perceptions on the analog

scale. They preferred the Likert scale because it was deﬁnite and concrete

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99

(Strongly Agree to Strongly Disagree). Similar pros and cons have been
expressed in the literature on the use of Likert and semantic scales
(Nieswiadomy, 1998; Polit & Hungler, 1995). The two forms of the Comfort
Instrument also were discussed with a statistician, who thought the semantic
scale allowed more Options for data analysis. Based on these assessments, the

semantic-scale form of the instrument was used in the actual study.

Table 5: Reliability coefﬁcients of the Comfort Instrument: Scale alphas.

 

 

 

 

 

 

 

 

 

 

 

 

 

Item Scale Mean It Scale Variance Corrected Item- Alpha If Item

Item Deleted If Item Deleted Total Correlation Deleted
Difﬁcult-Easy 26.1607 69.6282 .7152 .8953
Tense-Relaxed 26.0893 67.4282 .75074 .8905
Stressful-Unstressful 26.1786 63.3994 .8320 .8814
Anxious-Calm 25.6964 67.5244 .7977 .8867
Unsure-Confident 26.5279 73.9970 .4641 .9220
Unpleasant-Pleasant . 25.7500 64.9182 .7677 .8892
32:32:39' 25.8571 67.3974 .7569 .8906

 

 

Number of cases = 56 Number of items = 7

Alpha = .9079

The ﬁnal version of the Comfort Instrument contained seven bipolar terms

(Table 5), which studentsrated on a scale from 1 to 7. Thus, the total score for

the seven bipolar scales could range from 7 to 49. This total comfort score for

each subject was compared with the student’s scores on the Canﬁeld LSI and

the Gregorc Style Delineator.

100

 

r—\

 

In the Web assignments (see Procedures section), students were asked
to respond to several statements regarding demographic characteristics.
Students were also asked to respond to several statements using a semantic-
type scale ranging from Strongly Agree (1) to Strongly Disagree (7). These
statements elicited a range of answers to gain data about subjects’ comfort when
using computers and the lntemet (see Appendix F). Students completed these
assignments on the lntemet. Some of the responses to these statements were

correlated to students’ responses on the Comfort Instrument.

Procedures

Pilot Testing of Web Assignments and Syllabus

Because of the complexity and technical nature of Web-site development,
the researcher asked 33 students who had previously taken the course to
complete the Web assignments and review the Web syllabus. These students
were asked to provide feedback and make suggestions for further reﬁnement of
the multiple Web pages and to make sure the URLs and other technical aspects
functioned properly. Although no real problems were mentioned as a result of
this pilot test, the students did offer suggestions for making the Web pages more

appealing and easier to read (colors, fonts, page size, and so on).

Informed Consent
The researcher gave the students a short explanation of the research and
asked them to indicate their willingness to participate by signing a consent form

(Appendix B). The researcher assured them that their grades would not be

101

 

affected by whether they did or did not participate. However, the Web
assignments were a part of the course to get students to use the Web syllabus
and gain knowledge of lntemet sites on pharmacology that they would use in the
course and in future professional activity. If students did not complete the LSIs,
the researcher assumed they did not want to participate in the study. For those
students, information from the Web assignments was not used in the study, but it
was used in evaluating the course and determining whether Web assignments

would be used in succeeding semesters.

Data Collection

To pass the course, subjects were required to complete four activities
using the Web. The activities were included in a Web syllabus created by the
researcher, which was based on the course syllabus also developed by the
researcher. The syllabus was published on the Web in January 1998 through
two different servers, with access through a URL address. The assignments
were accessed through the Web syllabus, using the Web Assignments hyperlink
and a URL address set up speciﬁcally for the assignments. A replica of the Web
assignments is provided in Appendix F, along with directions for completing the
assignments.

The ﬁrst assignment was given the ﬁrst day of class. The home page of
the syllabus contained information about how to use and navigate through the
syllabus on the Web; it also contained the ﬁrst exercise. The home page

provided instructions on how to access a page titled NURS 151 (the course

102

 

syllabus) and then how to e-mail the instructor using the hyperlink. Students
were instructed to inform the instructor via e-mail that they had successfully
accessed the Web. This was to be done before the second class to ensure that
students could gain access to the lntemet and that any problems they
encountered could be solved before starting the course.

During the second class, students’ assignment was to access the Web,

 

go to the Web Assignments page, and again e-mail the instructor. In this
assignment, students were asked to answer a question about their comfort with
and feelings concerning use of the Web. The question was open-ended and l
designed to elicit students' initial reactions (positive or negative) about using the
Web. This assignment was to be completed by the third class period.

The assignment for the next activity, called Web Assignment 2 (Appendix
F), was given in the third class session. In this assignment, students were to
access a Web site on pharmacology (Food and Drug Administration—FDA).
Four Web sites were given-locations that dealt with pharmacology and
contained information that would be useful in the course and in their future work
They could look at all four sites, but it was mandatory that they go to the ﬁrst
site. All four sites had hyperlinks and could be accessed by just clicking on the
text in the syllabus under the assignment.

Subjects were to look at the FDA site. They then were instructed to return
to Web Assignment 2 and click on the text Discussion Group, which would
hyperlink them to a discussion group where there again was a question they had

to answer. They were asked to describe what the FDA site had to offer and how

103

L.
they could use it as a student and nurse. Students also were instructed to view
responses to this question by others who had already completed the
assignment. Subjects were able to read their own comments after posting them.
The researcher saved and printed all answers for data-analysis purposes.

Students were alerted that their comments would be viewed by anyone entering

the discussion group. They were to complete the assignment by the next class.

 

The directions and Discussion Group assignment are provided in Appendix F.

The third Web assignment, given during the fourth class, was to be
completed by the next class session. This assignment entailed students’ using a /
4-point Likert-type scale (Strongly Agree to Strongly Disagree) to respond to
questions concerning their comfort using the Web syllabus and the Web
assignments. Information was also obtained on subjects’ experience in using
computers and the lntemet, their educational background, whether they thought
the assignments were useful, and their future use of the lntemet. The students
answered the questions using drop-down boxes, text boxes, and other elements
frequently used to obtain information on the Web. A replica of the form is
provided in Appendix F.

Students were given printed directions only on how to access the Web
syllabus. The rest of the directions were given in each assignment on the Web.
They could access the syllabus through any laboratory at the university or from
home. They had to ﬁnd their own access to the Internet. A 25-station computer
laboratory was located next door to the room where the class was held; it was

open until 10 pm. every day except Sunday.

104

The Comfort Instrument, a paper-and-pencil survey,'was administered
during the next class session. The instrument was not put on the lntemet
because the researcher wanted to control the environment, ensuring that
students understood the instructions and answered the questions.

The Canﬁeld LSI and the Gregorc Style Delineator were administered
during the seventh and eighth class sessions. Instructions were read according
to criteria deﬁned in each instrument.

The researcher told the students that the Web assignments they were to
complete had not been added to the regular course assignments, but rather ( ‘
replaced other assignments that had been omitted. Students were assured that
they were not incurring any more work because of the Web assignments. Those
assignments were designed to meet the same course requirements as the ones

that had been omitted.

105

 

CHAPTER IV
RESULTS OF THE DATA ANALYSIS

Introduction

The results of the data analyses are reported in this chapter. Findings
regarding descriptive statistics are presented ﬁrst, followed by the results of
hypothesis testing. Then the qualitative ﬁndings are discussed. Descriptive
statistics were used to analyze responses to the Canﬁeld and Gregorc
instruments. Frequencies, means, and standard deviations were determined for
each of the 21 Canﬁeld scales and for the four channels'on the Gregorc
instrument. Data are presented throughout Chapter IV. Each of the seven
bipolar semantic scales of the Comfort Instrument was analyzed for frequency,
mean, and standard deviations; results are presented along with those for the
other two instruments.

Hypotheses were tested using both parametric and nonparametric
statistical techniques. Data were analyzed with the assistance and guidance of
two statisticians, who used Statistical Package for the Social Sciences (SPSS)
software to analyze the data for the three hypotheses. All data were taken from
the Canﬁeld and Gregorc instruments, the Comfort Instrument, demographic
items, and the Web Form and put into an Excel spreadsheet for use in SPSS.

All data were double-checked for accuracy after transfer. A logbook was also

106

It:

 

L:
used to maintain data and other material taken from the instruments. Alpha was
set at .05 for all tests for each of the three quantitative hypotheses. For
clariﬁcation, the three instruments (or sample items) are included in the
appendices, along with information on how data for the Canﬁeld and Gregorc
instruments are presented and on interpretation of the scores on each

instrument.

Descriptive-Statistics Findings

Scores on all four of the four mediation channels on the Gregorc
instrument were very close when viewing the group as a whole. Only the CS
(concrete sequential) channel was considered high (range = 27 to 40), with a
mean of 27. The other three channels were all considered intermediate (16 to
26); their means ranged from 22.49 to 26.78. The closeness of these ranges
may indicate that, as a whole, this group was able to use all four mediation
channels equally, demonstrating a wide range of Ieaming styles. They were
able to adapt easily to new Ieaming situations because they had a wide range of
mediation channels. (See Table 6.)

Table 6: Total for all students on each of the four channels of the Gregorc
Style Delineator.

 

 

 

 

 

 

 

 

 

 

 

 

Channel I! Mean Median §_D_

Concrete sequential (CS) 41 27.54 28.00 5.18

Abstract sequential (AS) 41 22.49 22.00 4.31

Abstract random (AR) 41 26.78 26.00 5.02

Concrete random (CR) 41 23.66 23.00 4.96
1 07

 

Analysis of the Canﬁeld LSI provided 21 group means. The range is 1 to

100 for each scale. A score of 50 is considered average, and those above 90

are considered very high. Of the group means, the highest was Detail (59.10),

which was only slightly above average. The lowest mean was 43.98 for the Goal

Setting scale. Nine means were between 50 and 60, and the rest of the 21

means were between 40 and 49. (See Table 7.)

Table 7: Total scores for all students, by scale, on the Canﬁeld LSI.

 

 

 

 

 

 

 

 

 

Scale I! Mean Median SQ
Preferred Condition for Learning
Peer 41 50.49 51.00 10.03
Organization 41 57.76 54.00 10.62
Goal setting 41 43.98 42.00 9.83
Competition 41 50.24 50.00 9.87
Instructor 41 47.61 46.00 9.49
Detail 41 59.10 60.00 10.18
Independence 41 42.02 40.00 8.43
Authority 41 52.93 54.00 9.88
Preferred Area of Interest
Numeric 41 53.29 53.00 10.02
Qualitative 41 46.24 46.00 9.21
Inanimate 41 48.41 48.00 9.60
People 41 51 .24 53.00 8.77
Preferred Mode of Learning
Listening 41 49.85 50.00 8.74
Reading 41 47.66 48.00 7.94
Iconic 41 47.83 48.00 8.09
Direct experience 41 55.00 54.00 10.63
Expectation for Course Grade
A—Total expectation 41 58.34 62.00 1 1.23
B-Total expectation 41 47.22 45.00 7.85
C-Total expectation 41 44.80 40.00 9.42
D—Total expectation 41 45.51 46.00 8.03
Total expectation 41 55.10 57.00 9.12

 

 

 

108

 

As with the Gregorc instrument, the absence of any high scales on the
Canﬁeld instrument and the clustering of means between 40 and 60
demonstrates that the group as a whole tended to use all of the 21 scales,
without any scales having a signiﬁcant impact over the others. Again this might
suggest that, as a group, the students used a variety of all four of the LSI modes
equally. They did not prefer any mode more than the others.
Descriptive statistics for the Comfort Instrument demonstrated very high
means on all seven of the bipolar scales. Six of the seven scales had a mean of
6.0. Only one had a mean of 6.5 (possible range = 7 to 49). This suggests that r“
the group as a whole was very comfortable. The mean for all seven of the

scales was 41.5. (See Table 8.)

Table 8: Descriptive statistics for the Comfort Instrument.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Bipolar Scale l_\l_ Mean Median S_D
Difﬁcult-Easy 41 5.70 6.0 1.47
Tense-Relaxed 41 5.53 6.0 1 .71
Stressful-Unstressful 41 5.25 6.0 1 .81
Anxious-Calm 41 5.43 6.0 1 .71
Unsure-Conﬁdent 41 5.48 6.5 1 .91
Unpleasant—Pleasant 41 5.50 6.0 1 .66
Uncomfortable-Comfortable 41 5.60 6.0 1 .77
Total comfort score of 1-7 41 38.48 41.5 10.48

1 09

 

Results of Hymthesis Testing

Hygothesis 1

There is no relationship between nursing students’ Ieaming styles and
their comfort in using the lntemet/WWW.

Data analysis. The ﬁrst test used in analyzing the data for Hypothesis 1
was the Pearson product-moment correlation coefﬁcient. Scores on the 21
scales of the Canﬁeld LSI (in the form of percentages) for each subject were
correlated with the total score obtained by each subject on the Comfort
Instrument (possible range = 7 to 49). The resulting 21 correlation coefﬁcients
were all considered low (r = .3 or less). Some were negative, but none showed
either a positive or a negative correlational strength of greater than .3 (see
Table 9). No statistically signiﬁcant ﬁndings were obtained.

The Canﬁeld LSI also gives an overall Ieamer typology (see Appendix C)
based on students’ scores. Nine typologies are possible. Each of the nine
overall typologies was coded using numbers arbitrarily assigned from 1 to 9; no
ranking of the typologies was possible. This categorical numbering was then
correlated with the Comfort Instrument using a nonparametric Spearrnan
correlation, which is used when data are categorical in nature. Almost no
correlation was found. The resulting _r_ = .007 was demonstrated after analysis.

Again, there was no statistically signiﬁcant ﬁnding at alpha = .05.

110

 

Table 9: Correlations between 21 Canﬁeld LSI scales and total scores on

the Comfort Instrument.

 

 

 

 

 

 

 

Scale Total Comfort Score
Preferred Condition for Learning
Peer .089
Organization .269
Goal setting -.205
Competition -.204
Instructor .099
Detail -.139
Independence -.083
Authority -.056
Preferred Area of Interest
Numeric -.053
Qualitative -.103
Inanimate -.020
People .1 12
Preferred Mode of Learning
Listening -.087
Reading -.068
Iconic -.047
Direct experience .191
Expectation for Course Grade
A-Total expectation -.162
B-Total expectation .184
C—Total expectation -.199
D—Total expectation -.209
Total expectation .007
By Ieamer typology .009

 

 

Pearson product-moment correlation was used again to correlate the total

of the Comfort Instrument with the four channels of the Gregorc Style Delineator

(AS, CR, AR, CS). Again, very low correlations were found between the total on

the Comfort Instrument and the four mediation channels. The highest correlation

found was -.285 for the Abstract/Random (AR) channel (see Table 10). Again,

 

 

La

no statistically signiﬁcant ﬁndings emerged. The subject group appeared to be

fairly comfortable in using the Web assignments for course work.

Table 10: Correlations between the four channels of the Gregorc Style
Delineator and the total score on the Comfort Instrument.

 

 

 

 

 

 

Scale Total Comfort Score
Gregorc CS .1 10
Gregorc AS -.285
Gregorc AR .077
Gregorc CR .015

 

 

 

Multiple regression techniques were used to determine whether any
combination of the Canﬁeld LSI or Gregorc Style Delineator scores had
signiﬁcance when viewed with the total scores on the Comfort Instrument.
Multiple regression is used when there are multiple levels of the independent
variable with one dependent variable. The independent variables were inserted
into the computer in a standard form, meaning there was no deliberate insertion
of variables based on importance or ranking.

First the four Canﬁeld scales making up Mode of Learning (direct
experience, iconic, numeric, and qualitative) were inserted as the independent
variables; total Comfort Instrument score was the dependent variable. From
Table 11 it can be seen that the results showed an adjusted R-square value of
-.046. ANOVA results from the same test indicated an F-value of .419 and a

signiﬁcance level of .740. The results again were not statistically signiﬁcant.

112

 

Table 11: Regression between the dependent variable, total Comfort score,
and the independent variables, Canﬁeld LSI preferred mode of

 

 

Ieaming.
Model Summary
| Model | g Iii-Square Adjusted B-Square | Std. Error of Estimate]
| 1 I.181‘| .033 -.046 I 12.2340 I

 

 

aPredictors (constant): Preferred mode of Ieaming.

 

 

 

 

ANOVA“
Model Sum of Squares g_f Mean Square E Sig.
1 Regression 188.332 3 62.77 .419 .740b
Residual 5537.863 37 149.627
Total 5726.195 40

 

 

 

 

 

 

 

 

aPredictors (constant): Preferred modes of Ieaming.
t’Dependent variable: Total score on Comfort Instrument.

11%: See individual correlations between all scales of the Canﬁeld LSI and the
Gregorc scales and the total score on the Comfort Instrument.

The same technique was used, only with the four channels of the Gregorc
Style Delineator (AS, CS, AR, AS) for the independent variables or predictors
and the total score on the Comfort Instrument as the dependent variable. Again,
from Table 12, it can be observed that no statistically signiﬁcant results were
found at alpha = .05.

Finding no signiﬁwnt results from the Comfort Instrument, the researcher
and statistician decided to use Item 20 on the Web Form (see Web assignments
in Appendix F). The 7-point semantic scale was used, asking students to rate
their frustration when using the Web. The students rated their frustration from

113

 

low or none (1) to high frustration (7). Again, no statistically signiﬁcant ﬁndings

were found at alpha = .05 when using the four channels from the Gregorc

instrument and the Web Assignment Form: Frustration (see Table 13).

Table 12: Regression between the four Gregorc channels (AS, CS, CR, AR)
and the total score on the Comfort Instrument.

Model Summary

 

 

 

 

 

 

 

 

 

Model I3 I_ R-Square Adjusted B-Square I Std. Error of Estimate I
1 I. 3I.0 -.051 I 12.2656 I
‘Predictors (constant): CS, AS, CR, AR. (1

ANOVAa
Model Sum of Squares d_f Mean Square 5 Sig.
1 Regression 310.165 4 77.541 .515 .725b

Residual 5416.030 36 150.445

Total 5726.195 40

 

 

 

 

 

 

 

 

:Predictors (constant): CS, CR, AS, AR.
bDependent variable: Total score on Comfort Instrument.

Note: See individual correlations between all scales of the Canﬁeld LSI and the
Gregorc scales and the total score on the Comfort Instrument.

In conclusion, all correlations and regression tests performed on the data
to test Null Hypothesis 1 indicated no statistically signiﬁcant results at alpha =

.05. Therefore, the null hypothesis cannot be rejected and must be retained.

114

 

Table 13: Regression between the four Gregorc channels (AS, CS, CR, AR)
and the Web Assignment Form: Frustration.

 

 

Model Summary
I Model I B _R-Square I Adjusted B-Square I Std. Error of Estimate I
I 1 I .277’3 .077 I -.026 I 2.1886 J

 

 

aPredictors (constant): CS, AS, CR, AR.

 

 

 

 

 

 

 

 

 

 

ANOVA‘
Model Sum of Squares d_f Mean Square 13 Sig.
1 Regression 14.339 4 3.585 .748 .566b
Residual 172.441 36 4.790
Total 186.780 40

 

aPredictors (constant): CS, CR, AS, AR.

bDependent variable: Web Assignment Form: Frustration.

Note: See individual correlations between all scales of the Canﬁeld LSI and the
Gregorc scales and the total score on the Comfort Instrument.

Discussion. The lack of a statistically signiﬁcant relationship between

students’ comfort using the lntemet/WWW and their Ieaming styles may have

been due to the small sample, which contained high variability. A larger sample

might produce different results. Students using the lntemet/Web in a classroom

might also have different Ieaming styles from those found in the Canﬁeld LSI or

the Gregorc Style Delineator. The Comfort Scale should be used again and

more reliability and validity tests performed to enhance the instrument. That

might also change the results in future studies.

 

 

The lack of statistically signiﬁcant ﬁndings contradicted the results
obtained by Davidson et al. (1992), Ester (1994), and Kaczor and Jacobson
(1996) using the Gregorc Style Delineator. Those studies, as well as the
present one, need to be replicated in order to obtain more concrete evidence
that Ieaming style theory does indeed measure the Ieaming that takes place
when students use the lntemet and computers. So far, the few studies that have
been done on the lntemet have been sketchy and have provided minimal
guidance, at best, for teaching and Ieaming using computers and the lntemet.
Only when more deﬁnitive studies are conducted can Ieaming styles be used to
assist faculty who are teaching and students who are Ieaming in these types of
situations. This includes using LSls that represent the many different levels of
Ieaming styles discussed earlier in this dissertation.

This study was based on lntemet assignments that can be considered
introductory in nature. Relatively stable, traditional Ieaming techniques were
used for most of the course. Had the lntemet been used for a greater portion of
the course, or even the entire course, it is possible that different ﬁndings
regarding the relationship between comfort in using the lntemet and Ieaming
style might have emerged. Greater use of the lntemet might have caused
students with certain Ieaming styles to become more uncomfortable as the

lntemet became a more integral part of the Ieaming experience.

Hygothesis 2

There is no relationship between nursing students’ personal experience in
using computers and the lntemet and their comfort in using the lntemetl
W.

116

 

Data analysis. Nonparametric correlations were used to test Null

Hypothesis 2, when correlating years of experience using the lntemet and

computers. Spearrnan correlation was used because response to years of

experience for both questions was given an arbitrary number for each possible

response on the Web Assignment Form (see Appendix F). The options given

were 0 years (1 ), less than 6 months (2), 6 months to 1 year (3), 1-2 years (4),

and so on, and can be found on the Web Assignment Form.

From Table 14 it can be seen that, when correlating the total score on the

Comfort Instrument with years of experience using a computer, the r value was

.454. This is a moderate correlation; however, it was statistically signiﬁcant at

.05 (2-tailed). It was even found to be signiﬁcant at alpha = .01 (2-tailed).

Table 14: Correlation of total score on the Comfort Instrument and experience

using computers and the lntemet.

 

 

 

 

 

 

 

 

 

Experience Using Experience on Total Comfort
Computer lntemet Score
Pearson Exp. on computer 1.0000 .672“ .454“
Correlation Exp. on lntemet .627“ 1.0000 .390'
Total Comfort score .454“ .390* 1.0000
Signif. Exp. on computer .000 .003
(2-tailed) Exp. 0n lntemet .000 .012
Total Comfort score .003 .012
N Exp. on PC 41 41 41
Exp. on lntemet 41 41 41
Total Comfort score 41 41 41

 

‘Sign'rﬁcant at the .05 level (2-tailed).

“Signiﬁcant at the .01 level (2-tailed).

117

 

 

Statistically signiﬁcant ﬁndings also were found (r = .390) when
correlating the total score on the Comfort Instrument and years of experience on
the lntemet, using nonparametric correlation (Spearrnan). Similar response '
options were given as for years of experience using a computer and are shown
on the Web Assignment Form in Appendix F. The results were statistically
signiﬁcant at alpha = .05 (2-tailed) (see Table 14).

Given the signiﬁcant ﬁndings for years of experience using the lntemet
and computers, the null hypothesis could be rejected. The researchers
assumptions were validated in this study. Experience did play a role in these
students’ comfort using computers and the lntemet.

Discussion. The signiﬁcant relationship found between students’ scores
on the Comfort Instrument and their experience using the lntemet and
computers has implications for using this technology for teaching and learningin
the classroom. If comfort increases with experience in using computers and the
lntemet, then courses in which students are introduced to these technologies
may be needed to ensure that students have the skills and conﬁdence to use

them in completing course work and as aids to Ieaming.

Hypothesis 3

There is no relationship between nursing students’ age and their comfort
in using the lntemet/WWW.

Pearson correlations obtained between a student’s age and his or her
total score on the Comfort Instrument indicated no statistically signiﬁcant results.

Age was then viewed as a categorical variable; the two groups were (a) those

118

 

 

considered traditional-age students (24 years of age and younger) and (b) those
considered nontraditional-age students (25 years of age and older). Again, no
statistically signiﬁcant relationship was found between the total scores of
students in the two age categories on the Comfort Instrument. Therefore, Null
Hypothesis 3 could not be rejected.

Discussion. The lack of statistically signiﬁcant ﬁndings when correlating
students’ age and their comfort using the lntemet indicates that students’
previous exposure to computers and the lntemet may be enough to make them
feel comfortable when using these two Ieaming aids, regardless of their age. (
Thus, skill in using these technologies may need to be included as a prerequisite
to students entering higher education or acquired soon after enrolling in a

college or university.

Results of the Qualitative Data Analysis

When students were asked to describe what made them uncomfortable or
frustrated with the Web assignments, they gave a variety of answers. Six stated
there was absolutely nothing that they would describe as making them
uncomfortable or as being frustrating. The other subjects gave short answers to
the question, most of which dealt with issues of technology and experience or
knowledge. Three themes emerged from students’ responses: technology,
access, and experience or knowledge. The overriding aspect of time was
involved in all the responses.

Qualitative data analysis was done by using a simple grid. Responses

that demonstrated some negative feedback were not used. Some students did

119

 

not provide any negative feedback and gave only positive responses.
Therefore, these responses were not included and the number of respondents
was fewer than the 41 included in the quantitative analyses. Some students
gave responses that would apply to more than one theme.

Responses were transcribed, and then the researcher took each
response and put it on a grid. Like responses were put on the grid together.
The responses then were viewed and rearranged. Finally, three themes
emerged, and the researcher soon realized that the three themes were all
speaking of time involved in using the lntemet for course assignments.

Of the issues termed technology (37.5%), the most prevalent aspect was
the frustration students felt when servers were down, busy, or somehow
inaccessible. These aspects of using computers and the lntemet are ones that
subjects could not control.

The second issue, access (17.5%), had two different aspects. The ﬁrst
was students’ inability to quickly get email and lntemet access because they
had to go through the process of registering through the lnfonnation Services
department at the university. Students thought this was confusing and time
consuming. After getting access, there was a 24-hour wait before signing on to
certain aspects of the lntemet and e-mail. Those with children and no lntemet
access from home saw this as just another obstacle keeping them from their
studies and their families.

The second aspect of access concerned students’ having computer

access. Students said it was very frustrating ﬁnding out where to start and get

120

 

access through the university if they had no other e—mail and lntemet access.
They thought it wasted valuable time having to go a computer lab and/or having
to make arrangements (planning) to get to one of the several computer labs on
campus or in their communities. This added stress to those who commuted and
had no computer access at home or in their communities. All of these concerns
appear to have compounded the stress of starting a new program that is very
intense, with most students carrying 19 credits in an abbreviated 12-week
summer course.

The third theme was students’ lack of knowledge (45%) about how to use
both the computer and the lntemet. Those who had little or no experience found
it ovenrvhelming to Ieam how to use the computer to access the lntemet and then
how to use the browsers to ﬁnd the information they needed. Some students
were overwhelmed by the amount of information they found, as well as by sorting
out the information they needed.

Overarching these three themes was the matter of time. All of the
problems with technology, access, and knowledge or experience gave rise to a
need for additional time to complete assignments. For these students, time was
at a premium. Completing their assignments on the lntemet took time away from
these students’ families and their “studying.”

Some students who found the assignments on the Web overwhelming
also said they were glad they had done the assignments. They understood that
they would need these skills in later courses, or it was something they had

wanted to Ieam but had not previously had the time or computer access.

121

 

Summar I

The results of the quantitative and qualitative data analyses, along with a
discussion of those results, were presented in this chapter. The results of the
quantitative data analyses for two of the three hypotheses were not what the
researcher expected, but the data did provide insight into the Ieaming styles of
this group of students.

Chapter V concludes the dissertation and provides possible reasons why
the results for this group of Ieamers were obtained. Limitations and reﬂections
of the researcher are provided in an attempt to bring some type of understanding
as to the results of the study. The researchers reﬂections provide for greater
understanding of the data and subsequent meaning for this group of Ieamers
using the lntemet and computers in a traditionally taught course in nursing

educaﬁon.

122

 

It.“

CHAPTER V

 

DISCUSSION, LIMITATIONS, RECOMMENDATIONS,
REFLECTIONS, AND CONCLUSION

Discussion

Not many studies have been undertaken on the topic of Ieaming styles
and the lntemet, and only a few of the available LSls were used in those -.
investigations. Further, previous researchers attempted to measure just a
couple levels of the onion metaphor presented by Tennant (1991). The ﬁndings
of the present study contradicted the results of previous studies in which it was
found that Ieaming styles inﬂuenced how students dealt with computers and the
lntemet. However, the limited nature of the studies that have been completed
on learning styles makes it difﬁcult to determine how Ieaming styles affect
Ieaming on computers and the lntemet. Because the studies that have been
done have not been replicated, it is difﬁcult to formulate deﬁnitive implications
for teaching and Ieaming.

This study was considered exploratory; among other things, it was
designed to determine whether factors such as age and experience in using
computers and the lntemet might affect students’ comfort in using this
technology. In this study, no correlation was found between students’ age and

their comfort in using the lntemet/WWW. However, a signiﬁcant relationship

123

was found between students’ experience using computers and the lntemet and
their comfort in using the lntemet/WWW, leading to the conclusion that
experience may play a signiﬁcant role in determining students’ comfort. This
study needs to be replicated with a larger sample to see whether the same
ﬁndings emerge. If they do, there are implications for teaching and Ieaming.
Students who lack skill in using computers and the lntemet may need to gain
such skill before entering colleges and universities.

The qualitative results from this study had one overriding theme-that of

 

time. Students thought that the extra time needed to access the lntemet, ('1
Ieaming how to use computers and browser software, and time spent when

servers were slow or inoperative, was time wasted. This time was taken away

from “studying” and other personal endeavors. For some reason, these students

did not perceive the Web assignments as Ieaming assignments and hence as

important as their “studying.” It would be interesting to know what these

students perceived as Ieaming and why they did not view the assignments as

adding to their Ieaming. Quite possibly these students felt more comfortable

with the traditional classroom setting and did not consider any deviation from

that setting a valuable Ieaming tool. Students might have viewed the Web

assignments only as the instructor's research project and not as Ieaming.

Limitations
One limitation of the study was the use of a convenience sample of
nursing students at only one university. Thus, the ﬁndings are generalizable

only to students who are similar to those who participated in this research. Use

124

.
i,
"I", in

of a larger, random sample would make the ﬁndings generalizable to a larger
population.

The researcher-developed Comfort Instrument needs to be administered
to a larger sample of subjects, to better determine its reliability and to further
reﬁne the instrument. A larger sample would have decreased variability, thereby
possibly yielding statistically signiﬁcant ﬁndings.

Results were dependent on subjects’ honesty in completing the
instruments and their comprehension of the terms used. Also, the students

seemed to have a strong bond with the instructor/researcher, and it is possible {I

that they might have tried to 'help” her by not giving negative answers on the
Comfort Instrument.

Students’ responses to the qualitative question were very limited, even
though they were asked to expound on their feelings and provide substantial

feedback. This limited the data that were available for analysis.

Recommendations for Further Research and
for Teaching and Learning

Using the lntemet in the classroom has enormous potential to enhance
teaching and Ieaming. Additional studies need to be undertaken to determine
how students learn by using this technology. Until then, students and faculty will
need to try new techniques and ﬁnd what works and what does not, through trial
and error. It is therefore important that more studies be done to validate the
ﬁndings of research that has already been completed and to explore new

directions to help students and faculty use the lntemet effectively.

125

 

The lntemet/Web has the potential of providing unlimited opportunities
and new avenues through which teaching and Ieaming can occur. Further study
of the way Ieaming takes place in this relatively new teaching and Ieaming
situation is needed so that students are given opportunities that enhance
Ieaming and best match their Ieaming styles. Even though, in this study, no
relationship was found between students’ Ieaming styles and their comfort in
using the lntemet/WWW, more research needs to be conducted to determine
whether students are comfortable using this medium in Ieaming. Research
should also be undertaken to determine whether current LSls measure the types
of Ieaming that students employ when using computers and the lntemet. New
Ieaming style theories and instruments may need to be developed to explain and
measure this type of Ieaming.

Not addressed in this study, but prevalent in the literature on teaching
and Ieaming, is the teaching style of instructors using the lntemet/Web in the
classroom. More studies need to be conducted on how best to use the lntemetl
Web to facilitate student Ieaming. There is also a need for research on how
instructional style relates to using the lntemet as a part of teaching, and what
skills instructors need in order to facilitate Ieaming using the lntemet.

Work on Ieaming styles has raised a number of questions. Further
research is needed to determine whether there is gender or cultural bias in LSIs.
Researchers need to focus on the role of age, race, and gender, to determine
whether these characteristics have more implications than previously thought. If

it is true that LSls identify only a portion of what constitutes Ieaming style, then

126

 

more studies will need to be conducted using multiple Ieaming style measures.
More qualitative and longitudinal designs also should be used, which would
provide added insight into Ieaming styles and whether they change over time.
Insight could also be gained into whether, over time, students are able to adopt

and use other Ieaming styles as they gain broader experience and knowledge in

 

a discipline. These implications also apply to studies focusing on Ieaming styles
and use of the lntemet/WWW because if students’ Ieaming styles do not match
the style involved in using the lntemet, universities must provide basic skills
preparation in this area so that students can effectively use the lntemet/WWW
as they progress through college and later in their careers.

College and university administrators will need to determine how to better
support faculty when incorporating the lntemet into the classroom because, as
this researcher learned, using such technology is very technical and time
consuming. Faculty will have to Ieam new communication skills, as well as
those related to the lntemet and computer technology.

College and university administrators should also study their facilities and
procedures for computer labs and Internet access in order to make access to
and use of these technologies as uncomplicated as possible and available to all
students. This issue recently has been addressed at Michigan State University,
where freshmen might in the future need to have a laptop computer when they
enter the university.

College and university personnel must also address the need for student

assessment in the skills needed to use computers and the lntemet. Students

127

coming onto campus without these skills might need an introductory course on
these technologies.

When looking at the use of the lntemet in teaching and Ieaming, the
quality of students’ responses on the lntemet needs to be evaluated. Also, ways
to enhance student communication in course work need to be investigated. As
noted in this study, students’ response was minimal when they were asked to

provide feedback in written form.

Reﬂections

The results of this study did not meet the expectations of the researcher,
as stated at the end of Chapter II. Reasons were given throughout Chapter IV
and in the discussion and limitations sections of Chapter V that might explain the
results. They are reviewed in this section to try to reach a better understanding
of the results and why the study had the results it did.

As stated in the limitations, researcher honesty, content construct of the
Comfort Instrument, sampling methods, and limited responses of students on the
qualitative question all could have affected the internal validity and affected the
study ﬁndings leading to the results. However, when looking more deeply at the
descriptive statistics gained from the Canﬁeld LSI, the Gregorc Style Delineator,
the Comfort Instrument, and group demographics, some interesting data were
revealed.

First, the group was typical because, as a group, the mean age was 9
years lower than the average student at the university. This means that younger

students comprised the group—one that had more exposure to computers and

128

 

possibly less anxiety or discomfort using computers and the lntemet because
they had greater exposure to the technology in their previous education. The
homogeneity of the group might have skewed the results of the study, leading to

the lack of correlation between Ieaming style and comfort using the lntemet in

 

course work because they were more alike than different. No correlation could
be found because of a lack of differences in the group.

This homogeneity also can be seen in the group scores on the two LSIs.
The group score on the Canﬁeld scales ranged from 40 to 60 using percentiles.
The average for that instrument on each scale was 50. The group mean was
clustered 10% above and below what is considered average (501h percentile),
demonstrating the homogeneity of the group. This led the researcher to assume
that the group had very little variability in general and very little preference for
any of the 21 scales over any other scale. The group, when viewed as a whole,
used all of the 21 scales, with very little preference for any of the scales when
Ieaming. Also no one, two, or group of scales was predominant over others, so
the group’s Ieaming styles were evenly distributed over the 21 scales,
demonstrating no preferred Ieaming style.

The same phenomenon can also be seen in the Gregorc scores on the
four mediation channels. The group means were closely clustered from 23.6 to
27.5. Only the mediation channel Concrete Sequential was considered to be
high and therefore highly preferred by Ieamers. The CS channel (mean = 2.75)
was only minimally higher than the low reference point of 26. A score of 26 or

greater means a channel is considered high for Ieamers and was predominantly

129

used and preferred by Ieamers. But given the group means, it is suggested that
the group was more alike than not. By preferring all four channels equally,
students had no high mean or preference for any one or two of the mediation
channels, which means they could use all four channels equally. If they had no
overriding preference and could use all four channels, then any new Ieaming
strategy like computers and the lntemet would be incorporated into their Ieaming
with no more stress or discomfort than any other type of strategy. This would
make this group adept at using any Ieaming strategy imposed on them.

\ﬁewing the group as not having any preferred Ieaming style, based on
the Gregorc and Canﬁeld instruments, that they did not highly prefer or did not
prefer, would provide a reason why the mean (38.4 group mean, range 7 to 49,
average of range 21) on the Comfort Instrument was fairly high. The students
did not experience a great deal of discomfort or negative feelings because they
could use any Ieaming style as measured by the instruments used in the study,
regardless of age.

When looking at the results for Hypothesis 2 in light of the preceding
discussion, it would seem, then, that just gaining experience using the lntemet
and computers would be enough for this group to report an increase in comfort
level when using the technology in the classroom. This was also borne out
when looking at comments made by students on the qualitative question, where
the biggest obstacles were the hassles in constraints of time. These were due

to the lack of knowledge of how to use the technology, accessing computers and

130

 

 

the lntemet, and delays incurred due to technology issues. Edelson (1998)
reported similar barriers to using the technology.

Therefore, with the ability to comfortably use all the Ieaming preferences
equally, as measured by the LSIs, students should be given ample support and
experience in Ieaming to use computers and the lntemet (Edelson, 1998;
Hubbard, 1998; O’Neil, 1970; Presno, 1998; Spielberger, 1970). This
experience and support would be adequate for this group of Ieamers to use the
technology comfortably to complete course assignments based on their abilities
to use multiple Ieaming styles and no strong preference for or against only one
Ieaming style.

When reﬂecting on the preceding discussion, the researcher also thought
about the issues of support for this group. It is possible that the group wanted to
make the researcher “look good” in the study because of their identiﬁcation with
the researcher, hence they might have reported more “comfort” because they
were being supportive of the researchers project. This was indeed a two-way
street for the issue of support.

It is also conceivable that students’ report of comfort when using the
lntemet was a nonissue for them relative to the wide array of very stressful
things they were experiencing that summer. Some of these stresses were
having a large number of contact hours, Ieaming to give shots, working with
medications, and Ieaming how to perform intimate procedures with real patients

in clinical settings. These new experiences could have entailed stresses that

131

made using the lntemet and technology pale in comparison when they rated
their comfort on the Comfort Instrument.

As mentioned earlier, the Web assignments completed by students were
just a small part of the total course expectations. Most of the course was taught
traditionally, and therefore the Web assignments were not a strong enough
stimulus to cause a great enough discrepancy between Ieaming styles and
instructional methods. Therefore, the stimulus was not great enough to reach
the threshold needed for students to have negative feelings and thus report a
lack of comfort. Possibly, using more intensive instructional methods based on /
the lntemet might have enhanced the discrepancy between Ieaming styles and
use of the lntemet and computers, leading to different results regarding student
comfort.

In conclusion, even though the results of the study were not what the
researcher expected, in light of the descriptive statistics and qualitative research
questions, the study did provide some interesting propositions as to the group’s
Ieaming needs. This, of course, needs to be studied further and leads to more
studies to Ieam about what happens if students do not have a preference for any
one Ieaming style. It also adds emphasis to the experiential Ieaming that takes

place for students.

onclusion

This study was completed using a group of nursing students in a medium-

sized state university; these students were enrolled in a course in which nursing

132

pharmacology was taught. The researcher substituted traditional assignments
with assignments on the lntemet to enhance Ieaming. Based on a review of
research studies and literature on Ieaming style theory, the researcher
hypothesized that students’ comfort using the lntemet and computers would
differ, based on their Ieaming styles. The discrepancy between students’
Ieaming styles and their use of the lntemet and computers would cause a
stimulus that would be apparent in the students’ comfort level.

It is also plausible that the researcher did not ﬁnd a correlation between
Ieaming styles and student comfort because the LSls used in the study were
developed and validity gained using traditional classroom settings. Current LSls
may not include the types of Ieaming styles that are employed when using the
lntemet and computers.

However, group analysis demonstrated a homogeneous group with little
difference in Ieaming styles on two LSls. In fact, the group did not demonstrate
any Ieaming style preferences on either instrument. Signiﬁcant ﬁndings were
indicated between comfort and experience in using computers and the lntemet.
Qualitative analysis indicated that students were more concerned about the lack
of knowledge in using the technologies and issues of access when asked about
their comfort using the lntemet and computers. Plausible reasons have been
presented for the ﬁndings of the study, including the limitations of sample
selection and the construct and content validity of the Comfort Instrument. The
study results, however, need to be compared with the results of research on

larger, more diverse student populations to determine whether relationships

133

 

exist between Ieaming styles and use of the lntemet and computers in the

classroom.

134

|
' .
1
.‘ -
-————

APPENDICES

135

APPENDIX A

DESCRIPTIVE STATISTICS FOR THE SAMPLE

136

I.)

Table A1: Breakdown of the sample by age.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Age Frequency Percent Cumulative Percent
18 2 4.9 4.9
19 1 2.4 7.3
20 7 17.1 24.4
21 6 14.6 39.0
22 5 12.2 51.2
23 5 12.2 63.4
24 1 2.4 65.9
25 2 4.9 70.7
26 3 7.3 78.0
29 1 2.4 80.5
30 2 4.9 85.4
32 2 2.4 87.8
35 2 4.9 92.7
36 1 2.4 95.1
38 2 4.9 100.0

 

 

137

Table A2: Subjects’ experience using the computer.

 

 

 

 

 

 

 

 

 

 

 

 

 

Experience Frequency Percent Cumulative Percent
0 years 1 2.4 2.4
Fewer than 6 months 1 2.4 4.9
6 months to 1 years 7 17.1 22.0
1-2 years 9 22.0 43.9
2-3 years 5 12.2 56.1
3-5 years 4 9.8 65.9
5—1 0 years 14 34.1 100.0
Total 41 1 00.0

 

 

Table A3: Subjects’ experience using the Web/lntemet.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Experience Frequency Percent Cumulative Percent
0 years 1 2.4 2.4
Fewer than 6 months 12 29.3 31.7
6 months to 1 years 3 7.3 39.0
1-2 years 14 34.1 73.2
2-3 years 6 14.6 87.8
3-4 years 2.4 90.2
4 or more years 4 9.8 100.0
Total 41 100.0
1 38

 

Table A4: Subjects’ educational level/background.

 

 

 

 

 

 

 

 

 

Educational Level Frequency Percent Cumulative Percent
High school 28 68.3 68.3
Associate degree 22.0 90.2
Bachelor’s degree 4 9.8 100.0

Total 41 100.0

 

 

Table A5: Subjects who had taken previous courses on the Web.

 

 

 

 

 

 

 

 

Had Taken Course Frequency Percent Cumulative Percent
Yes 12 29.3 29.3
No 29 70.7 100.0
Total 41 100.0

 

 

Table A6: Subjects who considered themselves computer literate.

 

 

 

 

 

 

 

 

 

 

Computer Literate? Frequency Percent Cumulative Percent
Strongly agree 12 29.3 29.3
Agree 19 46.3 75.6
Disagree 7 17.1 92.7
Strongly disagree 3 7.3 100.0

Total 41 100.0

 

 

139

Table A7: Subjects’ comfort using the Web.

 

 

 

 

 

 

 

 

 

 

Comfortable Using the Web? Frequency Percent Cumulative Percent
Strongly agree 17 41.5 41.5
Agree 16 39.0 80.5
Disagree 14.6 95.1
Strongly disagree 4.9 100.0

Total 41 100.0

 

 

Table A8: Subjects who had a computer at home.

 

 

 

 

 

 

 

 

 

 

Have Computer Frequency Percent Cumulative Percent
Yes 12 29.3 29.3
No 29 70.7 1 00.0
Total 41 100.0
1 40

 

APPENDIX B

INFORMED CONSENT AND LETTER OF PERMISSION FROM
THE UNIVERSITY COMMITTEE ON RESEARCH INVOLVING

HUMAN SUBJECTS (UCRIHS)

141

Informed Consent

The following Ieaming style inventories are being given to you to assist in
determining how student Ieaming styles relate to use of the lntemet and W
in a traditional classroom setting such as this, Nursing 151. It is a study by the
instructor in completion of requirements for a Ph.D. at MSU. You will receive the
results of the instruments and how to use them in understanding your own
Ieaming style later in the semester after they are scored.

It is important that you understand that your names will not be used in the
study, as only the group scores are to be used. Names are needed only to
match your responses to the Web assignments and to return the results to you.
Your participation in completion of the instruments will not be graded or impact
your grade in any way.

The Web assignments, however, are a part of this course participation
and will continue to be a part of this course in order to introduce students to, and
use, the lntemet/Web as a valuable source of communication and information.
Therefore, completion of Web assignments is part of your grade and will be
included in the study by completion of the Ieaming style instruments.

For participation you will be given one service credit of the three needed
for graduation. The instructor will ﬁll out the forms and return them to you to give
to your advisor. You will also receive the results of the Ieaming style
instruments with instructions how to use them to assist you in your course work.
The instructor will pay for the instruments and scoring of the instruments. This is
free, no cost to you, the student, and will give you valuable information about
how you Ieam best and how to help you use your style to enhance your Ieaming.

Thank you for your participation.

Denise L. Hoisington, RN, MSN

142

 

IJ

MICHIGAN STATE

UNIVERSITY

 

May 11, 1998

TO: Marvin Grandstaﬁf. .
Educational Administration
427 Erickson Hall

RE: IRB#: 98-296
TITLE: CONFORT USING COMPUTES AND RELATIONSHIP TO

LEARNING STYLES AND AGE: NURSING STUDENTS
REVISION REQUESTED: N/A A

CATEGORY: l-C, 1-
APPROVAL DATE: 05/04/98

The university Committee on Research Involving Human Sub'ects'(UCRIHS)
review of this project is complete.. I am pleased to adVise that the
rights and welfare of the human subjects appear to be adequately
rotected and methods to obtain informed consent are appropriate.

herefore, the UCRIHS approved this project and any reVisions listed I
above.

RENEWAL: UCRIHS approval is valid for one calendar year, beginning with
the approval date shown above. Investigators planning to
continue a project beyond one year must use the green renewal
form (enclosed with t e original agprovaI letter or when a
project is renewed) to seek u date certification. There is a
maximum of four such expedite renewals possible. Investigators

wishin to continue a project beyond that time need to submit it
again or complete reView.

REVISIONS: UCRIHS must review any changes in Erocedures involving human
subjects, rior to initiation of t e change. If this is done at
the time o renewal, please use the green renewal form. To
revise an approved protocol at an other time during the year,
send your written request to the. CRIHS Chair, requesting revised
approval and referenCing the preject's IRB # and title. Include
in your request a description of the change and any revised
instruments, consent forms or advertisements that are applicable.

pnosnms/ . . .

CHANGES: ShOuld either of the followin arise during the course of the
work, investigators must noti UCRIHS promptly: (1) roblems
(unexpected Side effects, comp aints, etc.) involving uman
subjects or (2) changes in the research environment or new
information indicating greater risk to the human sub'ects than
existed when the protocol was previously reviewed an approved.

If we can be of any future help, please do not hesitate to contact us
at (517)355-2180 or FAX (517)432-1171.

t) Ur

avid E. Wright, P
UCRIHS Chair

DEW:bed

Sincerely,

   

cc: énise L. Hoisington

143

APPENDIX C

SUPPLEMENTARY INFORMATION ON THE CANFIELD LSI

144

 

Table C1: Description of scales on the Canﬁeld LSI.

Conditions for Leaming (8 scales)
Preferred situation or content of instruction

 

 

Peer Enjoys teamwork, maintaining good relations
with other students, having student friends,
etc.

Organization Desires clearly organized course work,

meaningful assignments and a logical
sequence of activities

 

Goal Setting Wants to set own objectives, use feedback to
modify goals or procedures, and make his or
her own decisions on objectives

 

Competition Desires comparison with others, needs to
know how he or she is doing in relation to
others (

 

Instructor Wants to know the instructor personally and
have a mutual understanding and liking for
him or her

 

Detail Likes to know specific information,
assignments, requirements, rules, etc.

 

Independence Prefers working alone, determining his or her
own study plan, and doing things
independently

 

Authority Desires classroom discipline, maintenance of
order, and having informed and
knowledgeable instructors

 

 

 

 

Area of Interest (4 scales):
Preferred subject matter or objects of study

 

 

 

Numeric Prefers working with numbers and logic,
solving mathematical problems, etc.

Qualitative Likes working with words or language-writing,
editing, talking

Inanimate Enjoys working with things-building,

repairing, designing, and operating

 

People Prefers working with people-interviewing,
counseling, selling, helping

 

 

 

 

145

 

Table C1: Continued.

 

 

 

 

Mode of Learning (4 scales):
Preferred manner of obtaining new information
Listening Prefers hearing lectures, tapes, speeches,
etc.
Reading Enjoys examining written information, reading
tests, pamphlets, etc.
Iconic Likes interpreting illustrations, movies, slides,
graphs, etc.
Direct Experience ' Desires hands-on or performance situations,
such as shop, ﬁeld trips, practice exercises,
etc.

 

 

 

 

Expectation for Course Grade (5 scales):
Level of performance anticipated

 

 

 

 

 

 

 

A-expectation Outstanding or superior level

B-expectation Above average or good level

C-expectation Average or satisfactory level

D-expectation Below average or unsatisfactory level

Total expectation Weighted sum of A-, B-, C-, and D-
expectations

 

 

Canﬁeld LSI available from:

WPS
12031 \Ntlshire Blvd.

Los Angeles, CA 90025-1251

Source: Canﬁeld, A. A (1992). Canﬁeld Learning Styles Inventogy(LSI). Los
Angeles: Western Psychological Services, p. 2.

146

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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.< Ebon— ._w.._ Emtcmo .mﬁbmcm Em: HN0 @305.

147

 

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«:2; E2. 50 maﬁa) ES. :6 820) E2. :3. one; EB. En use; EB. new m=£m> E3. “or

 

 

 

 

 

 

 

 

 

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148

Table CS: Split-half scale reliabilities, Canﬁeld LSI, Form A.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Scale First Half Versus Odd- Versus Even-
Second Half Numbered Items
Peer .97 .97
Organization .96 .97
Goal Setting .97 .97
Competition .98 .98
Instructor .96 .97
Detail .97 .98
Independence .97 .98
Authority .98 .98
Numeric .98 .98
Qualitative .98 .99
Inanimate .98 .98
People .98 .98
Listening .98 .97
Reading .99 .99
Iconic .98 .98
Direct Experience .96 .96
A-expectation .98 .99
B-expectation .97 .97
C-expectation .98 .98
D-expectation .99 .99

 

 

Source: Canﬁeld, A. A. (1992). Canﬁeld LearninLStvlﬁlnvegtgrv (LSI). Los

Angeles: Western Psychological Services, p.38.

149

 

Sample Raw Scores for LSI Scales (Form A)

INSTRUCTIONS

This inventory gives you an opportunity to
describe how you Ieam best. There are no right or
wrong answers. You are to read each of the 30
statements and rank the responses according to how
well they describe your reactions or feelings. Be sure
to write your answers in the spaces to the right of the
appropriate question (a, b, c, or d) and to the left of
the dark line on the edge of the page. The example
below illustrates how the items are presented.
Examine it carefully to be sure you understand how
you are to mark your answers

EXAMPLE

Rank the following colors in the order in which you generally prefer
them.

a. Yellow a. i (least preferred)
b. Red b. A (third)

0. Blue 6. _1_ (most preferred)
d. Green d. _2_ (second)

For each statement, there are four responses to be marked.
Each response must be rated 1 through 4, with 1 indicating the
most-preferred choice and 4 indicating the least-preferred choice.
Use a different number of each response. Be sure to put a number
in each blank or your answers will be unusable.

If you are sure that you know what to do, begin. If you have
a question, ask for assistance before starting.

150

j
r

“ I

..

 

 

Sample Individual WPS Test Report for the LSI

_ --AA--‘
AA‘A‘AA‘AAAAAAAA‘AALAA‘AAAA‘AA‘ AAA”

" Proﬁle of Learning Styles Scores *

AAA A‘A“

 

Very Low Low Average High Very High
T-score 25 30 40 50 60 70 75
Percentile ---}....-.§.}9.-..2?.....§°-....Z§....?°.9?...-.??..-

SCALE 0 '1' %le lwﬂ ””‘Eéééééé'éonaiéiaa tor Learning' ' m ‘ “WT
Peer 36 8 ixxxxxxxxxxxx I , I 2
Organization 68 96 ;xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Goal Setting 45 32 xxxxxxxxxxxxxxxxxxxxxx I I
Competition 54 65 ixxxxxxxxxxxxxxxxxxxxxxxxxxxxxx I
Instructor 52 58 xxxxxxxxxxxxxxxxxxxxxxxxxxxxx I
Detail 34 6 xxxxxxxxxxx I I I ,
Independence 56 72 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx3 I
Authority 57 76 EXXX . . .

I Preferred Area of Interest

Numeric 63 90 XXXXXXXXXXXxXXXXxxxxxxxxxxxxxxxxxxxxxxxx
+ O .

Qualitative 52 58 xxxxxxxxxxxxxxxxxxxxxxxxxxxxx
+

 

 

Inanimate 36‘ 8 xxxxxxxxxxxxx I : I
People 51” 55 Exxxx . Ex :

+ Preferred Nbde of Learning
Listening 27 1 ;xxx I I I
Reading 66 95 :xxxXXXXXxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
iconic 46 34 Exxxxxxxxxxxxxxxxxxxxxx I I

Direct Experience 55 68 xxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxx.
Expectation for Course Grade
: O O

A-expectation 63 91 xXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
+ . .
B-expectation 52 57 XXXXXXXXXXXXXXXXXXXXXXXXXXXXX

 

+ . . .
C-expectation 40 16 XXXXXXXXXXXXXXXXX . . .
+ . . .
D—expectation 37 10 xxxxxxxxxxxxxx . . .
+ O O 0
Total Expectation 62 88 XXxXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
+ I O I
Percentile i 5 10 25 50 " 75 ' '90 95'r .-§;
T-score 25 30 40 50 60 70 75
very Low Low Average High very High

m TEST WT Western Psychological Services .12081 Wilshire Boulevard - Los Angola. CIIiIomia sums

Reproduced from: Canﬂeld, A. A. (1992). Canﬁeld learning styles inventogy
(LSI). Los Angeles: Western Psychological Serv1ces (p 12).

151

 

 

A‘AA‘AAA

AA------

AAAA-A-A‘

‘ Learner Typology *

AAAAAAAAAAA‘AAA!AAAAAMLA‘

This is how individual scales (T-scores) are combined to give summary scores:

 

 

 

 

Direct Summary
Organization Qualitative Reading Experience Inanimate Iconic x score
68 + 52 + 66 ~ 55 ~ 36 ~ 46 = 49
Goal Summary
Peer Instructor Setting Independence Y score 0
36 + 52 ~ 45 ~ 56 = ~13
These typology results are from summary scores:
X X X
less than from greater than
~15 ~15 to 15 15
4 + --------- +—- — — +
Y SA S SC
greater than
10 Social/Applied Social Social/Conceptual
Y A N C
from
~10 to 10 Applied Neutral Preference Conceptual
Y IA I IC
less than
~10 Independent/Applied Independent Independent/Conceptual
*** you iii

 

t

 

_L
T

 

_L
T

#WE 131' MT Western Psychological Services . 12031 Wilshire Boulevard . Los Angeles. California 90025

Reproduced from: Canﬁeld, A. A (1992). Canﬁeld Ieaming styles_inventg_ry
(LSI). Los Angeles: Western Psychological Services (p. 13).

152

 

J
1'

 

I l

 

Students tend to be most comfortable and involved with Ieaming when instructional
techniques are matched to their own or a nearby group as charted above.

Social— prefers extensive opportunities to interact with peers and instructors; has no strong
preference for either applied or conceptual approaches; instnlction involving small
groups and teamwork will create the closest match.

Independent—prefers to work alone toward individual goals; has no strong preference for either
applied or conceptual approaches; instructional techniques such as analysis of case
studies or self-selected and self-paced programs will create the closest match.

Applied—prefers to work in activities directly related to real world experience; has no strong
preferences for either social or independent approaches; instnlction involving
practicums, site visits, and team labs will create the closest match.

Conceptual-prefers to work with highly organized languageoriented materials; has no
preference for either social or independent approaches; instruction involving lectures and
reading will create the closest match.

Social/Applied—prefers to have opportunities to interact with students and instructors in activities
closely approximating real-world experiences; instruction involving role playing, group
problem solving, and supervised practicums will create the closest match.

' SociallConceptual—prefers to have opportunities to interact with students and instructors using
highly organized language-oriented materials; instruction involving a balance of lecture
and discussion will create the closest match.

lndependentlApplied—prefers to work alone toward individual goals in activities closely
approximating real-world experience; instruction involving individual labs or
0 unsupervised technical practicums will create the closest match.

lnd'ependent/Conceptual-prefers to work alone toward individual goals with
->> highly organized language-oriented materials; instruction allowing for
YOU - >> independent reading, literature searches, and reviews will create the
- >> closest match.

Neutral preference-tends to have no clear areas of strong preference; may ﬁnd adequate match
in any other type, but may also at times ﬁnd it difﬁcult to become entirely involved.

_WiE TEST REPORT Western Psychological Services .12031 Wilshire Boulevard . Los Angeles. California 90025

Reproduced from: Canﬁeld, A. A. (1992). Canfield learning styles inventgry
(L l). Los Angeles: Western Psychological Services (p. 14).

153

APPENDIX D

ADMINISTRATION AND SCORING OF THE
GREGORC STYLE DELINEATOR

154

Style Comparison

Following are brief synopses of the style characteristics of the four dominant channels. (p. 38).

 

 

 

 

 

 

 

 

 

 

 

 

Caleggry cs As AR CR
WORLD OF Concrete world of the Abstract world of the Abstract world of Concrete world of
REALITY Physical senses intellect based upon feeling and emotion activity and abstract
concrete world world of intuition
Sequential step-by-
ORDERING step linear Sequential and two- Random non-linear Random three-
ABILITY progression dimensional; tree-like and multidimensional dimensional patterns
Now: total of the
VIEW OF TIME Discrete units of past, The present, The moment; time is past, interactive
present, future historical, past and artiﬁcial and present, and seed for
projected future restrictive the future
Instinctive,
THINKINING methodical, Intellectual, logical, Emotional, psychic, Intuitive, instinctive,
PROCESSES deliberate, structured analytical, rational perceptive, critical impulsive,
independent
Personal proof via Personal intellecmal Inner guidance Practical
the senses; formulae; system demonstration;
\P/RIOIEESISON accredited experts conventionally personal proof: rarely
accredited experts accepting of outside
authority
Material reality; Knowledge facts. Emotional Applications,
FOSUC OF objects of value documentation attachments, methods, processes
ATTENTION relationships and and ideals
memorles
Product, prototype, Synthesis, theories, Imagination, the arts, Intuition, originality,
CREATIVITY reﬁnement, models and matrices reﬁnement, inventive, and
duplication relationships futuristic
Slightly adverse: Notoriously Subject to emotions, Open and amenable,
APPROACH speculative, hesitant indecisive, cross- level of interest often instigator,
TO CHANGE and slow checks, deliberation, critical or 'rolling stone’,
fence-straddler impressionable ‘trouble shooter’
Realist, patient, Realist; serious, Idealist emotional, Realist/Idealist;
APPROACH conservative and determined, logical, exuberant, telescopic attitudinal,
TO LIFE perfection-oriented and intellectual transcendent, and inquisitive, and
intense independent
Ordered, practical, Mentally stimulating, Emotional and Stimulus-rich,
quiet. stable ordered and quiet, physical freedom: competitive, free from
ESEI'BE'RMEEIICEAL non-authoritative ‘ rich: active and restriction, amenable
colorful
Literal meaning and Polysyllabic words: Metaphoric, uses Informative, live,
USE OF labels: succinct, precise, rational: gestures and body colorful: 'words do no
LANGUAGE logical highly verbal language: colorful convey true meaning'
GOOD Excellent Super, Fantastic, Superior, Great
PRIMARY Out-OF-Sight
EVALUATTIVE
WORDS

Gregorc, A. F. (1994). An adult’s guide to style. Columbia CT: Gregorc Associates Inc. (p.38)

155

Administration of the Gregorc Style Delineator ' - i

The Gregorc Style Delineator is nor reproducible but can be obtained from:
Gregorc Associates, Inc.
P. O. Box 351
Columbia, Ct 06237-0351

The Researcher prior to subjects starting the Research (Canﬁeld, 1994, p.5) read the following
directions which also showed an example of a word set and how to complete it .

Before starting with the word matrix on the next page, carefully read all seven of the following

direction and suggestions:

1. Reference Point. You must access the relative value of the words in each group using you
SELF as a reference point: that is, who you are deep down. NOT who you are at home, at work,
at school or who you would like to be or feel you ought to be. THE REAL YOU MUST BE THE
REFERENCE POINT.

2. Words. The words used in the Gregorc Style Delineator matrix are not parallel in construction .
nor are they all adjectives or all nouns. This was done on purpose. Just react to the words as /
they are presented.

3. RANK. Rank in order the ten sets of four words. Put a “4" in the box above the word in each
set which is the best and most powerful descriptor of you self. Give a '3' to the word which is
the next most like you, a “2" to the next and a “1" to the word which is the least descriptive of
your SELF. Each word in a set must have a ranking of 4, 3, 2, or 1. No two words in a set can
have the same rank.
4= MOST descriptive of you

1 = LEAST descriptive of you

4. React. To rank the words in a set, react to your ﬁrst impression. There are no “right' or “wrong”

answers. The real, deep-down you is best revealed through a ﬁrst impression. Go with it.

Analyzing each group will obscure the qualities of SELF sought by the Delineator.

Proceed. Continue to rank all ten vertical columns of words, one set at a time.

Time. Recommended time for word ranking: 4 minutes.

Start. Tum the page and start now.

N935”

An example is given below the instructions as to how to rank- each set. Each set contains 4 words in
a vertical column. Each word has a box to put the ranking by the subject. See next page.

 

Gregorc, A. F. (1994). An adult’s guide to style. Columbia CT: Gregorc Associates Inc. (p. 9—14)

156

The Gregorc Style Delineator Instrument

Below is an example of how the instrument looks. There are 5 columns on the page. The top half of
the page contains sets 1-5 and the bottom half of the page contains sets 610. Each has a number
above the sets and total columns on the right hand side of the page for tallying of rows. There are 4
boxes at the bottom below the row tally to total columns a, b ,c and d. Below is a facsimile of the
instrument containing ﬁctitious word sets and is intended to demonstrate how the instrument is
presented and scored.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ROW TOTALS
1 2 3 4 5 a b c d
a. cow 6. clouds a. dog a. snow 6. leaves _
b. horse b. sun b. cat b. ice b. trees _
c pig 6. stars c. hamster c. sleet c. ﬂowers _
d. sheep d. moon d. bird d. hail d. weeds _
6 7 8 9 10

a. measles

b. woman

c. ﬂoor 0. son

d. rubella d. wall

Column Totals: cs AS AR CR

 

Concrete-Sequential (CS), Abstract- Sequential (AS), Abstract-Random (AR) and Concrete Random
(CR)

Gregorc, A. F. (1994). An adult’s guide to style. Columbia CT: Gregorc Associates Inc. (p. 9-14)
1 57

,~J

 

Scoring the Gregorc Style Delineator

The following directions are given by Gregorc in scoring the instrument (p. 11):

1. Add Across. Add across the “a.” row of words in the ﬁrst ﬁve sets. Put that total in the top 'a'
column box. Do the same for the “b", “c” and “d” rows of the ﬁrst set. Next do the last group of ﬁve
set, putting the row totals in the bottom group of boxes. These totals are those of each of the 4
channels *. (See the Example on previous page.)

2. Add down. Add the top and bottom box in each scoring column to go I he total for that column.

3. Check. If you combined total scores of CS (a), AS (b), AR (0), and CR (d) is greater or less than
100, please recheck your addition. All four columns should total exactly 100.

All subject instruments were scored in this way by the researcher.
INTERPRETATION of Gregorc Scores (p. 14)

Gregorc states that every individual has the ability to demonstrate all four channels (CS, AR, AS,
and CR) but will strongly lean toward one of the channels. This channel is the one most strongly
used by the person. Some maybe strongly oriented to one, two, or even three; an individual’s
qualities will seldom be distributed equally (p.11).

SCORES

1. HIGH (27-40) — mediation qualities are powerful means of transaction for the students.

2. lntennediate (16-26) - means the students will have moderate mediation ability and capacity to
transact in the channel indicated.

3. Low (1-15) - If a score on a channel falls with in this range, the channel has the least mediation
ability and least powerful.

4. An even distribution in all 4 channels (2525-25-25) — A) This demonstrates that all four
channels are equally distributed and the person has “great momentum and concentration ina all
or channels, or B) the person has equal and moderately distributed abilities in all four of the
channels

- NOTE: The four Channels are: Concrete-Sequential, Abstract- Sequential, Abstract-Random
and Concrete Random

Gregorc, A. F. (1994). An adult's guide to style. Columbia CT: Gregorc Associates Inc. (p. 9-14)

158

 

 

APPENDIX E

THE COMFORT INSTRUMENT

159

NAME:

 

Comfort Instrument

The following are rating scales and are designed to get feed back about using the
lntemet in a traditionally taught course such as Nursing 151. Please determine
you response to the following seven scales. Please respond to these not just
about your feeling on using the lntemet, but using the lntemet as a part of Pharrn
151. Remember using the lntemet includes access to the lntemet and e-mail as
well as completion of the assignments.

 

 

1. DIFFICULT EASY
1 2 3 4 5 6 7
2. TENSE RELAXED {
1 2 3 4 5 6 7
3 STRESSFUL UNSTRESSFUL
1 2 3 4 5 6 7
4.ANXIOUS CALM
1 2 3 4 5 6 7
5. CONFIDENT UNSURE
1 2 3 4 5 6 7
6. UNPLEASANT PLEASANT
1 2 3 4 5 6 7
7. UNCOMFORTABLE COMFORTABLE
1 2 3 4 5 6 7
TOTAL Comfort SCALE
(POSSIBLE 749)

160

APPENDIX F

WEB ASSIGNMENTS

161

General Information About Web Assignments

From this page you can reach the web assignments to be completed.
Clicking on each assignment below will take you to the assigned page. Make
sure to read each assignment completely before continuing with each.

162

 

Web Assignment #1

E-mail the Instructor. TOPIC: What are your feelings, observations about using
this web site?

In the SUBJECT box type: ASSIGNMENT #1.
Hit tab key and type your response to the above topic (my feelings, observations
about USING THIS WEB SITE) in the large white box.

Make sure to type your name at the end of the message so the message has an
author. No name, no points.

Click on the SEND button and send the message when done with answering the
topic question.

Click on the following e-mail address and you will go to e-mail and complete the
assignment (What are your feelings, observations about using this web site?):

dhoisington@net-Qrt.com

163

 

Web Assignment #2

You will visit a web site on pharmacology in this assignment. Move around the
site and ﬁnd out what information you can ﬁnd there.

There are several sites. You may look at them all, but you must go to at least
the ﬁrst one (FDA) and ﬁnd out what information you could mine there to use in
your nursing practice.

When done, come back to the assignment and go to the discussion button
(bottom of page) and click on it. Read the instructions on that page, read other
comments already submitted, and answer the question of the discussion page.
Go to the ﬁrst web site below and play around. Note what information you could
ﬁnd and think of how you could use it in your pharmacology course. You need
only go to the ﬁrst site, but feel free to look at more! When done, go to the
assignment below, and get into the discussion page and answer the questions
posed.

httg:ll\nmw.fda.govlfdahomegage.html

http:/Mwwhealthtouchcom

httg:llgharminfo.comlgin hg.htmI

Don’t forget there are other sites on nursing at http:/lnet-
port.com/~dhoisingtonlprofessi.htmL

When done viewing the web site on pharmacology above, to complete the
assignment you must go to the discussion group, register and answer the
questions posed. To go to the discussion group Click “discussion group” below.

DISCUSSION GROUP

164

Web Assignment #3

This assignment entails answering questions and ﬁlling in information about
yourself and then submitting it to the instructor.

use the mouse or tab keys to move from box to box. Type in the information
needed or click the appropriate answer.

Make sure you ﬁll in ALL information. You will receive no points if info is
missmg.

Before you leave this page, make sure to click SUBMIT below. It is the last box
at the very bottom of the page to send the information. You will be notiﬁed by
the program if any information is missing. If so, go back and provide the
information and reclick SUBMIT.

Information Form
1. Last Name
2. First Name:

3. Gender
Male
Female

4. l have a computer at home hooked to access the Web/lntemet.
Yes
No

5. How long have you been using a computer?
0 months

Fewer than 6 months

6 months-1 year

1-2 years

2-3 years

3-5 years

5-10 years

.‘IP’S’IPP’Nr‘

6. Have you taken a prior course on the Web/lntemet?

7. What is your highest educational background?
1. High school diploma
2. Associate degree
3. Bachelor’s degree
4. Higher than a bachelor’s degree

8. How many hours do you normally spend on the Web/lntemet?

 

165

9. What is your age?

 

10. Have you ever taken a course that uses the lntemet/Web?

 

Read each statement below. Click on the arrow next to the box below each
statement. In the box then click on the phrase (from Strongly Agree to Strongly
Disagree) that best describes your reaction to each statement.

11. I am computer literate and am comfortable using a computer.
Strongly Agree Agree Disagree Strongly Disagree

12. I had difﬁculty completing the web assignments (e—mail, visiting the web
' site, using the discussion group, and ﬁlling out this information.
Strongly Agree Agree Disagree Strongly Disagree

13. l was able to ﬁnd pages in the web syllabus with little problem.
Strongly Agree Agree Disagree Strongly Disagree

14. I would not buy a paper copy of the syllabus from the university if it were
available on the web.
Strongly Agree Agree Disagree Strongly Disagree

15. Overall, I feel the web assignments were a valuable Ieaming experience.
Strongly Agree Agree Disagree Strongly Disagree

16. I will use the web again to ﬁnd information to assist me in completion of
course work even if no other assignments are made in subsequent courses.

Strongly Agree Agree Disagree Strongly Disagree
17. I will use the web again for personal use.
Strongly Agree Agree Disagree Strongly Disagree
18. I feel that a course in lntemet use is needed prior to these web
assignments.
Strongly Agree Agree Disagree Strongly Disagree

19. I felt comfortable using the web/lntemet.
Strongly Agree Agree Disagree Strongly Disagree

20. On a scale of 1 to 7, how frustrating was the lntemet to use?

Not Frustrating Frustrating
1 2 3 4 5 6 7

166

__J
In the box below, answer the following question:

21. What part(s) of the use of the web/lntemet was (were) the most uncomfort-
able (frustrating, stressful, difﬁcult, anxiety producing, made you
unsure, or unpleasant) for you?

EXPLAIN! Click in the white box below and type COMMENT]

ANSWER.
Don’t forget to click SUBMIT below the box in which you have typed
your answer when you are done.

When ﬁnished entering all the information, push the SUBMIT button below.

SUBMIT

167

 

Discussion rou

Fill in the boxes below for ﬁrst and last name.

Read the text following your name and then answer the question in the large
white box below the questions.

When done click on POST ARTICLE found below the comments box to submit
your comments. If you do not click on POST ARTICLE, your comments will not
be saved and you will receive no credit.

POST ARTICLE

Last Name:
First Name:

Read the following and answer/comment on the question below.

I do not want to know your comments on the pharm course, but what you have
experienced while using the web for assignments. Don’t just say 'I don’t like it"
or “I had no problems.” Tell me what you have experienced. No one—liners will
do. To get credit, you will need to do some explaining to me as to what you feel
about the assignments.

1. What islare your experience/feelings of visiting the web sites, using the
discussion group and e-mail for completion of web assignments for this
course?

CLICK IN THE BOX BELOW AND TYPE YOUR COMMENTS IN BOX BELOW.
When done, click the POST ARTICLE button below the comment box to save
your comments.

168

REFERENCES

169

J
' A}
.

 

REFERENCES

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718)

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Cafferty, E. (1980). An analysis of student Enormance based upon the deg rg
of ma___t__ch between the educational cogr_1_itive sgle of the teachers and the

educational anitive sgle of the students. Unpublished doctoral

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Cairy, M. (1997). The effects of a coogrative Ieaming environment on

attitudes, social skills and processing of baccalaureate nursing students.
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Carey, J. C., Fleming, S. D., 8 Roberts, D. Y. (1989). The Myers-Briggs Type
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&.

 

Cochenour, J. J., Lee, J., 8. \NIIKII'IS, R. D. (1996). Image maps in the world-
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Comwell, J. M., 8. Manfredo, P. A (1994). Kolb’s Ieaming style theory revisited.
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Cranston, C. M., & McCort, B. (1985). A Ieamer analysis experiment: Cognitive
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Creswell, J. W. (1994). Research design: Qualitative and Quantitative
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Cross, K. P. (1981). Adults as Ieamers: Increasing participation and facilitating
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Dabney, J. (1995). Opinion: Stress in students: Implications for Ieaming?
Innovations on Education and TraininLlntemationaJ. 21(2), 112-116.

 

Davidson, G. V., Savenye, W. C., & Orr, K B. (1992). How do Ieaming styles
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Research on Computing in Education, 24(3), 348-358.

Domino, G. (1970). Interaction effects of achievement orientation and teaching
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