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This is to certify that the

dissertation entitled

Attitudes of Higher Education Interior Design Faculty
Toward the Innovation of Distance Education

presented by

Diane M. Bender

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Ph.D. degreein HED: Design & Mgmt.

 

 

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6/01 c:/ClRC/DateDua.965-p.15

 

ESIGN FACULTY

ATI'ITUDES OF HIGHER EDUCATION INTERIOR D
DUCATION

TOWARD THE INNOVATION OF DISTANCE E
By

Diane Marie Bender

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Human Environment and Design

2002

ABSTRACT

ATTITUDES OF HIGHER EDUCATION INTERIOR DESIGN FACULTY
TOWARD THE INNOVATION OI= DISTANCE EDUCATION

By

Diane Marie Bender

. . , . - u
The purpose of this investigation was to explore Interior design iac lty

attitudes toward distance education. The need for this investigation was
promulgated by the lack of research on educational innovations and the minimal
attention given to distance education by faculty members teaching in the arts.
Diffusion of innovations conceptual framework argues that the perceptions of an

innovation’s attributes will predict an individual’s i ntention to adopt an innovation.

The sample for this study included sixty-seven self‘Selected interior design
faculty members from across the United States who had no previous experience
with distance education, The experimental treatment was a 15-minute
presentation demonstrating interior design instru ction using distance education.

A Solomon four-group experimental design was used with a questionnaire

addressing the attributes of an innovation serving as both the pretest and

posttest instrument.

Major findings included: ( 1) posttest scores compared to pretest scores
for relative advantage, compatability, trialability, complexity, and the intention to
adopt were higher regardless of whether they were in the treatment group or not;

(2) subjects Who received the treatment intervention yielded Significantty higher

posttest means on the variables relative advantage and the intention to adopt

than those not exposed to the treatment intervention; and (3) compatability and
trialability are significant predictors of the intention to adopt distance education.
These findings can help explicate the faculty member’s perceptions of

distance education endeavors. The unique Characteristics of interior design

faculty members and traditional interior design instructional methods need to be

considered when implementing persuasive campaigns for the integration of

distance education into interior design curricula, Such an understanding WI“

prove helpful to faculty members and academic administrators who are [“3an

to adapt distance education methodologies into their curriculum. Examining the

attributes Of an innovation as an approach to determining faculty attitudes toward
distance education does appear to have potential. The implications of the

findings and directions for future research are discussed.

DEDICATION
This research study is dedicated to the memory of my grandfather.
Edward A. Bender (1908 — 2000), a brilliant and inquisitive scientist
whose regret of not completing his college education

taught me its inherent value.

ACKNOWLEDGEMENTS

The author wishes to express her sincere appreciation to the members of
her Doctoral Guidance Committee: Jon D. Vredevoogd, Dr. Stephen
Yelon and Dr. Brenda Stemquist. Special appreciation is expressed to Dr.
Linda Good, Chairperson of her Doctoral Committee, for her insight and
assistance. Gratitude is also extended to my friends, Sharon Yentsch and
Carol Beard, who tirelessly read initial drafts of this study. Sincere
appreciation must also be expressed to the faculty members and
administrators in the sample population who participated in the research
study. Finally, thanks go out to my parents, Don and Janet Bender, who
not only had to read this dissertation many times, but kept me going by

constantly asking, “Aren’t you done yet?”

TABLE OF CONTENTS

Chapter & Topics Page
List of Tables ................................................................................. viii
List of Figures ................................................................................ ix
CHAPTER ONE - Introduction ........................................................... 1
Significance of the Study .................................................................. 1
Problem Statement ......................................................................... 3
CHAPTER TWO - Literature Review ................................................... 5
Distance Education ......................................................................... 5
History and Growth ................................................................ 6
Instructional Technologies and the Internet ................................. 7
Faculty Participation in Distance Education ................................. 10
Interior Design Education ................................................................. 11
Attitude Change and Behavior Modeling .............................................. 13
CHAPTER THREE - Conceptual Framework ........................................ 17
Diffusion of Innovations ................................................................... 17
Rate of Adoption ................................................................... 18
Attributes of an Innovation ....................................................... 19
Relative Advantage ....................................................... 22
Compatability ............................................................... 25
Trialability .................................................................... 28
Complexity .................................................................. 3O
Observability ............................................................... 32
Gatekeeper ................................................................................... 35
Summary ...................................................................................... 38
CHAPTER FOUR - Method .............................................................. 40
Sample ......................................................................................... 40
Instrument .................................................................................... 41
Experimental Treatment ................................................................... 43
Experimental Design ........................................................................ 44
Procedure ..................................................................................... 45
Hypotheses and Research Questions ................................................. 46

vi

TABLE OF CONTENTS

Chapter & Topics Page
CHAPTER FIVE - Results ................................................................. 49
Sample and Procedure .................................................................... 49
Sample Demographics ..................................................................... 49
Instrument Reliability ....................................................................... 52
Data Analysis and Hypothesis Testing ................................................ 52
Research Question Analysis ............................................................. 56
CHAPTER SIX - Discussion of Results ................................................ 57
Summary of Results from Experimental Design .................................... 57
Summary of Results from Research Questions ..................................... 61
Relative Advantage ................................................................ 61
Compatability ........................................................................ 62
Trialability ............................................................................. 63
Complexity ........................................................................... 63
Observability ........................................................................ 64
Gatekeeper .......................................................................... 65
CHAPTER SEVEN - Conclusion ......................................................... 66
Limitations of the Study .................................................................... 66
Sample Size ......................................................................... 66
Attitude and Behavior .............................................................. 68
Study Design ........................................................................ 69
Recommendations for Future Research ............................................... 69
Summary ...................................................................................... 72
APPENDICES ............................................................................... 74
Appendix A - Construct Items and Reliabilities ..................................... 74
Appendix B — Slides from Experimental Treatment ................................. 76
Appendix C - Letter of Participation and Reply Postcard ......................... 87
Appendix D — Variables Means and Standard Deviations Using
Posttest Data ...................................................... 89

Appendix E — Means and Standard Deviation Values of Individual Scales. 90

BIBLIOGRAPHY ............................................................................ 92

vii

LIST OF TABLES

 

Description Page
Table 1: Reliability of Variables from Original Instrument .................. 42
Table 2: Content Analysis of Gatekeeper Measurement Items ........... 42
Table 3: Solomon Four-Group Experimental Design ........................ 44
Table 4: Timeline for Experimental Design Procedure ...................... 46
Table 5: Participants by Experimental Group .................................. 49
Table 6: Participant Demographic Data ......................................... 51
Table 7: Treatment Effect Results Using Posttest Data ..................... 54
Table 8: Multiple Regression on Intention to Adopt Using

Posttest Data ...................................................... 56
Table 9: Construct Items and Reliabilities ...................................... 74
Table 10: Variable Means and Standard Deviations Using

Posttest Data ...................................................... 89
Table 11: Mean Scores of Groups for Relative Advantage...... 90
Table 12: Mean Scores of Groups for Compatability .......................... 90
Table 13: Mean Scores of Groups for Trialability ............................... 90
Table 14: Mean Scores of Groups for Complexity .............................. 90
Table 15: Mean Scores of Groups for Observability ........................... 91
Table 16: Mean Scores of Groups for Gatekeeper ............................. 91
Table 17: Mean Scores of Groups for Intention to Adopt ..................... 91

viii

LIST OF FIGURES

 

Description Page
Figure 1: S-Curve Rate of Adoption ................................................... 19
Figure 2: Variables Influencing the Intention to Adopt ............................ 21
Figure 3: Distance Education Technologies & the Design Studio ............. 76
Figure 4: Teaching in a Design Studio 1 .............................................. 76
Figure 5: Teaching in a Design Studio 2 ............................................. 77
Figure 6: The Traditional Design Studio .............................................. 77
Figure 7: Student Step 1 .................................................................. 78
Figure 8: Student Step 2 ................................................................. 78
Figure 9: Student Step 3 ................................................................. 79
Figure 10: Student Step 4 ................................................................ 79
Figure 11: Student Step 5 ................................................................ 80
Figure 12: Faculty Step 1 ................................................................ 80
Figure 13: Faculty Step 2 ................................................................ 81
Figure 14: Faculty Step 3 ................................................................ 81
Figure 15: Student Step Download .................................................... 82
Figure 16: Student Step Preview ....................................................... 82
Figure 17: Student Assistance .......................................................... 83
Figure 18: Student Advantages 1 ...................................................... 83
Figure 19: Student Advantages 2 ...................................................... 84
Figure 20: Faculty Advantages ......................................................... 84
Figure 21: Disadvantages ................................................................ 85

LIST OF FIGURES

 

Description Page
Figure 22: Design Studio Strategy ..................................................... 85
Figure 23: Design Studio Summary ................................................... 86

CHAPTER ONE

Introduction

Coping with rapidly accelerating change is one of the most important
challenges in today’s world. With the multiplicity of new technology tools and
multimedia communication methods, today’s higher education system is moving
from the “industrial age” to the “information age”, as these institutions pursue
distance education as an alternative mode of instruction. Results of a survey of
4,000 two- and four-year universities by Market Data Retrieval (Eggen, 2000)
demonstrate the rush to offer more web-based distance education courses. The '
percentage of online degrees has more than doubled from 15% in 1998-1999 to
34% in 1999-2000. Likewise, distance education course offerings have also
increased from 48% in 1998-1999 to 67% in 1999-2000 (Eggen, 2000). Distance
education using the Internet can be considered an innovation because it is new,
original, and could supplement or even someday replace the current methods of
teaching in higher education. Currently, distance education is not widely
accepted. Like any innovation, it will take time to spread, or diffuse, in a social

system.

Significance of the Study
Distance education can be defined as the teaching and learning process
where half or more of the instruction occurs when faculty members are separated

from their students by location and/or by time. Distance education courses are

emerging in many fields of study. This study focuses on the development and
instruction of distance education courses by higher education faculty members in
the field of interior design. According to research by Abacus Associates (2000)
for the National Education Association (NEA), the two educational fields with the
highest percentage of distance education faculty involvement are math/science
(20%) and social science (15%). Only one percent (1%) of those surveyed teach
a distance education course in the area of the arts. No reasons were provided
as to either the lack of interest or inability to provide instruction through distance
education in these areas (Abacus, 2000).

Many distance education advocates have concentrated their research
efforts on the implementation of specific telecommunications technologies, rather
than the practice of instruction (Olcott, 1991). The majority of research in the
area of distance education focuses on student outcomes, course and program
design, and the effectiveness of distance education technologies (“what’s the
difference”, 1999). Yet research addressing faculty concerns and issues is
sparse (Visser, 2000). This study will contribute to the body of knowledge
involving the perceptions of the faculty body toward distance education.

The focus of this research will be on interior design educators, one of the
subsets of the arts. Only one percent of these educators are involved in distance ‘
education (Abacus, 2000). Today’s interior design education is based on the
traditional principles and instructional methods of the Ecole des Beaux-Arts, a
French school of design established in 1863. The Beaux-Arts educational

approach is based on instruction in small studio settings where design and

artistic demonstrations can take place. Other components of the Beaux-Arts
approach include a small student-to-faculty ratio of approximately 20 to 1

(“F IDER accreditation”, 2000) and a high level of interaction. Because of their
tradition of studio-based instruction, interior design educators may see distance
education as inappropriate to serve their instructional needs.

Research on the adoption of an innovation has focused on the adoption
rate, or the characteristics of the individual adopters (Rogers, 1995), with only
recent studies focusing on the attributes of an innovation as a way to understand
an individual’s intention to adopt (Moore & Benbasat, 1991; Plouffe,
Vandenbosch, & Hulland, 2001). This study contributes to the body of
knowledge addressing the attributes of an innovation (relative advantage,
trialability, compatability, Observability, and complexity).

Based on adoption theory, faculty should be more likely to adopt distance
education methodologies if it is recognized as better than traditional education, is
compatible with their values, and the results of participation are clearly visible. In
addition, if faculty members are given the opportunity to try teaching at a distance
and it is not perceived as too complex, it will more likely be adopted. An
additional construct addressing the role of peers the gatekeeper in the adoption

process is included in this study.

Problem sgtement
There is clearly a demand for online learning today (Everhart, 2000). Due

to an increase in distance education course offerings over the past 10 years,

interior design educators may soon be pressured to provide design education
through distance education methodologies. This study assesses the attitudes of
individual interior design faculty members toward the development and delivery
of distance education courses, using the attributes of an innovation as a
framework in data collection and analysis. This study will aid higher education
administrators and other educators to develop strategies to encourage the

adoption of distance education as an alternative method of instruction.

CHAPTER TWO
Literature Review

Distance Education

Access to higher education has increased in the past 30 years (Abe,
1988), and the demand for education from formal institutions is greater than the
economic capacity to supply them (Mani, 1988). Institutions of higher learning
are under public pressure to become more accountable for their educational
product and are looking for innovative solutions to meet this increasing demand.

The definition of distance education is continuing to change as the
technology used in the delivery of education also continues to change. Most
academics would agree that what separates distance education from other forms
of education is its reliance on some form of mechanical or electronic
communication (Dillon & Walsh, 1992). No universally accepted definition of
distance education exists. Consistent with the definition used in the NEA survey
(Abacus, 2000), the operational definition of distance education created by the
researcher and used in this study is: Distance education refers to a process of
instruction where the instructor and student are separated by time or place.
More than half of the interaction is in the delivery of synchronous or

asynchronous instruction via audio, video, and/or computer technologies.

Historv and Growth

Distance education has gained heightened awareness though it has a
long history in higher education. In 1840, Sir Isaac Pitman, the inventor of
shorthand, developed a way to provide correspondence courses by mail
(Matthews, 1999). This development continued with the initiation of the United
States Postal Service in the early 19th Century and its access across the country
(“what’s the difference”, 1999). In 1892, William Rainey Harper directed the
world’s first university distance learning program at the University of Chicago
(Sherron & Boettcher, 1997). The Industrial Revolution, World War I, and the
invention of radio and television opened the arena to more educational
opportunities, culminating in the use of computer communication in the last few
decades (Moore, 1989). The United Kingdom’s Open University, founded in
1969, marked a turning point for distance education with its multimedia approach
to education (Matthews, 1999).

Since the late 19608, acceptance of distance education has continued to
grow. The United States Department of Education’s report on distance education
at postsecondary education institutions (National Center for Education Statistics,
1 999) found “1,680 institutions offered a total of about 54,000 online-education
courses in 1998, with 1.6 million students enrolled” (p. 4). This is still a fairly
small percentage of students compared to the total number of students enrolled
in traditional Ieaming environments. However, the 2000 report from the
Department of Education found 44% of higher education institutions offered

some form of distance education in 1998. This is an increase from 33% reported

in 1995 (Weiss, 2000). A major external force influencing the development and
dissemination of distance education courses is the change in student
demographics. Today’s younger college students have been surrounded by
technology for most of their lives. The expectation of quick access to information
at all hours of the day and night will increasingly drive the need for education and

training on demand (Baird & Monson, 1992).

Instructional Technolggies and the lntemet

Distance education is being catapulted forward by the integration of
technology into the curriculum. Technological developments used in distance
education have the potential to revolutionize teaching and Ieaming by enabling
target groups to be reached and improving the overall quality of the educational
experience (Bates, 1995). The synthesis of computers and telecommunications,
the advances in fiber optic cabling, and the growing affordability of s0phisticated
technology tools increases the potential of delivering superior course content
(Dede, 1989). The intention of web-based instruction is not to use technology
simply as a substitute for face-to-face interaction or to deliver the same old
course in a new way (Rickard, 1999), but as a tool for increased student Ieaming.

The latest study by the United States Department of Education (Moore,
2000) reported institutions would be focusing their efforts on lntemet
technologies and two-way interactive video more than other forms of technology
in the future. Currently, 54% of distance education courses rely primarily on

video technology for the relay of instruction and 44% rely on web-based

 

technology (Abacus, 2000). Courses that rely primarily on the lntemet as the
medium of communication are often referred to as virtual courses or virtual
education, as the form of interaction is often indirect and not dependent on time
or place. Use of the lntemet in course instruction may vary from having the
course materials available on-line to making significant use of Internet technology
for class instruction. Virtual courses that rely in some way on the lntemet can be
divided into three models: independent, collaborative, and broadcast (Russell,
2001)

In the independent model, learning is unscheduled. Also known as
asynchronous communication, this model allows students to access the material
and interact whenever they wish. Asynchronous communication involves the
delivery of information between student and instructor but not at the same time or
in the same place. Media often used for delivery of information include:
telephone, facsimile, email, television, videotapes, audiotapes,
videoconferencing, satellite broadcasts, lntemet, and computer software.
Advantages of this approach include its flexibility in providing access to the
course material from many locations, allowing the student time to reflect, and
being cost-effective as text-based asynchronous systems do not require high-end
computers to operate (Mason, 1999). A disadvantage is the possibility for social
isolation. Students taking distance courses expressed concern of not being able
to mix with their peers when taking a distance education course (Eggen, 2000).
Ninety percent of students who participated in distance education courses in

Iceland in 1995 strongly agreed that there should be some face-to-face

communication in distance courses where they could meet the instructors for
both educational content and for the personal contact (Jonasson, 1997).

The synchronous model requires collaboration and communication
between students and faculty at prescheduled times. Access to materials may
be 24 hours a day, seven days a week, but class participation is at specified
times. Synchronous communication occurs when the instructor and the student
are both present at the time of instruction, even if they are in different
geographical locations. Two forms of synchronous communication are
videoconferencing and video animation. Synchronous communication has
advantages such as real-time interaction or telepresence, a means to motivate
the student to keep pace with the group, and the ability to provide timely
feedback from the instructor to the student or between students (Mason, 1999).
The expectation in traditional education is that the instructor will provide the
information and an appropriate interpretation of that material (Anderson, 1997-
98). In distance education, students are expected to take more responsibility for
their learning and to collaborate with peers (Baldwin, 1998).

The final model is known as broadcast, in which students access
previously recorded lectures on the Internet. This lecture-based form of
instruction places little emphasis on feedback from the faculty member or
interaction with the instructor and other students. Active participation is limited
and time management is essential. The advantage of this model is the self-
paced instruction that gives the student freedom to work on a personal time

schedule. All forms of lntemet instruction have advantages and disadvantages,

but in the end, the use of each depends on learning styles and the larger

educational context (Mason, 1999).

Facum Participation in Distance Education
The NEA study conducted by Abacus (2000) has shed light on faculty

participation in distance education endeavors. This research firm compared
feelings toward distance education by traditional faculty (n=130) and faculty who
teach one or more distance education courses (n=402). The two groups were
similar in their demographics, with distance learning faculty being full time (89%),
tenured (73%), and holding a masters’ degree (48%) rather than a Ph.D. (31%).
Both groups were split evenly between full professors (35%) and lecturers and
adjuncts (35%). Distance and traditional faculty are from similar academic
disciplines, such as math, science, business, education, and arts.

Abacus (2000) noted that 86%of distance education faculty members
developed their distance course from a traditional course. Traditional faculty
members are less positive toward distance education endeavors (51%) than
distance education faculty (72%). A significant portion (28%) of traditional faculty
has no opinion about the benefits of distance education (Abacus, 2000). These
faculty members are undecided and are waiting to see the impact of distance
education on students, faculty, and institutions. In a related study by Betts
(1998), 64% of faculty members, representing a variety of disciplines at a large
United States (US) university, stated they had never contemplated either

teaching, co-teaching, or designing a distance education course. How do faculty -

10

know that a particular pedagogical approach will work as well or better than the
present approach? Faculty members want evidence of the success of distance
education before making the effort required for potential transition (Duning, Van

Kekerix, & Zaborowski, 1993).

Interior Design Education

The methodologies used when teaching at a distance are truly innovative
and immersed in technology. Therefore, this instructional model may be
unfamiliar and viewed as incompatible with the traditional teaching methods
represented in disciplines such as interior design. Today’s interior design
education practices are based on the principles and instructional methods of the
Ecole des Beaux-Arts. Known as both a style of design and a school of design,
the Beaux-Arts approach focuses on personal instruction and criticism in addition
to a high level of interaction between students and instructors. The cornerstone
of the Beaux-Arts approach is the “design problem” given to each student at the
beginning of the semester. The student follows steps to analyze the design
problem and then continues to develop the design solution under the supervision
of master artists and architects (“architecture”, 2000). The design problem
begins with sketching and ends in final rendered drawings. The final evaluation
of the design project often consists of a juried exhibition and critique by invited
architects and designers.

Unfortunately, this “school of fine arts” was not consistent in its teaching

methodology. It did not provide basic instruction in paintings or graphics, but

11

 

 

 

 

   

catered to the advanced student engaged in Officm competitions (Boime 1982)

Formal instruction and theory were separate entities of education - In 1863

instruction shifted from the th eo'et'ca' to the practical and from the private to the

Public (Boime,1971). The Ecole des Beaux-Ans expanded its Curriculum
. - uction b ‘ : - .
beyond elementary drawmg "‘5" y d\V\d\ng No two sections: painting

and sculpture, and architecture-
The study of architecture has branched into various profesSi
. . . con cent . _ °"S. one of
thCh rs interior desrgn where the r 3170" Is on the more intim
ate/y Seal
aspects of design. An indrvrdual who practices the dISCIpIine of interior d
esiQn is
referred to as an interior designer- A“ Interior designer “is qualified by education
experience and examination to GNhance the function and quality of interior
s for the purpose of imPVOVi09 the quality of life, increasing product‘wttv.

space

and protecting the health, safety, and welfare of the public” (“FIDER webs-“e '

2000).

Perpetuated by past
teach in the same format as in the Beaux-Arts tradition, even though there is no

experience, interior design educators continue to

evidence to suggest that it is an effective means of instruction (R890 port, 1 934),

The current models 01 teaching and learning in higher education 3'9 not used
beca use they iltustrate the “right way”, but because the method has Worked for
slit/'7- a long time (Farrington, 1999). Change is being asked of the faculty in two

15, First, they are being asked to adopt new teaching tools. Second, they are
9
s
”3109 a
change the form of interaction with the student (Dias, 1999).

sked to alter the way in which instruction is delivered to the student and to

12

Academic fields such as natural science and mathematics have been
working with technology tools longer than other areas such as the arts and
humanities (BaldWin, 1998)- Lawn (1 998) 8‘30 found that diSCiplines in the arts
lag behind the schoo\S 0‘ b“ siness' engineefiw' 3““ meme in putting digital
technology into effect in their C” mema' Tec'hm‘osv has demonstrated “a

significant impact on the way art is taught, Studied, and practiced“ (LEWn 199
p. 56). As expressed in an amide by Bea Udoin ( 7990): “Well. those n ‘ 8‘
techniques may work in some other disciplines, but they certainly Won.:w .

(p. 25). Distance education may be see” as inappmpriate to serve the int:::: ”

of interior design and therefore faculty in this diSCipline may be reluctant to

pursue the endeavor.

Attitude Chan e and Behavior Modelin

As indicated by the 28% of faculty in the NEA survey who remain
undecided about distance education. there clearly remains a gap betvmeen the
POtential of web-based technoIOgy and its full utilization in higher edu Cation
(Abacus, 2000). The study of attitude and behavior is a complex area of
’eSea rch. An attitude may be defined as a learned predisposition to respond to a
giVen object in a consistently favorable or unfavorable manner (Fishbein & Ajzen, '
$73 ) .
As Triandis (1971) states, “attitudes are neither necessary nor sufficient
ufies of behavior" (p. 15). An individual’s attitude toward a specmc behavior is

a function of the beliefs about the intended consequences of performing the

13

Wu“...

 
   

(spawn-

 

 

 

behavior, An in dividual'5 behavioral intention is determined by his attitude
toward the innovations perceived ease of use and awareness of its usefulness
(Taylor & Todd, 1995). The medics" ”ml” °‘ ““8 variable is based on the fact
that perceived usefulness and 3358 Of use are lssues under the individual’s
control (Taylor & Todd, 1995} In addition, \he individuals evaluation of these

possible consequences is take" into account (Vallelend. Deshaies Q
. uerrier,

Pelletier, & Mongeau, 1992) and the Dre—ammo" amuse is base
pr ”Tiarily
on

indiIGCt experience (Karahanna, Sl'an. & Chen/any, 1999).
Research summarized by Millard and Bass (1991) identified attitude
change as an obstacle related to the adeption of instructional techno,ogy into the
curriculum. Attitudinal change is difficult to ascertain as it involves the personal
beliefs of a person (Millard & Bass, 1991). Because Ieaming is a relative“!
permanent change in behavior (Decker, 1986), the goal of implementing a
behavioral modeling training program is to influence a person’s attitude toward
an innovation and encourage a change in subsequent behavior.
Bandura (1 9??) determined that human behavior is learned
Obse Nationally through modeling that later serves as a guide for actiQn. The
emp h asis is on vicarious learning, by which individuals learn by imitating others
Withc: out receiving an immediate, observable reward. According to social learning
We (N four processes govern observational Ieaming (Ba ndura. 1 977), Learning
/in5 with attentional processes. These processes determine What behaviors

Vie noticed and what information is extracted from these observations, Retention
%

processes involve remembering previously observed behavior after the model is

14

no \ofiger present to provide direction. The third component involves mom,

reproduction processes, or the conversion of symbolic representations into
action. The final component involves motivation. Motivational processes of
learning influence the adoption of modeled behavior. If the outcomes of the
behavior are valued or rewarded, the behavior will be adopted (Bandura, 1977).

Behavior modeling research has been conducted on interpersonal
relationships, corporate training, supervisory roles in business, and adult
education (Buchanan & Badham, 1999; Nunns & Bluen, 1992; Gist, Rosen, and
Schwoerer, 1988). Decker (1986) found that modeling is superior in training
applications because demonstrations can be made both orally and in written
format. In their study of 160 computer users, Simon and Werner (1996)
determined that training with behavior modeling had a higher rate of user
satisfaction than self-paced study or use of a lecturing format. A meta-analysis
of 70 studies by Burke & Day (1986, as cited in Goldstein, 1989) demonstrated
the effectiveness of behavior modeling as a training method.

Behavioral modeling involves three stages of applied Ieaming: (1)
presentation of the role behavior; (2) imitation of the modeled behavior; and (3)

positive social reinforcement (Nunns & Bluen, 1992). These stages result in six

 

basic Ieaming states, which are: (1) new attitude; (2) manual skills, (3) social
skills; (4) verbal skills; (5) cognitive skills; and (6) memory for factual material
(Decker, 1986). Though all six states can be taught in training sessions, all

Programs of training attempt to have an affect on only one or more state.

15

   

 

 

Parry and Reich (1984) note several advantages to behavioral modeling,
including the ease of learning. Learning by imitation places little demand on the
instructor and learners because it is quick and easy. Because training done with
this technique is rather structured, instruction is uniform. Well-designed training
packages can be created to provide consistency between Ieaming sessions
within a set time frame. There are also disadvantages with this type of training.
First, the models are simplistic and offer only one solution to a given situation.
Second, training tends to focus on the process while ignoring the explanation of
the underlying theory. Third, because modeling follows the same format without
variation, learning is passive and monotonous. Therefore, the transfer of training I
may be weak. Even though participants may imitate the desired behaviors in
training, they fail to apply these behaviors outside the training arena (Parry &
Reich, 1984).

Rogers and Shoemaker (1971) believe the decision process of adopting
an innovation begins “when the individual is exposed to the innovation’s
existence and gains some understanding of how it functions” (p. 104). The
process of awareness and learning may occur through behavior modeling
training because modeling is recognized as the major vehicle for transmitting

innovative behavior in the process of diffusion of innovation (Bandura, 1977).

The ability to model a behavior, such as teaching a design course with distance
Education methodologies, can be achieved through an experimental treatment.
The Opportunity to visualize this instructional model may influence an interior

design educator's intention to adopt distance education.

16

 
  

    
 
  

to . >
.!'|\~,.“‘-h\h-

 

 

 

CHAPTER THREE
Conceptual Framework

Diffusion of Innovations

The conceptual framework for this study is the diffusion of innovations.

This is related to attitude change and behavior modification because an
individual’s beliefs and attitudes about an innovation (such as distance
education) have bearing on the individual’s decision process in adopting the
innovation (Rogers and Shoemaker, 1971). Rogers (1995) defines diffusion as
“the process by which an innovation is communicated through certain channels
over time among the members of a social system” (p. 5). An innovation is a
creative idea that works. It may be a process, product, method, or system. More
than an idea, an innovation is a continuous process put to action. What makes
diffusion different from communication in general is its focus on the acceptance
process of the innovation.

The innovation of interest in this study is the development and use of
distance education courses by interior design faculty members. According to
Rogers and Shoemaker (1971), research in the area of educational innovation

diffusion is not as prolific as in areas such as business and agriculture, and
therefore, it is “rather difficult to count on what is known about the diffusion of
educational innovations” (p. 58). Web-based education is known as a
technological innovation because it is a new process adopted by institutions of

higher education for their own use (Brown, 1981).

17

Rate.“ Adoption

One aspect of the diffusion of innovations is the time it takes for a person
or groups of persons to adopt an innovation. This process begins with the period
of time when the individual passes through the innovation-decision process. This
process has five stages: (1) knowledge stage, when an individual learns of an
innovation; (2) persuasion stage, which occurs when a favorable or unfavorable
attitude toward the innovation is formed; (3) decision stage, when an individual
engages in activities which lead to the adoption or rejection of the innovation; (4)
implementation stage, which occurs when the innovation is put into use; and (5)
confirmation stage, when reinforcement of the adoption decision is sought
(Rogers, 1995).

The rate of adoption is the speed with which an individual or group adopts
or starts using an innovation. An individual’s perception of an innovation, not the
innovation itself, affects an innovation’s rate of adoption. Most innovations have
an S-curve rate of adoption (see Figure 1). This is usually measured by the
length of time (X-axis) with the percentage of individuals who adopt the

innovation (Y-axis). As time increases, so does the percentage of adopters.

18

Percentage of Adopters

Time

Figure 1: S-Curve Rate of Adoption

There is an obvious variation in the slope of the “S” from innovation to
innovation and even with the same innovation but in different social systems.
Rogers and Shoemaker (1971) analyzed diffusion research and found that one
educational innovation (modern math) reached 100% adoption in five years,
while another innovation (kindergarten) took 50 years. Of the 12 innovations
studied by Mansfield (1961, as cited in Lowe 1995) from the iron, steel, railroad,
brewing, and coal industries, nine of them took over 20 years to completely

diffuse into their particular societies.

Attrib utes of an Innovation

 

Every innovation has unique characteristics that are perceived differently

by every individual. These include relative advantage, compatibility, trialability,

19

 

  
  

"in...“

 

 

 

complexity, and obsewabilitY, which will be discussed in detail. Rogers (7995)
states, “past research indicates that the attributes of an innovation are the most
important characteristics of innovations in explaining the rate of adoption” (p. 16).

Rogers (1995) suggests the presence or absence of some of these
attributes can predict whether it will be adopted and its rate of diffusion through
the system. Karahanna et al., (1999) support this claim. Their research of
information technology adoption found that potential adopters based their attitude
on the innovation’s characteristics. These attributes are not the only variables for
determining the rate of innovation adoption, but they constitute an important
component to adoption.

Of all the diffusion research, relatively little effort has been spent on the
analysis of the innovation and how its properties affect its rate of adoption
(Rogers, 1995). Rogers and Shoemaker (1971) found that much of the diffusion
research literature is devoted to the studying of “people” differences based on
innovativeness (i.e. the adopter categories) but little effort has been given to
analyzing the “innovation” differences (i.e. the attributes of an innovation). The
research done in this area has led to a standard classification scheme of the
attributes of an innovation.

Another area important to adoption is an individual’s intention to adopt.

This is related to a person’s attitude in which beliefs will predispose action

(Rogers, 1995). An individual’s behavioral intention to adopt an innovation (such

as distance education) can be influenced by increased awareness of the

 

innovation, the active seeking of information about the innovation, persuasion by

20

mass media messaging, an individual offering an opinion, or a group of peers
who can offer social reinforcement (Rogers, 1995).

In addition to the attributes of an innovation, a person who can influence
an individual’s intention to adopt an innovation is the gatekeeper. A gatekeeper
is someone appointed by an organization to oversee the allocation of resources,
such as a chairperson or dean in higher education. They can either increase or
decrease the rate of innovation diffusion.

Figure 2 illustrates the model for the study that suggests the attributes of
an innovation, in addition to the gatekeeper, will influence an interior design
faculty member’s intention to adopt the innovation of distance education. Each

model component will be defined and discussed in detail.

Relative
Advantage
Compatability

 
   
    

 

 

     

Observability Gatekeeper

Figure 2: Variables Influencing the Intention to Adopt

21

Relative Advantage.

The first attribute related to an individual’s intention to adopt an innovation
is relative advantage. Relative advantage is the degree to which an innovation is
perceived as better than the innovation that it may replace and is based on the
perceptions of the individual.

Often expressed in economic profitability, the relative advantage of a new
idea may be stressed by a crisis, either speeding up or slowing down the rate of
adoption. For example, Sutherland (1959, as cited in Rogers 8. Shoemaker,
1971) concluded the labor shortage in World War II quickened the adoption of a
cotton spinning innovation in England. Plouffe et al. (2001) found that
consumers participating in a card-based payment system in Canada identified

relative advantage as the most important characteristic leading to adoption.
Likewise, Axin (1988) found relative advantage to be the single most significant
indicator of firm export performance. Relative advantage may be seen as
decreasing one’s discomfort with the innovation, thus saving time and effort,
lowering risk, and providing immediate rewards. The greater the recognized
advantages of the new innovation, the quicker the innovation will be adopted.
Relative advantage is positively related to the adoption of the innovation.

In academic settings, the acceptance of distance education as an
innovation lies with the faculty. Many faculty members are realizing the benefits
of teaching and Ieaming at a distance. One benefit is the flexibility of scheduling
for the instructor (Taylor and White, 1991; Landstrom, 1995). Though the fear of

job loss is real (Camevale & Young, 1999; Guernsey & Young, 1998),

22

respondents to the NEA survey (Abacus, 2000) believe the number of faculty
jobs will not decrease, the quality of the instruction will not decline, and students
will remain as candid in the distance classroom as they are in the traditional
classroom. This study found that faculty members teaching a web-based course
rated their web-based course significantly higher than their traditional courses (of
the same subject matter) on these five items: (1) Providing access of information
to students; (2) Assisting the students in mastering the subject matter; (3) Giving
the students a high quality of course material; (4) Dealing with the variety of
student learning styles; and (5) Assessing the course’s educational effectiveness
(Abacus, 2000). In research by Baird and Monson (1992), many educators who '
had taught distance courses found the experience better than their on-campus
experience, both in course organization and student interaction.

Additional benefits include the accuracy and consistency of distance
education instruction. All students viewing the lecture are guaranteed to receive
the exact same course material, regardless of the instructional model
implemented (Charp, 2000). All students get the same view of the professor and
material, unlike the front row advantage in conventional classroom situations
(Romiszowski, 1988).

On the other hand, faculty members may not be aware of the relative
advantages of distance education, especially in the areas of time and workload.
A distance education course that is delivered via the lntemet takes more time to
develop than a traditional course, often twice as much (Mason, 1999; Sherron 8.

Boettcher, 1997; Gaud, 1999; Abe, 1988). Faculty members also agree that

23

teaching a distance learning course takes more time than teaching a traditional
course (Abacus, 2000; Rickard, 1999; Mason, 1999). Over half (53%) of the
respondents in the NEA survey (Abacus, 2000) spend more hours per week
preparing and delivering their distance education course than they do for a
comparable course taught in a traditional manner.

The individual assessment of students is another challenge faculty face
regarding their time. Faculty members teaching a distance education course
estimated they spent approximately 15 minutes per student, per week (Gaud,
1999). One hundred percent of the participants in Landstrom’s (1995) study
(n=20) found that the time spent grading assignments and exams in distance
education courses was extensive. Faculty members also find it difficult to spend
time learning new instruction tools (Lawn, 1998). Individual faculty member’s
interest in professional development of technology skills is low and often viewed
as so labor intensive to learn that it wastes their time (Parker, 1997).

In addition to the time it takes to develop and teach a course, faculty have
concerns regarding the weight and recognition of distance education on their
workload. Workload is “the distribution of faculty effort and the outcomes of that
effort over time” (“principles and guidelines", 1998, p. 5). Workload policies vary
between and within institutions. Studies on faculty workload typically focus on
average course loads, contact hours, and credit loads (Layzell, 1996). . It is
believed that the distance education instructor will have a larger workload if
multiple locations are involved in the instructional model (Willis, 1998). Workload

policies for traditional campus courses are available. Policies for distance

24

education teaching workloads are either not included in university workload

statements, or are unclear and ambiguous.

Compatabil'mr.

The second attribute of an innovation is compatability. Compatability,
which is also positively correlated to the intention to adopt, involves the
perception of consistency between the existing values, past experiences, and
needs of the potential adopter. Innovations that are consistent with these values
and norms will be adopted rapidly. Compatability makes the innovation more
meaningful to the adopter because it ensures security and reduces risk. The
question “Is distance education compatible with existing academic values and
traditions?” must be answered by individual faculty members prior to adoption.

In addition to technology, another force pushing the move to distance
education is the constantly changing demographics of the student body.
Changes in the student population and the rapidly expanding technology provide
ideal opportunities for colleges and universities to pursue the creation of distance
education courses and programs. Distance education may be perceived as
compatible with traditional education because it can address problems of scale,
rarity, and cognitive Ieaming styles. Students with unusual Ieaming needs (i.e.
English as a second language), students desiring courses in atypical subjects
(i.e. Japanese), and students who have a more dominant visual Ieaming style
(Dede, 1989; Massy & Zemsky, 1995) can more easily be accommodated in

distance education courses. Technology allows complex content to be conveyed -

25

 

 

 

more effectively due to the integration of multiple representations of material
such a computer animations with audio and video (Dede, 1989). The format and
technology used in many distance education courses offer the faculty an
opportunity to customize their courses to facilitate student learning styles, goals,
and abilities while providing instruction on an “any time, any place" basis (Massy
& Zemsky, 1995).

According to theory, distance education must be consistent with the
existing values of faculty before it will be adopted. In dual mode institutions
where distance education and traditional classroom classes are taught, faculty
may suspect that distance education courses are not as rigorous as regular
courses (Landstrom, 1995; Anderson, 1997—98). Mani (1988) found the
curriculum content and evaluation methods were the same for many distance
and traditional courses. Dillon (1989) found that 83% of faculty teaching
university teleccurses in the Oklahoma Telecourse Program believed they were
of acceptable academic quality, with an equal or greater level of difficulty when
compared to traditional on-campus courses.

Compatability may be affected by innovation negativism. Innovation
negativism is the degree to which a previous innovaticn’s failure conditions the
receiver of the message to reject future innovations (Rogers & Shoemaker,
1971 ). This occurs when a previous innovation was not adopted or was
discerned negatively. An example of this would be the failed attempts of
technology, beginning when Thomas Edison first predicted in 1922 the motion

picture was to revolutionize the process of Ieaming and that it would surpass the

26

 

 

 

 

use of classroom textbooks (Bollentin, 1998). Since its advent in the early
19505, television has not made as much of an impact on education as predicted.
Television and the VCR that emerged in the 19808 were predicted to close movie
theaters. Yet movie theaters still exist and are flourishing (Gandolfo, 1998).

Faculty work expectation may be incompatible with distance education
methodologies since the professor’s job description is so rapidly changing.
Today’s faculty member must be adept at facilitating students’ Ieaming by
focusing on the process of quality instruction (Beaudcin, 1990). Michele Tolela
Myers (2000), President of Sarah Lawrence College, wrote the “emergence of
computers challenges us to know what our business is. We must respond that
we are in the business of ideas, not information, of forming minds, not filling
them” (p.»A25).

As the “sage on the stage," the instructor is recognized as an information
provider who lectures to a room full of students. With distance education, the
instructor seeks to create an environment in which students discover the
knowledge for themselves. This places the instructor in the role of navigator,
coach, mentor, or the “guide at your side” (Denning, 1999). This forces the
faculty member to go beyond his traditional role of lecturer and grader.

Yet faculty members see themselves as creators of the curriculum and
content delivery experts, rather than mere managers of information. Faculty
members who prefer “privacy in teaching and ‘hands-on’ involvement hesitate to
use the new technologies" (Rose, 1982, p.14). The emergence of a “cyberprof”

causes anxiety in many faculty members who fear that students will be

27

 

 

processed in a factory-like model where the faculty grades and makes telephone
calls (Catchpole, 1992). Denning (1999) notes it is only a “matter of time until
these technologies mature and become capable of automating important parts of
what we now call coaching, facilitating and guiding” (p. 4).

Involvement in distance education may also lessen the much valued
autonomy and independence of faculty. Faculty members value their autonomy
(Gandolfo, 1998) and are “not easily persuaded to change time—honored
pedagogies from which they themselves learned successfully” (p. 35). Teaching
is seen as a solo activity in which the learning situation is driven by the force of
the instructor’s personality (Rose, 1982). Faculty teaching distance education
courses may find they no longer have sole responsibility for creating instructional
materials, organizing and supervising activities, and evaluating student
performance. More likely, a team of instructors and specialists share various
roles in the development of a distance course (Bers, 1999). This team approach
may undermine the faculty members’ control of the curriculum and their
independence (Olcott & Wright, 1995), resulting in the fear that distance

education will be truly distant (Moore, 1989).

Trialabil'fiy.
Trialability is the third attribute of an innovation. Trialability is the degree
to which an individual may experiment with the innovation on a limited basis.

New ideas that are tried incrementally, on the installment plan, and as “pilot

tests” are more likely to be adopted as they reduce anxiety and uncertainty.

28

Distance education pi\ct prolBCts provide faculty with evaluation data for
improving instruction and for determining the feasibility of implementing the
course on a permanent basis. Spotts and Bowman (1995) propose faculty
members and administrators need time and experience with an innovation (such
as distance education) to incorporate these new ways of learning into behavioral
patterns. Trialability is positively correlated with the intention to adopt.

Evidence suggests that faculty attitudes toward teaching with technology
improve as they become more familiar with it and the process of teaching at a
distance (Dillon & Walsh, 1992). To help faculty ease into distance education
endeavors, many universities offer faculty development programs. Faculty
development can be defined as the practice of improving faculty performance
and opportunity for the faculty member to produce better work (“American”, 2001;
Gillespie, 1998). By providing faculty the opportunity to explore new
technological applications and investigate alternative teaching methods, faculty
can develop insights into designing their own courses.

Yet in many institutions, the opportunity for development and training is
lacking (Murphy & Terry, 1998). A NEA survey found that there was a positive
relationship between a high degree of technical support and whether a faculty
member has positive feelings toward distance education (Abacus, 2000).
lnfonhation specialists have been hired at many universities because faculty
need more than basic computer training. They need advanced information and
skills to keep one step ahead of the students and the competition. But if these

inforrnaticn specialists are too busy to teach the faculty, the faculty members feel

29

\cst and on their own (McCollum, 1998), decreasing the perception Of distance

education compatability.

Complexity.

The next attribute of an innovation is complexity, which is an innovation’s
degree of difficulty in usage and understanding. There is a continuum between
simplicity and complexity on which all innovations can be placed. Some
innovations are clear in their meaning while others are not. New ideas that are
simple to understand are adopted more rapidly than ideas that require an
individual to seek out new skills and understanding (Rogers, 1983). For
example, Graham (1956, as cited in Rogers & Shoemaker, 1971) looked at the
vastly different diffusion rates of television and the card game known as canasta.
He found canasta to be more difficult to learn and an active, rather than passive,
activity. The Ieaming of canasta occurred through detailed personal explanation
by other card players. On the other hand, television is a relatively simple idea
that only required the ability to turn a knob. In the case of distance education,
technical systems must work efficiently and be easy to understand in order for
faculty to focus on the instruction. Complexity is negatively correlated with the
intention to adopt an innovation.

As higher education turns more to distance education, faculty members
will be expected to have some degree of comfort with technology. While the
written word and the use of textbooks are entrenched in traditional education, the

use of instructional technology is being used to achieve instructional objectives at

30

a distance (Spotts & Bowman. 1995). Technology is a direct agent of change
because it affects the way faculty members do their work and interact with their
colleagues. In its broadest definition, technology is the application of science to
a practical problem (Dalton, 1989).

E. Michael Staman (1990), Associate Vice President for Information
Services at West Chester University, addressed the lack of technological
progress in higher education, “the use of technology in pedagogic environments
is not commonplace, and what momentum exists is developing at an
excruciatingly slow rate" (p. 35). Murphy and Terry (1998) surveyed faculty
members teaching in the college of agriculture at a land grant university as to
their competency with distance education technology. Over 44% were not
familiar with teaching methodologies used in teaching distance courses and were
generally negative concerning their competence in producing appropriate
instructional materials for these types of courses. In addition, of 306 full-time and
part-time faculty members at Western Michigan University, only nine percent
indicated knowledge of the instructional technologies utilized in distance
education with six percent indicating experience with them (Spotts & Bowman,
1 995).

The complexity of an innovation such as technology can also be a
motivating factor. Research at Iowa State University (Stinehart, 1988) showed
that technology, along with curriculum control, is a co-determinant in the faculty
members’ willingness to continue their initial distance education endeavors.

Assisting faculty to integrate technology into higher education instruction is the

31

singie most important info mation technology challenge (“the continuing
challenge,” 1999). Most campuses have information technology development
programs and campus support centers where technology support personnel can
be available during traditional and non-traditional hours. Faculty members rate
technical support as significantly more important to the success of their course
than the type of student or the type of educational institution (Abacus, 2000).
Despite the negative connotation given to the labor-intensive technology needed
in distance education courses, faculty respondents to the NEA survey gave
higher ratings to library and laboratory facilities, and to the level of technical

support provided by the institution than expected (Abacus, 2000).

Observabil'gy.

The next attribute of an innovation is Observability, which is the degree to
which the results of the innovation itself are not only visible and communicable to
others, but the idea of the innovation is also visible (Rogers, 1983). Rogers
(1995) illustrates the use of cellular phones as an innovation that is highly
observable. If it is easy to observe the results, the innovation is more likely to be
adopted. If an innovation is not easily seen or even described, adoption is
hindered. For example, Rogers and Shoemaker (1971) report that pre-emergent
weed killers sprayed on farmland before the weeds even appear were very
slowly adopted. Why? There were no dead weeds that the farmers could show
to their neighbors. Therefore, some innovations do not lend themselves to visible

demonstrations. This is similar to distance education because a faculty member

32

cannOt “see" student \earni'ig. but only the outcomes of that learning process.
Observability is positively correlated to the intention to adopt.

Since Observability focuses on the tangible results from distance
education, these alternative technologies can provide a degree of motivation that
is not present in traditional classroom instruction. One distance education
instructor at the University of Windsor, interviewed by Landstrom (1995), felt that
preparing a distance course forced him to view the course through the eyes of a
student. He felt students who might otherwise be intimidated by the amount of
unfamiliar material were better served in a distance education course because
the material had to be accessible without an instructor present for explanation.
Self-paced Ieaming is enabled with distance education technology, due to a
continuous assessment of student progress and learning. The instructional
process is then transformed into a more outcome-oriented enterprise (Massy &
Zemsky, 1995). Student advantages cited by faculty members involved in the
Oklahoma Telecourse Program included the ability for students to see concrete
examples of abstract concepts, the opportunity for the students to review
programs more than one time, the ability to have a variety of viewpoints, and the
ability to see the top names in the field of study (Dillon, 1989). Recent research
has demonstrated that students educated in cyberspace learn as well as, or
better than, traditional learners (Navarro & Shoemaker, 2000; “what’s the
difference”, 1999; Russell, 1999; Smith, 1983, as cited in Whittington, 1987).

Student to student and faculty to student interaction can be a benefit of

distance education. In the recent NEA survey, faculty members rated their web-

33

based courses on the sarfle level with traditional courses when addressing the
goal of developing student interactivity (Abacus, 2000). In addition, many
students experience a higher intensity of participation than in the passive state of
traditional lecture formats (Farrington, 1999). Beaudoin (1990) states that
students who commute to campus one or two evenings a week, sitting
anonymously in a classroom with 50 other students will have little interaction with
the instructor, despite the close physical proximity. Off-campus students
participating in distance education courses are more likely to develop a
productive one-on-one relationship with the instructor due to periodic contact and
detailed feedback. Faculty members involved in distance education endeavors
feel their students are disciplined, highly motivated (Landstrom, 1995), and
actively involved in the education process, rather than being passive recipients of
information (Bellman, 1992).

The results and benefits of distance education may not be as visible or
tangible as the examples mentioned previously. Concerns about the recognition
of distance education in the faculty reward system can be considered a negative
aspect of Observability. Because the promotion and tenure system is an integral
component of the traditional academic culture, there is a need to recognize and
reward distance education efforts in the same manner as traditional teaching
(Sherron & Boettcher, 1997). Yet distance education is rarely mentioned as an
activity for which faculty members should receive promotion and tenure “credit”
(Wolcott, 1997). In interviews conducted with 32 faculty members, Wolcott

(1 997) found that several faculty members (no number given) thought distance

teaching should be weightECl more heavily than traditional classroom teaching in
the promotion and tenure process due to the additional time it takes to create and
teach a distance class. Gunawardena (1992) summarizes the biggest frustration
of distance education faculty as “the lack of recognition for the amount of time
and effort that goes into planning and teaching a distance class” (p. 70).
Observable behaviors are limited by observing the people with whom one
associates (Bandura, 1977). If distance education is not visibly recognized, the

adoption process will be slow.

Gatekeeper

A gatekeeper is an individual who is empowered by the leadership of an
institution to distribute resources and make decisions. The gatekeeper is often a
person in authority who controls the access to resources. He is usually from a
small group of individuals who have been empowered by their institution to make
decisions. The concept of the gatekeeper as a role in organizations began with
the social psychological research of Kurt Lewin in the mid-1940s David Manning
White then applied Lewin’s theory to the field of communication (Divelbiss, 1981 ).
Since that time, the term has been so widely used that it is now considered
common jargon in a wide variety of contexts.

A necessary function of the gatekeeper is the dissemination of scarce
resources. The gatekeeper has to select from a mass of detailed information a

few items that are worthy enough to pursue, given the conditions of limited

resources such as budget, available labor, and time (Divelbiss, 1981). If a

35

gatekeeper moves information or resources through an organization to the right
person in a timely manner, he or she is viewed positively. On the other hand, if a
gatekeeper retains information or resources in a negative way, he or she is
considered a bottleneck in an organization’s communication network (Rosner,
2001). For example, medical physicians must ration medical care to individual
patients. By enabling some to receive care, other medically needy persons may
not be granted access and therefore, will suffer the consequences of that denial
(Reitemeier, 1991). Also in the field of medicine, Bodenheimer, Lo, and Casalino
(1999) conducted a survey of chronically ill persons younger than age 65 and
found that 22% were unable to see a specialist due to the primary care
physician’s role as gatekeeper.

The gatekeeper in higher education is often an individual in an
administrative position. He serves the various needs of the institution, college, or
department as a whole, as well as individuals in the faculty body. A department’s
program coordinator is important in determining the future direction of the
program and its teaching innovation (Clark, 1993). The program coordinator
must be an impartial decision maker who is objectively rationale because he
schedules and approves teaching assignments, allocates financial resources,
and determines which academic activities will receive support and which
activities will be rewarded in the promotion and tenure system. In addition, these
administrators can determine the extent of faculty training or re-tooling in the
area of distance education (Olcott & Wright, 1995). After all, major innovations

are often introduced as part of a top-down process (Lowe, 1995). On the other

36

hand, he or she is also the advocate and sponsor of the faculty’s interests
(Erickson 8 Shultz, 1982). Therefore, the gate swings in both directions. The
gatekeeper experiences conflicting expectations due to his double function as
both advocate and judge.

The role of the gatekeeper in the adoption process is to make key
decisions about which innovations to diffuse, how to diffuse them, and to whom
(Rogers, 1995). As centralized authority figures, university administrators make
the decision for a faculty member to teach a distance course. Dalton (1989)
states that this “edict-from-on-high approach typically generates fear and anger”
inthe faculty (p. 20). Faculty dislike the idea of administration planning and
developing a technology-based instructional program without consulting with
them, as'witnessed in the failure of the State University of Nebraska project in
the early 19705 (Millard 8 Bass, 1991). This project failed because the faculty
members were all but ignored, thus limiting the involvement and subsequent
support of the academic community. Seven percent of faculty participating in a
study by Clark (1993) expressed their doubts about distance education based
solely on a distrust of university administrators. The result is that faculty
members feel administrators are telling them how to teach and how to do their

job, when the effort may be simply to assist or advise them (Beaudoin, 1990). As '
Staman (1990) states “integrating technology into the curriculum is not an
administrative process. It is a faculty process which requires a great deal of

administrative support” (p. 36).

37

 

Faculty members recognize the important role of the administrator and
wish to see this group commit to distance education before the faculty agree to
participate. Administrative support was critical (p <.001) to 168 faculty members
i mplementing technology in their teaching at 3 Midwest state university
(Gueldenzoph, Guidera, Whipple, Mertler, & Dutton, 1999). Faculty members
may be reluctant to expend their time and energy on an endeavor that will be
discarded in a short time. They may remember the experimental distance
education projects started in the 19805 and 19905 that were not continued after

external funding ceased (Laaser, 1988; Eggen, 2000).

Summagy

Distance education is a momentous reconfiguration in higher education
instruction and has triggered interest and motivation on one hand, and conflict
and opposition on the other. Motivated by individual faculty self-interest and
organizational concern, faculty members from all disciplines are struggling with of
how to appropriately utilize technology and distance education methodologies in
the education process.

The five attributes of an innovation from Rogers’ (1995) diffusion of
innovation can be combined with the role of the gatekeeper to assess the

attitudes of interior design faculty members toward distance education. Social
learning theory and behavioral modeling provide the framework for an
experimental treatment. The experimental treatment consists of a brief audio

and video presentation on CD-ROM that demonstrates how an interior design

38

 

 

course can be taught with distance education methodologies. This treatment is

i ntended to influence a faculty member’s intention to adopt distance education.

39

 

CHAPTER FOUR

Method

This chapter presents the full study design, methodology. instrumentation,
data collection procedures, statistical analysis design, hypotheses, and research
questions involved in investigating interior design faculty member’s perceptions

of distance education. An experimental treatment for a Solomon four-group
experimental design was developed, and administered to the sample by the
researcher. The sample included higher education interior design educators

teaching in the US.

Sample

The sample included faculty members from the Interior Design Educators
Council (IDEC) organization. Founded in 1963, IDEC is devoted to the promotion
of education and research in interior design. IDEC concentrates on
strengthening the avenues of communication between interior design educators
and interior design practicing professionals (“IDEC website”, 2001). At the start
of this study in September 2001, 514 members residing in the US. were included
in this population. Participation in this study was voluntary. The protocol for self-

selection is described in the following procedures.

40

 

Instrument
This study utilized an experimental design format that will be discussed in
detail. A survey instrument served as both pretest and posttest evaluation.
Faculty members were invited to add written comments. Requested
demographic variables included age, membership in professional design
organizations, years of teaching experience, gender, ethnicity, and the type of
institution at which they taught.

The survey instrument focused on the attributes of an innovation as
described in Rogers (1995) and Moore and Benbasat (1991), These attributes
and the number of measurement items are: relative advantage (3); compatibility V
(3); trialability (3); complexity (4) and Observability (7). Due to its established link
in the learning and adoption process, perception of the gatekeeper (4 items) was
also measured. Finally, an additional construct, intention to adopt (4 items), was
included in the instrument to “capture the respondent’s sense of urgency to
formally adopt the innovation” (Plouffe et al., 2001, p. 69). Individual
measurement items are provided in Appendix A. Comments on distance
education were also solicited from participants.

All items were presented on a seven-point Likert—type rating scale ranging
from strongly disagree (1) to strongly agree (7). The items related to the

attributes and intention to adopt were developed and extensively tested by Moore
and Benbaset (1991) and modified by Plouffe et al. (2001). The reliabilities for
each attribute (Moore & Benbaset, 1991) and for the intention to adopt (Plouffe et

al-, 2001) are listed in Table 1.

41

 

 

 

Table 1'. Reliabilfiof Variables from Original Instrument - 7

 

 

 

 

 

 

l Relative Advantage 0.92 J
Compatibility 0.83
Complexity 0.80
Trialability 0.71
Observability 0.73
Intention to Adopt 0.95

 

 

 

 

Based on the literature, measurement items were created by the
researcher to assess the perception of the gatekeeper. The items and the
definition of the gatekeeper were presented to 22 faculty members in design-
related disciplines for content analysis. After the initial analysis phase, one
gatekeeper item, which had both the dean and the program coordinator listed in
the same statement, was divided into two separate items. The second phase of
analysis was conducted with 15 graduate students in the field of education. All

items achieved inter-rater reliability with 63-85% of respondents (see Table 2).

 

Table 2: Content Analysis of Gatekeeper Measurement Items
Phase 1 Phase 2 Measurement Item

 

 

 

 

1 75 00/ I am worried there may be a lack of support for
95.2% ' ° distance education by my dean.
2 84 6% I am worried there may be a lack of encouragement

from my program coordinator.

 

3 . I worry that my program coordinator's commitment to
L 77.8% 63.6% distance education initiatives will wane as time goes
4

 

by.

I am concerned about the lack of release
time/compensation awarded by my program
chairperson to adequately develop a distance
education course.

 

53.3% 84.6%

 

 

 

 

 

42

 

Experimental Treatment

The treatment consists of an automated instructional presentation on CD-
ROM (created by the researcher) to demonstrate the process and technology
used in the instruction of a distance education interior design course. An existing
interior design course at Michigan State University, entitled Computer-Aided
Design and Structural Systems, utilizes a high degree of web-based technology
and was used as an example of how an interior design course could be
conducted at a distance (Bender, Vredevoogd, & Witt, 2002). The content of the
treatment begins with a listing of the advantages and disadvantages of teaching
a traditional design studio. The focus of the treatment is a process for using
distance education methodologies in teaching a design studio course. This
includes a four-step student process for completing the weekly design
assignment, converting the assignment to image format, and uploading it to the
course website. Then there is a five-step faculty process that is used for
compiling all student assignments into one presentation file, creating an audio
critique file, and uploading both files to the course website. Finally, there is a
two-step student process where the student downloads and reviews the
presentation and critique files to make changes to his design solution. The
treatment concludes with a short list of student and faculty advantages for using
distance education as the instructional model for teaching interior design studio
courses. See Appendix B for slide illustrations. The development of this

instructional presentation represents one application of behavioral modeling.

43

 

Experimental Design

The Solomon four-group design (SFGD) is a true experimental design. To
qualify as a true design, random assignment of subjects to each of the four
groups must be involved (Gay, 1996). The SFGD combines the pretest-posttest
control group design and the posttest only control group design (see Table 3).
Four groups are formed: two groups are premeasured (one control and one

experimental) and two groups are not premeasured (one control and one

 

 

 

 

 

 

 

 

 

experimental).
Table 3: Solomon Four-Group Experimental Design
GROUP PRETEST TREATMENT POSTTEST .
G1 Pre-Tested Treatment Post-Tested
GZ Pre-Tested No Treatment Post-Tested
G3 Treatment Post-Tested
64 No Treatment Post-Tested

 

 

 

 

 

 

The SFGD has been used with success in fields such as drug abuse
resistance education (Dukes, Ullman, & Stein, 1995), effects of newly relocated
nursing home residents (Haight, Michel, & Hendrix, 1998), assertion training
(Aschen, 1997), band students and the integration of students with disabilities
(Johnson & Darrow, 1997), and hope and humor (Westburg, 1999). The SFGD
eliminates nearly all sources of internal and external invalidity. Threats to internal .
and external validity that are minimized by the SFGD are: history, maturation,

testing, instrumentation, regression, selection, mortality, selection interactions,
pretest-X interaction, and multiple-X interference (Gay, 1996). Gay (1996) also
states that this design increases generalizability. As summarized by Michel and

Haight (1996), the process of pre-and post-measurement reduces between-

 

subleCt variation, “'lncreasing the power of the study to detect true intervention

effects” (p. 367). If a posttest only design is used, the risk of a pretest effect is
eliminated but the amount of change is unknown (Eckhardt & Ennann, 1977). By
combining the two designs together into a four-group design, interaction effects
can be revealed and controlled. These may include effects of selection,
maturation, instrumentation, regression, sampling, and treatment (Eckhardt &
Errnann, 1977) that could limit the generalizability of the study (Walton Braver a,
Braver, 1988). Though considered a strong design, SFGD has been
underutilized for reasons such as its complexity, little research in pretest
sensitization effects, the need for a larger sample size, and the lack of certainty

concerning the stages of analysis (Walton Braver & Braver, 1988).

Procedure
This procedure was reviewed and approved by Michigan State
University’s University Committee on Research Involving Human or Animal
Subjects (UCRIHS). Interior design faculty members who do not use distance
education methods were the target sample for this study. Initial correspondence
was sent to 514 IDEC members residing in the United States to explain the study
and to request their participation (see Appendix C). The mailing list was provided
to the researcher from IDEC in August 2001. The procedure and timeline for the
execution of this experimental design is shown in Table 4. A self-addressed,
stamped postcard was included on which the potential participant indicated his

willingness to participate in the study (see Appendix C). As participation

45

 

postcards were returned, email addresses and other information were input into a
spreadsheet to prepare for division into the four groups. Participating
respondents were randomly assigned to one of the two experimental groups or

the two control groups by using a table of random numbers.

 

Table 4: Timeline for Experimental Design Procedure

 

9/08/01 Request participation from all IDEC members via postcard

 

10l20/01 Randomly distribute participants into four groups

 

10/22/01 Mail pretest to Group 1 and Group 2

 

11/12l01 Email reminder to Group 1 and Group 2

 

11,14/01 Mail treatment and posttest to Group 1 and Group 3
Mail posttest only to Group 2 and Group 4

 

12/12/01 Email reminder to all groups; postcards to unknown emails

 

1/22/02 Email second reminder to all groups

 

 

 

2/01/02 Begin data analysis

 

Directions for completing the questionnaire, the treatment presentation on
CD-ROM, instructions for watching the treatment presentation, a self-addressed
stamped return envelope, and a hard copy of the presentation were all provided
to the participants. Responses were kept confidential. The questionnaires were
coded for tracking purposes only, in order for group identification and the

electronic mailing of reminders. Each participant kept the CD-ROM presentation.

Hypotheses and Research @estions
H1: Interior design faculty members who are administered the experimental
treatment will exhibit higher overall posttest scores on all seven variables

than faculty members who are not administered the experimental

treatment.

46

 

 

H22

H32

H43:

H415:

H4c:

H4d2

H4e2

H4f§

Interior design faculty members who are administered the pretest and the
experimental treatment will exhibit higher posttest scores on all seven
variables than faculty members who are not administered the pretest or
the experimental treatment.

Interior design faculty members who are not administered the pretest but
are administered the experimental treatment will exhibit higher posttest
scores on all seven variables than faculty members who are not
administered the pretest or the experimental treatment.

Relative advantage will be a significant predictor of an interior design
faculty member’s intention to adopt distance education.

Compatability will be a significant predictor of an interior design faculty
member’s intention to adopt distance education.

Trialability will be a significant predictor of an interior design faculty
member’s intention to adopt distance education.

Complexity will be a significant predictor of an interior design faculty
member’s intention to adopt distance education.

Observability will be a significant predictor of an interior design faculty
member’s intention to adopt distance education.

Gatekeeper will be a significant predictor of an interior design faculty

member’s intention to adopt distance education.

Two research questions are created to determine whether interior design

educators” attitudes of the study variables are consistent with the results from

47

past diffusion research. The first research question states that regardless of
exposure to the experimental treatment, relative advantage, compatability,
trialability, and Observability will have a positive relationship with the intention to
adopt distance education. The second research question states that regardless

of exposure to the experimental treatment, complexity and gatekeeper will have a

negative relationship with the intention to adopt distance education.

48

 

 

Participation for this study was solicited from the 514 members of l DEC
teaching in the US. One-hundred fourteen faculty members self-selected to
participate in this study for a response rate of 22.2%. At various stages of the

study, 47 faculty members discontinued participation. Sixty-seven participants

CHAPTER FIVE

Results

Sample and Procedure

returned usable surveys for a final response rate of 13.0%.

Surveys were logged as they were returned between September 8, 2001

and February 1, 2002 (see Table 5). Each returned survey was examined for

accuracy and completeness. Respondents with missing data were excluded

from analyses involving those missing data.

 

Table 5: Participants by Experimental Group

 

 

 

 

 

 

 

 

Group Original N Completed Study

Group 1 (01, X, 0;) 29 10

Group 2 (01, Oz) 28 14

Group 3 ( X, 02) 29 19

Group 4 ( Oz) 28 24

Total 114 67 J

 

 

 

 

 

Sample Demographics

Demographic data requested of participants included age, membership in

professional design organizations, years of teaching experience, gender,

ethnicity, and type of institution where they taught (see Table 6). The majority of

participants were between 51 and 60 years of age (37.3%), female (68.2%),

Caucasian (93.9%), hold a master’s degree (55.2%), and teach in a four-year

49

institution (76.1%). The average participant has over 13 years of combined part-
time (2.7 years) and full-time (10.6 years) teaching experience and is a member
of one or more professional design organizations. The 24 participants who
completed the pretest but failed to complete the study have a similar

demographic profile. Two participants in group one and seven participants in

group two completed no part of the study.

50

 

Table 6: Participant Dermgraphic Data

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Demographic Frequency Percentage
Type of Institution
2-year 12 17.9
4-year 51 76.1
Neither 3 4.5
Missing data 1
Highest Degree Acquired
Bachelor’s 10 14.9
Master’s 37 55.2
Doctoral 16 23.9
Other 3 4.5
Ag
Under 40 1 3 19.4
41-50 22 32.8
51 -60 25 37.3
61 or Older 5 9.0
Gender
Male 19 28.8
Female 45 68.2
Missing data 1
Ethnicity
Caucasian 62 93.9
Hispanic 2 3.0
Asian American 1 1 .5
Other 1 1 .5
Missing data 1
Professional Organization Membership
IDEC 67 100
NA 6 9.0
ASID 26 38.8
IIDA 24 36.4
Other 15 22.4

 

 

 

 

51

 

 

Instrument Reliatllity

Reliability tests were performed on instrument constructs to represent as
much measurement accuracy as possible. Cronbach alpha was used as a
statistical method for determining internal consistency and item-by-item reliability
on posttest data (n=67). The reliability coefficient for each variable is presented
in Appendix A.

Data Analysis and Hypothesis Testing

lnferential statistics were used to analyze the data. An alpha level (level
of significance) of .05 was used throughout data analyses. Statements phrased
in the negative were recoded for analysis. The data for each subscale were first I

analyzed using descriptive procedures. With the exception of gatekeeper, that
had a mean of 2.65 using posttest data, the overall means for all other variables
ranged from 3.49 to 4.33 (see Appendix D). With a neutral point of four in the
seven-point Likert scale, responses to these variables had no strong direction.
Interior design faculty members neither strongly agreed nor strongly disagreed
with the various aspects of distance education.

The first stage in the analysis of the SFGD is to examine pretest
sensitization. Simply taking the pretest may change a person’s attitude
(Solomon, 1949). Therefore, it is desirable to detect and control
premeasurement effects that could threaten the validity of the experiment (Haight
et al., 1998). The existence of pretest sensitization can be determined by
conducting a 2 x 2 between-groups analysis of variance (ANOVA) of all posttest

results. Shavelson (1996) notes that the use of the ANOVA will determine

52

“whether any combination of the treatment groups is significantly different from
any other combination” (p. 378). The two independent variables are the
control/experiment variable (i.e. treatment occasion) and the pretest/posttest
variable (i.e. test occasion). It is acknowledged that using individual ANOVAs for
each variable increases the likelihood of Type II error. Results of this initial
ANOVA on posttest scores produced F-scores that were low (relative advantage
0.291; compatability 1.186; trialability 0.251; complexity 0.135; Observability
2.063; gatekeeper 1.383; intention to adopt 0.315). Probabilities were
consistently greater than .05 for each of the seven variables. There was no
significance at this stage. Therefore, a premeasurement effect does not exist
and the analysis can continue.

The second stage of SFGD analysis proposed by Walton Braver and
Braver (1988) is the examination of the main effect of the intervention in the
previous ANOVA to determine whether there is a treatment effect (H1). See
Table 7 for treatment effect results. Relative advantage (p = .026) was
significantly higher after treatment than prior to treatment. Interior design
educators could see the benefit using distance education to improve the quality
of instruction, enabling them to teach students more effectively. No other
variables reached a satisfactory level of significance. Therefore, the hypothesis
that subjects administered the experimental treatment would exhibit higher

overall posttest scores on all seven variables was not supported.

53

 

Table 7: Treatment Effect Results Using Posttest Data

 

 

 

 

 

 

 

 

 

Pretest No Pretest MS F Sig
Relative Advantage 10.506 5.174 .026”
Treatment 4.4000 3.7193
No Treatment 3.1429 3.3056
Compatability 4.408 1 .828 .181
Treatment 4.3667 4.3667
No Treatment 3.3333 3.3194
Trialability .039 .018 .894
Treatment 3.6000 3.8947
No Treatment 3.6429 3.7500
Complexity 1 .568 1 .439 .235
Treatment 3.5250 3.9342
No Treatment 4.2262 3.8785
Observability .182 .186 .668
Treatment 3.9286 4.5564
No Treatment 4.0510 4.2143
Gatekeeper .093 .049 .826
Treatment 3.7250 4.7588
No Treatment 4.3393 4.3021
Intention to Adopt 4.239 2.534 .116
Treatment 5.000 4.3158
No Treatment 4.0357 4.2188

 

 

 

 

 

 

ABBREVIATIONS: MS, Mean Square, F, Fisher’s F ratio; Sig, Significance

NOTE: *p < .05

If the treatment effect test shows no significance, the analysis continues to

the third stage of SFGD analysis (H2). At this stage, the researcher has the

choice of three tests to perform on the premeasured groups: a two group

analysis of covariance (ANCOVA) on the posttest scores, covarying the pretest

scores; a gain score analysis in the form of a t-test between pre- and post-test

scores; or a repeated measures 2 x 2 ANOVA with treatment and time as the two

factors (Michel & Haight, 1996). The gain score analysis was chosen in an

attempt to determine pre-post score difference for group one (pretest, treatment,

posttest) and group two (pretest, no treatment, posttest). The intention to adopt

variable achieved significance (p < .05). No other variables reached a

 

satisfactory level of significance. Therefore, the hypothesis that subjects
administered the pretest and the experimental treatment would exhibit higher
posttest scores on all seven variables was not supported.

Since the previous three stages of analysis yielded no significant results,
the testing continues to the next stage (H3). In the fourth stage of analysis, a t-
test was performed on group three (treatment and posttest) and group four
(posttest only). Similar to the analysis in stage three, this test is not very
powerful because it omits half of the available data (i.e. groups 1 and 2). No
variables reached significance at this stage of analysis. Therefore, the
hypothesis that subjects not administered the pretest but administered the
treatment would exhibit higher posttest scores on all seven variables was not
supponed.

A multiple regression analysis was used to compare the six independent
variables (relative advantage, compatability, trialability, complexity, Observability,
and gatekeeper) against the dependent variable (the intention to adopt). Multiple
regression analysis on posttest data had an adjusted R2 value of .662 (see Table
8). Significance was achieved for compatability (p < .000) and trialability (p
<.001). Interior design educators would pursue distance education endeavors if
distance education fit their current teaching style and they had the opportunity to
try and experiment with it. No other variables achieved a satisfactory level of
significance. Therefore, hypothesis 4b that compatability would be a significant
predictor of intention to adopt was supported. Hypothesis 40 that trialability

would be a significant predictor of intention to adopt was also supported.

55

Hypotheses 4a, 4d, 4e, and 4f that relative advantage, complexity, Observability,

and gatekeeper would be significant predictors of intention to adopt were not

 

 

 

 

 

 

 

 

 

supponed.

Table 8: Multiple Regression on Intention to Adopt Using Posttest Data
Variable Beta T score Significance
Relative Advantage .096 .770 .443
Compatability .612 10.906 .000*
Trialability .201 3.416 .001”
Complexity -.097 -1 .065 .290
Observability .035 .421 .675
Gatekeeper -.016 -.240 .81 1

 

 

 

 

NOTE: * p < .001

Rese_arch Mon Analysis

There were two major research questions in this study. Both questions
were created to determine whether the opinions of interior design faculty toward
distance education were consistent with the findings of other diffusion of
innovations research. Findings from the diffusion of innovations theory are
based primarily on agricultural research (Rogers, 1995).

Looking at the Beta scores from Table 7, it is apparent that results from
this study are in agreement with past diffusion research results. Relative
advantage, compatability, trialability, and Observability all have positive Beta
scores. Complexity and gatekeeper both have negative Beta scores. Therefore, '
the two research questions that interior design educators’ attitudes of the study

variables would be consistent with past diffusion research were supported.

56

 

CHAPTER SIX

Discussion of Results

The purpose of this chapter is to present a restatement of the problem and
an interpretation of the research findings. The conclusions regarding the
research questions and hypotheses are summarily discussed. Participant
comments relative to each variable are included where appropriate.

The purpose of this study is to assess the attitudes of individual interior
design faculty members toward the development and instruction of distance
education courses. It uses the attributes of an innovation as the conceptual
framework for data collection and analysis and an experimental treatment to
present the process of teaching interior design with distance education
methodologies. This study investigates whether the attitudes of interior design
educators change as a result of behavioral modeling (how interior design can be
taught as a distance course). The study also looks at the consistency of interior
design educator’s attitudes toward an innovation with the theoretical findings of
previous diffusion of innovations theory applications. This study is conducted
with interior design educators who self-selected to participate. A Solomon four-

group design and an experimental treatment comprise the methodology.

Summam of Results from Experimental Design

With the lack of research on educational innovations (Rogers &

Shoemaker, 1971) and no evidence of research that directly addresses distance

57

education and faculty who teach in an area of the arts (such as interior design), it
was imperative to select a strong and methodologically appropriate blueprint for
data collection and analysis. The Solomon four—group design was selected
because it has the precision of pretesting, as well as the potential for identifying
an interaction between the pretest and the treatment. A post-test only design
would be free of pretest sensitization but the interpretation of results would be
limited. The SFGD gives explicit consideration to issues of reliability, validity,
and generalizability (Gay, 1996).

The first hypothesis states that interior design faculty members
administered the experimental treatment will exhibit higher overall posttest
scores on all seven variables than subjects not administered the experimental
treatment. The hypothesis is not supported by the data. The only variable to
achieve significance for a treatment effect is relative advantage (p<.05). Faculty
members who watched the presentation demonstrated stronger agreement that
distance education would improve teaching quality and effectiveness and provide
them more control over the teaching experience than faculty members who did
not watch the presentation.

The greater the perceived advantages of distance education, the quicker it
will be adopted (Rogers, 1995). Relative advantage has been found to be the
most important characteristic leading to adoption (Axin, 1988; Ploufe et al., 2001)
and the findings of this study support that claim. Overall, this study indicates
interior design educators see a stronger relative advantage of distance education

after watching a demonstration of how a design studio course could be taught

58

using distance education methodologies. The treatment addresses various
advantages of teaching at a distance, such as the reduction of faculty workload
by not having to repeat information to individual students, the use of available
technology tools to speed the feedback process, and the continuance of quality
education while serving an increased number of students. It should be noted,
however, that while attained scores do not reflect support for the first hypothesis,
educators watching the presentation (groups one and three) did score higher on
the posttest measures for relative advantage, compatability, trialability, and
intention to adopt than educators not watching the presentation (groups two and
four). See Tables 10 to 16 in Appendix E for the listing of mean scores for each
variable by group.

The second hypothesis states that interior design faculty members
administered the pretest and the experimental treatment would score higher on
all seven variables than faculty members not administered the pretest or the
experimental treatment. The hypothesis is not supported. However, one
variable, the intention to adopt, is significant (p=.04). Interior design educators
who were administered the pretest and viewed the presentation on CD-ROM
show an increase in their intention to adopt distance education as compared to
faculty members who did not view the presentation.

As stated previously, the intention to adopt variable is included to get a
sense of the faculty member’s urgency to become involved in distance education.
As behavioral intention is the direct determinant of an individual’s behavior, the

significance of this variable suggests interior design faculty members may pursue

59

distance education endeavors in the near future. Two measurement items have
high mean scores, indicating faculty’s recognition of the need for distance
education (M=5.24) and their personal interest in using distance education
(M=5. 1 9).

The third hypothesis states that interior design faculty members who were
not administered the pretest and were administered the experimental treatment
would score higher on all seven variables than faculty members administered
neither the pretest nor the experimental treatment. The hypothesis is not
supported. Participants in group three who watched the presentation on CD-
ROM stated higher mean scores for all variables (except complexity) than did
participants in group four who did not watch the presentation. However, the
difference between these mean scores was not large enough to be significant.
It should be noted that the second and third hypotheses are largely dependent
upon relative support of the data for the first hypothesis. Therefore, these
hypotheses lack a certain degree of interpretive integrity on their own merit.

Hypotheses 4a — 4e state that the six independent variables (relative
advantage, compatability, trialability, complexity, Observability, and gatekeeper)
would be significant predictors of the dependent variable, intention to adopt
distance education. Hypotheses 4b (compatability) and 4c (trialability) were
supported (p < .001). No other hypotheses were supported. These results
indicate that an interior design educator who believes distance education

methods could be applied to the education of interior design and has the

60

opportunity to test this instructional model is very likely to adopt the practices of

distance education.

Summary of Resglts from Research Questions

The intention to adopt variable is included in this study to assess the
participant’s sense of urgency to formally adopt distance education. This
variable bridges the gap between attitude and behavior so important in
understanding the diffusion of innovations. From the multiple regression results
between the intention to adopt and the remaining study variables (see Table 7), it
isclear that interior design educators are in agreement with all aspects of an
innovation’s attributes, as described by previous diffusion of innovations research
results. It should be noted that the Beta scores for relative advantage,
complexity, Observability, and gatekeeper are all close to zero, indicating a weak
relationship. Discussion of individual variables will provide insight into faculty

attitudes toward distance education.

Relative Advantage

The advantages of using distance education should theoretically decrease
a faculty member’s discomfort with the innovation. Participants in this study
indicated a positive relationship between relative advantage and their intention to
adopt distance education (8 = .036). They believe the use of distance education
will impact the quality and effectiveness of their teaching. One participant

provides the comment, “I am currently doing a web-enhanced course and have

61

found it to be a positive experience - with challenges. I’m looking fonivard to

doing a totally web course.”

Compatabilig

Interior design educators perceive distance education as fitting their
teaching style. Participants in this study indicate a positive relationship between
compatability and their intention to adopt distance education (8 = .612).
Compatability is the consistency between existing values, past experiences, and
needs of the potential adopter. The diffusion of innovations states that
compatability should be positively correlated to an individual’s intention to adopt.

Based on the high number of comments received in this study, interior
design educators are concerned about the way distance education could be used
to teach interior design. Gandolfo (1998) states that faculty who become
involved in distance education may exhibit expressions of grief due to the loss of
what is familiar, such as traditional teaching methods. One participant expresses
his willingness to explore distance education for courses such as the history of
architecture, design, and furniture. But he does not “ see it replacing the majority
of ID. courses and art courses. Interior design is about people and their
places/spaces; it is a creative and functional problem solving [process] at the
same time; students and faculty need to ‘feed’ off each other.” Another interior
design educator does not believe studio courses are suitable for distance

education delivery because the “person-to-person creativity enhancement would

62

 

be missing and the quality of the graphics are not adequate for an appropriate

studio experience.”

Trialabilfly

Participants in this study indicate a positive relationship between trialability
and their intention to adopt distance education (8 = .201). Trialability is the
degree to which an individual may experiment with the innovation on a limited
basis. If interior design educators were trained in distance education
methodologies and allowed to test them on a limited basis, distance education
may be adopted more quickly. By providing the opportunity to explore new
technological applications, investigate alternative teaching methods, and view or
participate in a sample distance course, faculty could develop insights into
designing their own courses. The experimental treatment utilized in this study
did not provide the opportunity for participants to try teaching with distance
education methodologies. One participant says he is “in the process of trying it

now.” Another interior design educator comments, “I’m willing to try.”

Complexiy

Participants in this study indicate a negative relationship between
complexity and their intention to adopt distance education (8 = -.097).
Complexity is the degree to which an innovation is perceived as difficult to use or

understand. Rogers (1983) states that ideas that are difficult to understand are

63

adopted slowly. According to the diffusion of innovations, the attribute of
complexity should be negatively correlated with adoption intention.

The process of distance education often involves technology that may be
unclear or difficult to use. One participant in the current study comments, “My
major concern is getting and understanding and dealing with the glitches of
technology.” Research at Iowa State University has shown that technology is
one of the determinants for faculty willingness to continue their initial distance
education endeavors. The use of the computer enhanced the distance
experience for the NEA faculty participating in distance education (Abacus,
2000). This suggests faculty who are adequately trained in technology would be I

most satisfied teaching a web-based distance education course.

Observability

Observability is defined as the degree to which the results of the
innovation itself are not only visible and communicable to others, but the idea of
the innovation is also visible (Rogers, 1995). Participants in this study indicate a
positive relationship between Observability and their intention to adopt distance
education (8 = .035). One participant writes, “I do see a very strong need for it”
while another comments that she is interested but needs “to see more positive
examples.”

The experimental treatment created and administered in this study was an
attempt at increasing the visibility of distance education in interior design.

Faculty members had the opportunity to see the usefulness and application of

distance education in interior design, but not necessarily its consequences or

impact.
Gatekeemr

Literature explains the dual role of the gatekeeper as both the advocate
for the faculty body and the judge who administers limited resources. The
gatekeeper, which in higher education can be a program coordinator or dean, is
perceived negatively if he retains resources or prohibits the flow of information,
creating a bottleneck in the department’s or college’s communication network
(Rosner, 2001). Participants in this study indicate a negative relationship
between the gatekeeper and their intention to adopt distance education (8 = -
.016)

Over half of both traditional faculty members (52%) and distance
education faculty members (51%) participating in the NEA survey believe
administrators to be the most forceful proponents of distance education (Abacus,
2000). Many comments arose in this study related to the role of program
coordinators and cleans in supporting faculty involvement in distance education.
One participant states, “I would be willing to teach studio via distance education.
However, I have no support from my department, colleagues, and chair. I really
would be willing to get involved in distance education, but I have no support to

accomplish this from my environment.”

65

CHAPTER SEVEN

Conclusion

The purpose of this chapter is to provide a conclusion to the topic of
interior design and distance education. The limitations of the study are
addressed. Insight is given for increasing the adoption rate of distance education
among interior design educators. Recommendations for future research are

provided, along with concluding statements.

Limitations of the Study

The findings in this research should be interpreted in light of several study
limitations. Issues of sample size and the design of the study limit the
generalizability of the study’s findings to other populations. Future replication of
this investigation should attempt to address these limitations in order to acquire

more generalizable results.

Sample Size
Even though the entire US. population of IDEC was solicited for

participation in this study, individuals made the decision to participate. A self-
selected sample risks bias. Because the demographic profile of the population of
IDEC members is unknown (R. Brown, personal communication, February 25,
2002), it is assumed that this sample is representative of the population. For the

experimental design, self-selected participants were randomly distributed into

66

one of the four groups, ensuring equal distribution of the accessible population
into each group. In addition, all interior design educators are not necessarily
members of IDEC and their opinions may differ from those presented in this
investigation.

The study began during the fall semester, which is a busy time for
educators in academe. A related limitation was the unexpected terrorist attacks
in New York, Pennsylvania, and Washington DC. on September 11, 2001.
These events delayed delivery of the initial request for participation. Some
participants received their letter four to six weeks after initial mailing. Therefore,
the initial participation stage of this study extended longer than expected. These '
conditions may have negatively affected faculty members’ willingness to
participate in general. Another unfortunate issue related to the terrorist attacks
was the anthrax threats that occurred from November 2001 to February 2002
(Parker, 2001). Individuals who agreed to participate early in the semester may
have forgotten their commitment and disposed of the follow-up mailings for fear
of Opening mail from an unfamiliar source.

The validity of the statistical conclusions and the statistical power of the
study would undoubtedly be stronger with a larger sample size. Use of the
SFGD requires a large sample size, especially since stages three and four utilize '
data from only two of the four groups. Johnson and Leone, (1964, as cited in
Haight et al, 1998) believe a group size of 45 in each group provides 90% power.

This study was unable to achieve this sample size per group.

67

W

Bandura (1977) expresses concern that mere exposure to modeled
activities may not result in observational learning. All aspects of modeled
behavior may not be observable. If observed, the behavior may not be retained
for any length of time. The 15-minute treatment used in this research combines
instruction with exploration, which is part of the behavioral modeling approach
(Simon & Werner, 1996). Harrison (1992) conducted an experimental design
concerning cultural assimilation by employees in a US. military agency and
found no significant relationship between the length of training and resultant
behavior. In Harrison’s (1992) research, the first group received behavioral
modeling training; the second group watched videos; and the third group
received no training. Participants reacted favorably to receiving any training,
regardless of the training approach and format utilized, as opposed to receiving
no training at all. Harrison ( 1992) concluded that watching videotapes alone was
all that was needed for some learning to occur. The groups receiving the
experimental treatment in this study had no opportunity for practice and feedback
on the material presented. Due to design limitations, it was not possible for the
researcher to travel across the US. to provide training sessions on the use of
distance education methodologies in interior design. The integration of a training
component in the experimental treatment may have increased the treatment

effect.

68

Study Design

Moore and Benbaset’s (1991) scale development process for the
attributes of an innovation resulted in the formation of both a long list and short
list of measurement items. This study utilized the short list of items in order that
the questionnaire not appear long and intimidating to participants. Using the long
list of measurement items should increase the reliability of each variable.
Therefore, it is recommended that further research be conducted with this longer
list of measurement items.

The exposure to identical testing conditions was not possible as
experimental and control subjects were not tested simultaneously. A time lapse
of almost four weeks occurred between administering the pretest to groups one
and two and administering the posttest to groups three and four. Therefore, it is
assumed all participants were exposed to similar environmental conditions but at
varying times. Aschen (1997) experienced a similar situation in her analysis of
patients in an assertive training therapy study. It is presumed that a tighter time
window would have maintained the faculty’s interest in and awareness of the

study, resulting in a higher number of completed posttests.

Recommendations for Rye Rflarcj
Distance education is truly an innovative approach to teaching interior
design. Its impact on higher education as a whole and faculty members in
particular remains unclear. Research is needed in various areas related to

faculty attitudes toward distance education. First, investigating variations in

69

training methods to affect faculty attitudes toward distance education would be
beneficial. Behavioral modeling involves three stages of applied Ieaming: (1)
presentation of the role behavior; (2) imitation of the modeled behavior; and (3)
positive social reinforcement (Nunns & Bluen, 1992). Research on persuasive
techniques that utilize one, two, or all three stages of behavioral modeling could
provide insight into effective attitude change strategies.

Second, longitudinal research should be done on the retention rate of
attitude change and an individual’s intention to adopt distance education. By
contacting the study participants with a positive attitude toward the intention to
adopt distance education at a later date, one could see whether they had
adopted it. Another related study could be conducted with interior design faculty
members who currently utilize distance education methodologies in their
teaching. Comparisons between their perceptions of an innovation’s attributes
and the perceptions of the current study participants would make a distinction
between pre-adoption and post-adoption beliefs, as evidenced in research by
Karahanna et al. (1999) and Plouffe et al. (2001).

Third, further investigation is needed on related factors that could impact a
faculty member’s pursuit of distance education (Karahanna et al., 1999;
Mathieson, 1991). Exploration of whether the initial adoption decision would be
voluntary or forced upon the individual is another area that was neglected in this
study and deserves further research. Assessing the attitudes of interior design

faculty toward distance education and including variables emphasized in the

70

theory of planned behavior (Ajzen, 1985), should be more fully explored with this
educational innovation.

Fourth, research is paramount in recognizing distance education in the
traditional faculty reward system. Faculty members in the fine arts have typically
been evaluated on the basis of tangible and creative activities (Lawn, 1998). As
design education moves into the digital world, new tools and materials need to be
developed for instruction at a distance. Yet faculty members are reluctant to
recognize the development of high quality, academic software in the same light
as contributions to refereed scholarly journals (Staman, 1990). When distance
education is aligned with service or outreach at research-based universities, it
carries even less prestige than teaching (Wolcott, 1997). If distance teaching
and traditional teaching are viewed as having equal status in the faculty reward
system, faculty in the arts will be more inclined to integrate distance education
methodologies.

Fifth, intellectual property and copyright ownership is becoming an
important issue in distance education (Smith, Eddy, Richards, & Dixon, 2000;
Abacus, 2000; Guernsey & Young, 1998). One participant in this study believes
“copyright/ownership issues with the University for course materials” are an issue
for developing interior design distance courses. The US. Copyright Office is
considering the impact of the Internet on copyright infringement because
copyright law, which was created for print media, may be discouraging innovation
in education (Fisher, 2000). For this reason, Smith et al. (2000) feel that federal

antitrust regulations, copyright laws, and intellectual property litigation will be

71

areas of concern as higher education moves toward online distance education.
University policy related to online course ownership may impact a faculty
member’s participation in distance education.

Finally, Moore and Benbaset (1991) strongly encourage using their
instrument to assess the opinions of various populations, with a diversity of
innovations. This study addressed interior design faculty members only. The
ability to generalize past this population to all arts and humanities content areas
is limited and may be misleading. Any lack of significance can be due to the
homogeneity of the population exposed to the innovation. In other settings,

different patterns of predictors are likely to emerge.

Summam

In conclusion, this study attempted to illuminate the attitudes of interior
design faculty on distance education. Though none of the hypotheses were
supported, the results provide insight as to which attributes of an innovation have
the most impact on the attitudes of interior design educators. The two research
questions addressed the unique population of interior design educators, who may
or may not react to an innovation as hypothesized in the diffusion of innovations.

Major findings included: (1) subjects who were administered the pretest
received higher posttest means on relative advantage, compatability, trialability,
complexity, and the intention to adopt regardless of whether they were in the
treatment group; (2) subjects who received the treatment intervention yielded

significantly higher posttest means on the variables relative advantage and the

72

intention to adopt than those not exposed to the treatment intervention; and (3)
compatability and trialability are significant predictors of the intention to adopt
distance education.

Whether using an asynchronous or synchronous delivery method.
distance education courses are increasing in number every year (Eggen, 2000;
Everhart, 2000) with no apparent end in sight. As new electronic technologies
become available, traditional education methods are converging with those
illustrated by distance education. Rather than having distance education merely
supplement on-campus instruction, it is suggested that a paradigm shift will occur
where the two instructional models become one. This will be triggered by
advancing technology, declining funds, globalization, the demography of the
students, and an increase in the individual’s responsibility to pay for education
(Moran & Myringer, 1999; lnnoVisions Canada, 1998; Otchet, 1998). Interior
design educators should be prepared to seek answers to their questions and

determine where they stand on the issue of distance education.

73

 

 

APPENDICES

Appendix A

Table 9: Construct Items and Reliabilities

NOTE: *phrase recoded in analysis

 

Relative Advantage (r = .82)
Using distance education would improve the quality of my interaction with
students.
Distance education would enable me to teach students more effectively.
Using distance education would give me greater control over my teaching
endeavors.

 

Compatability (r = .92)

Using distance education would fit with my style as an educator.
I think that using distance education would fit well with the way I educate
students.

Using distance education would be compatible with all the ways I like to teach.

 

Trialability (r = .70)
I’ve had a great deal of opportunity to try distance education.

Before deciding whether to use distance education for instruction, I would be
able to properly try it out.

I am able to experiment with distance education methodologies as necessary.

 

Complexity (r = .72)
Learning to teach at a distance would be easy for me. *
The process of distance education is clear and understandable to me.*
I would find it easy to get distance education to do what I want it to do.*
I would find distance education easy to use.*

 

Observability (r = .69)

Distance education is not very visible in my institution.*

I have seen what others are doing with distance education.

I have not seen many others using distance education in my department or
college.*

I have had plenty of opportunity to see distance education being used.

I believe I could communicate to others the consequences of using distance
educafion.

The impact of using distance education is apparent to me.

I would have no difficulty telling others about my experience with distance
educafion.

 

I

74

 

, J.

 

 

Table 9 (cont’d)

 

Gatekeeper (r = .80)

I am worried there may be a lack of encouragement for distance education by
my program coordinator.*

I worry that the administration’s commitment to distance education initiatives
will wane as time goes by.*

I am worried there may be a lack of support for distance education by my
deanf

I am concerned about the lack of release time/compensation awarded by my
pmam coordinator to adequately develop a distance education course.‘

 

 

Intention to Adopt (r = .95)
I would be interested in using distance education.
I will arrange to teach a distance education course as soon as possible.
I will recommend that my colleagues use distance education for instruction.
I don’t see much need to use distance education.*

 

75

 

 

Appendix B
Slides from Experimental Treatment

Figure 3: Distance Education Technologies & the Design Studio

 

Distance Educatlg Eech110|ogies
...& thelDestgn guidic’i} ...:

=1 knit: [Ln:_ ._.,_

      

Figure 4: Teaching in a Design Studio 1

 

Teaching In a Design Studio

- An introduction to the apprentice system

- The ability to overhear critic’s conversation with
others

- An opportunity for students to critique, network,
and socialize with peers

 

 

 

76

 

Figure 5: Teaching in a Design Studio 2

 

Teaching in a Design Studio

- Individual critiques move to faculty/student
collaboration

- The first project critiqued receives the most
in-depth and specific feedback

- The faculty repeats the same or similar
comments to each student

- Faculty may experience burn out or fatigue

 

 

 

Figure 6: The Traditional Design Studio

 

The Traditional Design Studio

. When more than one faculty involved, it can
become a critique of faculty

- With 20 students in each 3 hour studio session,
a student gets less than 9 minutes of attention
(less than 6 minutes if session is 2 hours)

- One or more students will wait 2 hours and 50
minutes for their personal critique

. Students do not see all projects until the end

 

 

 

77

Figure 7: Student Step 1

 

 

’3‘...” ...........o....... Student Ste 3

- eyeliclmg and dragging wrtmour mouse. you can M51. tum and spin a 3D moat An endless number
otylevmornts ls DOSSIbIe

. You can manipulate any new, Including plan, elevation, section, perspecttye and isometric wows

- 300nm displays on screen a Circle dmded into 4 quadrants This IS called an arcoal: ‘

- Bypicklng on the 4 quadrant paints orby picking ouslde the arcball. you can rotate the new around the ,
x ans, the Y axis or the XY plane

- You can View the entire drawing model or you can select particular oblects wrthln the model to View.

- By nght-cllclong on the screen while in 3Dorbrt, you can access any ofthe options listed below
mums

.................
, .............. ‘

Pan Shuts the new in real-time without distortion 3 Z
Zoom Shrrls the view in real-time wrth distortion 3 a
Omit Rotates the new around the arcoall Y X
More Sets and adusls the cllopngplanes plus other options ';
Praectlm Rotates the new around parallel or perspective planes
Shadno rmrhls Hides and shades the model during rotation g _______________________________ }
visual ads Controls compass, and and ucsrcon settings i
Resetylew Returns to the original View from the beginning ofthe command

Presawews Picks one of 10 orthogonal or Isometric views
NOTE Related 30 commands include 30cm). 30dlstance, 3Ddan, 305mm and 30:oom

Now new this usmg the 3D omit command - It should look something like lhls

1. The student is given a design project Explanation is provided in writing and
verbally during lecture.

 

 

Figure 8: Student Step 2

Duhmul-n-muvfi

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

    

 

   

2:? 7.1." .:.“.;r.::: '3: ° '1: “5.11:.“ 2.7.3:” ’ §tudent Steps
2
l .l
I
l
l
a... n ’ a _,
rt: Index: ‘57; whammmmwmfl’”’w ' ___._ " ‘ "w # .-__. ‘—-~"'J ' .
2. The student completes the weekly task and “captures the drawing or
image at the end of the task from the computer screen using the Print
Screen key.

 

 

 

78

 

Figure 9: Student Step 3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I-l

 

the image by cropping it to remove the menu bars of the software and

 

a JPEG image.

3. The student pastes the image onto a blank PowerPoint slide and modifies

resizing it to fit the screen. The student then exports the PowerPoint slide as

 

 

Figure 10: Student Step 4

    
    

1‘" lllli.’ llllili- Ilplilill \l’ tsi ilii
Flo at View Go Commutator HQ __

assesses

  

 

 

 

  

 

'l ‘f em Acmlmudoodmwmmmmumwmw

 

Upload a flle to the server.

being uploaded by clicking the appropriate radio button. then press the Start the

 

The file is
6 Binary (this includes files in a word processor format)
P Text

Select file to upload: I Browse...

sun lilo upload I

 

 

 

tools.

Use the Browse button to locate the file you want to upload, select what type of file IS

upload button, When the upload has finished you wrll see a message indicating 50.

?l W: Don- 21,372.-.bfl9._>&m.i /A
4. The student transfers the image to the course site using email or Internet

 

 

79

 

 

 

Figure 11: Student Step 5

FPITT new-h 80""'
61:: :e_ tug-g- :1qu a??? Soss:f'__‘9l.3 aCUIt pstes

auvmi --Q

 

 

l ..-__

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Palavifi 7'7 .r
1. The faculty member or Teaching Assistant downloads all student f Ies from

the course site. Each image is imported into one PowerPoint presentation.

 

 

 

 

Figure 12: Faculty Step 1

 

 

2 The faculty member prints all slides (6 per page) Faculty/guest critic
reviews all submissions identifies problems common to all students. and
creates a thoughtful critique of student work

80

 

Figure 13: FaculW Step 2

an. in 1:39;!!29‘3'0 1&2": lat-‘3:- Hg,
QEEEWEMWM

owl—cl

 

  

 

 

      
 

 

 

 

 

 

 

 

.1 W ”W ill“ on. 1.”. ,naue
u

u

u

o e a . was EIEC
mini-1] glut] mama—**" m

. 7 .. . "ii-nomad“ um "him to: ”zoos" oil

3. The faculty member creates an outline for the critique and records
comments with audio software.

 

Figure 14'. Faculty Step 3

 

5. The faculty member drChives the week‘s files for comparison with
Subsequent submissrons.

 

 

81

Figure 1 5: Student Step Download

I

 

 

 

 

 

 

The student downloads the appropriate files and liSlens to the critique to make
corrections to his preject

 

Figure 16'. Student Step Preview

   
     
   

Students are expected to preview the task for the coming week. All students
come to class to communlcate concerns. get personal attention, and ask
questions of the faculty and teaching assistants.

82

Figure 17: Student AsSiStance

Students have several options for getting assistance: email. Open lab timeS.
and Microsoft Netmeeting.

 

   
  
  
 

Figure 18'. Student Advantages 1

Design Studio: Current Modifications

 

Student Advantages:

. Each student can view all projects submitted

- Students can review the critique at any time
from any computer during the week

- All students receive the same information,

feedback, and direction
- Students can easily see where their project

“fits” in relation to others
- Students maintain their original work (i.e. not
lost. damaged, etc.)

 

83

Figure 19: Student Advantages 2

[/Design Studio: Current Modigcations

 

 

Student Advantages:

- Stude"ts do not question the faculty's objective
critique (i.e. no “favorites”)

- The amount of time necessary for feedback is
substantially decreased (both faculty time and

student time)
. The student does the assignment rather than

the faculty

 

 

 

 

Figure 20: Faculty Advantages

Design Studio: Current Modifications

 

Wes;

- FaCUItY can better manage feedback and
turn-around-time of critiques is shorter
. Faculty can easily determine the progress of

the class as a whole
. Feedback is more consistent

- Faculty Spends less time repeating information
- Faculty has more illustrative material
- Guest critics can more easily be included

. Faculty have a record of student progress and
ever)l Comment ever made in the course

 

 

 

 

 

 

Figure 21'. Disadvantages

Wesign Studio: Current Modigcations

 

 

W

. Faculty Will spend less personal time with each
student (Student's choice)

- Traditional techniques of drafting and rendering
may be sacrificed (scanning is possible)

- Development time will increase while
instruction time will decrease

. Faculty will need to learn instructional tools and
teach them to the students (if needed)

. Without limits, faculty can find themselves
working 24/7 answering email etc-

 

 

 

 

Figure 22: Design Studio Strategy

 

Design Studio: Strategy

Use distance education techniques ONLY in
courses where they may add to the learning
experience

Use technology as the primary mode of
delivering information that students would
want or need (24 hours/7 days a week)

 

Use class time as time with faculty and peers
for socializing, networking, and group
problem-solving

 

 

 

85

 

Figure 23.. Design Studio Summary

 

 

Design Studio: Summary

- The student gets more instruction in less time

. Students Ieam to communicate using current
technologies

- Some traditional techniques may be lost

 

 

 

86

PM
Letter of Participation and Reply Postcard

September 1,2001

Dear Educator:

Has your university begun discussing terms like “distance education” and “virtual
university”? Are you feeling Pressured to teach “at a distance”? Some even say

it may not be long before the Use of distance education methodologies is no
longer an option for interior deSIgn faculty.

 

Your perceptions regarding distance ed ucation are critical
to program planning for interior design education.

 

YOU are asked to participate a study to determine how interior design faculty
perceive distance education and how increased awareness of distance education
could influence faculty attitudes. Participation is voluntary. Subjects may choose
not to participate at any time and have the right to discontinue participation in ““5
study without penalty or loss to which the subject is othenivise entitled-

I need your participation to make this study happe‘“

You would be involved in either one or two parts of the study dependiw 0.“
' t E e ' ' ' -' roxtmaieiy

QVOUP aSSignmen - V tyone Wlll get a questionnaire that Will take app '

7-10 minutes to complete. You may also be asked to watch an instructional .
movie (on CD-ROM), which will take another 15-20 minutes to View. The move
will demonstrate how distance education methodologies can be applied to an
interior design course. The CD-ROM is yours to keep. Even if you are not ask
to watch the movie, I will mail it to you for your own personal use at the ed

conclusion of the study. If you agree to participate, the study will begin in
October.

If you participate, results will be kept confidential. Your privacy will be protect
to the maximum extent allowable by law. The number in the Upper right corneerd
each questionnaire will be used for follow-up purposes only. Only the research or

Will know your identity and reports of research findings will not associate nameser

With individual responses.

Enclosed is a self-addressed. Stamped postcard for you to indicate your

willingness to participate in this study. Your participation is necessagy to assess
the im act of distance education on interior desi n education. Regardless of

your willingness to participate. please drop this postcard in the mail by
September 20‘".

87

if you have any questions or concerns related to your pair/oi '

. pat/on,
contact Diane Bender at (517) XXX'XXXX- if YOU have any questiong/iziz‘ed to
your rights as a partrcrpant, please contact David E. Wright, MSU UCRIHS Chair.

at (517) XXX-XXXX.
Thank you for your help.
Diane M. Bender, Doctoral Candidate Linda Good, Professor

A

Your participation is important to the success of this study!

 

 

  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
  

Please check the item that indicates your willingness to
participate:

:i I have never developed or instructed a distance education
course and M9 to participate in this study.

a l have developed or instructed a distance education course
and am willing to participate in this study.

a l have never developed or instructed a distance education
course but am not Wilang to participate in this study.

a l have deve\0ped or instructed a distance education course
but W to participate in this study.

 

 

My email address is: _
My preferred communication method is:
0 Email
a US. Postal Service
a Facsimile
(If selected, please provide a fax number;

 

Regardless of your willingness to participate,
please drOp this postcard in the mail by September 20th!

88

 

ABM

Table 10; Variable Means and Standard Deviations Using Posttest Data

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Variable [ Mean J so
Relative Advantage 3,5522 1.4536
Compatability 1 3.4925 1.561 7
Trialability A 3.7463 1.4461
Complexity [A 4.231 3 1.0246
Observability 4.2345 0.9909
Gatekeeper I 2.6468 1 .3906
Intention to Adopt 4.3246 1.2990

 

 

 

 

 

89

Appendix E

Means and Standard Deviation Values of Individual Scales

 

Table 11: Mean Scores of Groups for Relative Advantage

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

N Pretest M Pretest SD Posttest M Posttest SD
1 10 4.0000 0.9813 4.4000 1.0159
2 14 2.9286 1.1560 3.1429 1.1301
3 19 ---- ---- 3.7193 1.7960
4 24 ----- ---- 3.3056 1 .3828
Table 12: Mean Scores of Groups for Compatability
N Pretest M Pretest SD Posttest M Posttest SD
1 10 3.9000 1.2771 4.3667 1.2712
8 14 2.9762 1.4290 3.3333 1.5359
3 19 ---- ---— 3.3684 1 .6737
4 24 ---- ---- 3.3194 1 .5650
Fable 13: Mean Scores of Groups for Trialability
r \ N \ Pretest M Pretest SD Posttest M Posttest SD
\T \ 10 \ 3.4667 1.4333 3.6000 1.3407
2 14 \ 3.2619 1.5088 3.6429 1.4991
3 19 i ---- —----- 3.8947 1.5318
4 24 ------ ---- 3.7500 1 .4687
Table 14: Mean Scores of Groups for Complexity
N Pretest M Pretest SD Posttest M Posttest SD
1 10 4.2233 1.2385 3.5250 1.1987
2 14 4.3860 1.2596 4.2262 0.8155
3 19 -—-- -—--- 3.9342 1.2579
4 24 ---- ----- 3.8785 0.8992

 

 

 

 

 

 

 

90

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 15: Mean sEJTes of Groups for Observability J
N Pretest M Pretest SD Posttest M I Posttest SD I
1 10 4.1571 1.0333 3.9286 [ 0.8116 1
2 14 4.0204 1.2338 4.0510 1.1546
3 19 ----- ----- 4.5564 1.0123
4 24 mm» ----- 4.2143 0.9258
Table 16: Mean Scores of Groups for Gatekeeper
N Pretest M Pretest SD Posttest M Posttest SD
1 10 3.7250 1 .4741 3.7250 1.5787
2 14 4.4107 0.9836 4.3393 1.2504
3 19 ---- ---- 4.7588 1.3330
L4 24 _.._..._ —--- 4.3021 1.4103
gable 17: Mean Scores of Groups for Intention to Adopt
[ N Pretest M Pretest SD Posttest M Posttest SD
1 10 4.7500 1.0737 5.0000 1,1 426
2 14 3.8214 1.2876 4.0357 1.1596
(3’ 19 ---- ----- 4.3158 1.3146
4 \24 \----- ---- 4.2188 1.3994

 

 

 

 

 

91

BIBLIOGRAPHY

Abacus Associates (2000, June). A survey of traditional and distance
learning higher education members. National Education Association. [On-line].
Available: http://www.nea.org/nr/nr000614.html

Abe, Y. (1988). Communications technology. In D. Sewart, & J.S. Daniel
(Eds), World conference of the international council for distance education:

________________—___________________——————

Develo in distance education (pp. 9-15). Vamamo, Sweden: Faiths Tryckeri.

Ajzen, l. (1985). From intentions to actions: A theory of planned behavior.
In J. Kyhl & J. Beckmann (Eds), Action control: From cpflition to behavior (pp.
11-39). NY: Spring Verlag.

American Association for Higher Education (2001). [On-line]. Available:
http://www.aahe.orgl

Anderson, M.D. (1997-98). Critical elements of an lntemet based

asynchronous distance education course. Journal of Educational Technology-
Systems, 2_6(4), 383-388.

Architecture: History of western (2000). In Encyclopedia Britannica
online. [On-line]. Available: http://search.eb.comlb0lltopic?et_ij119572@sctn=2

Aschen, SR. (1997 February). Assertion training therapy in psychiatric
milieus. Archives of Psychiatric Nursing, 1_1_(1). 46-51,

Axin, C.N. (1988 Summer). Export performance: Do managerial
perceptions make a difference? lntematjonal Marketing Review, 5(2). 61-71-

Baird, M.A. & Monson, MK. (1992, Fall). Distance education: Meeting
diverse learners’ needs in a changing world. In M. J. Albright & D. L. Graf (Eds),

Teaching in the information age: Theigle of educaitonal technolggy, {fl (pp, 65-
76). San Francisco: Jossey-Bass.

Baldwin, R.G. (1998, Winter). Technology’s impact on faculty life and

work. In K. H. Gillespie (Ed.), The impact of technology on faculg development, ‘
life and work, 26 (pp. 7-21). San Francisco: Jossey-Bass.

 

Bandura, A. (1977). Social Ieaming theom. Englewood Cliffs, NJ:
Prentice-Hall.

Bates. AW. (1995). Technology, open Ieaming and distance education.
London: Routledge.

92

Beaudoin, M. (1990). The instructor’s changing roIe in distance education.
The American Journal of Distance Education, 51(2), 21-29.

Bellman, BL. (1992, Fall). Computer communications and learning. In M.
J. Albright & D. L. Graf (Eds) Teaching in the information age: The role of
educaitonal technology. §1 (pp. 55-63). San Francisco: Jossey-Bass.

Bender, D.M.. Vredevoogd, J.D. & Witt, MA. (2002). Integrating
technolo & desi n education. Manuscript in preparation. Michigan State
University.

Bers, T. (1999, Fall). The impact of distance education on institutional
research. In L. Sanders (Ed), How technology is changing institutional
research. New Directions in Institutional Research, 133 (pp. 61-78). San
Francisco: Jossey-Bass.

Betts, KS. (1998. Fall). An institutional overview: Factors influencing
faculty participation in distance education in postsecondary education in the
United States: An institutional study. Online Journal of Distance Learning
Administration. 1(3). [On-line]. Available:
http://www.westga .ed ul~d istance/betts1 3. htrnl

Bodenheimer, T., Lo, B., & Casalino, L. (1999 June 2). Primary care
physicians should be coordinators, not gatekeepers. Journal of the American
Medical Association. [On-line]. Available: http:l/proquest.umi.coml

Boime, A. (1971). The academ and French aintin in the nineteenth
century New York: Phaidon.

Boime, A. (1982). American culture and the revival of the French
academic tradition. Arts Magazine, 33, 95-101.

Bollentin, W. R. (1998, January/February). Can information technology
improve education? Measuring voices, attitudes and perceptions. Educom
Review, 33(1). [On-line]. Available:
http:llwww.educause.ed u/pub/erlreview/reviewArticlesl331 50.html

Brown. LA. (1981). Innova_tipn diffusion: A new perspective. New York:
Methuen.

Buchanan, D. & Badham, R. (1999). Politics and organizational change:
The lived experience. Human Relations, 32(5), 609-629.

Camevale, D. & Young, JR. (1999, December 17). Who owns on-line

courses? Colleges and professors start to sort it out. The Chronicle of Higher
Education. 59(17). A45-A46.

93

Catchpole, M.J. (1992). Classroom, open, and distance teaching: A
faculty view. The American Journal of Distance Education, 3(3), 3444.

Charp. S. (2000 May). Internet usage in education. THE. Journal,
21(10). 12,14.

Clark, T. (1993). Attitudes of higher education faculty toward distance
education: A national survey. The American Journal of Distance Education.

,——-———-——
1(2), 19-33.

Dalton, D.W. (1989, November). Computers in the schools: A
diffusion/adoption perspective. Educational Technolmy, 23(11), 20-27.

Decker, P.J. (1986). Social learning theory and leadership. Journal of
Management Development. 3(3), 46-58.

Dede, C. (1 989, July). The evolution of distance learning: Technolpgy-
mediated interactive learning. Washington DC: Office of Technology
Assessment.

Denning, P.J. (1999, May/June). Teaching as a social process. Educom
Review. 35(3). [On-line]. Available:
httpzllwwweducauseedu/irllibrarylhtmI/erm9932.html

Dias, LB. (1999, September). lntergrating technology: Some things you
should know. Learning and Leadingflith Technolpgy, International Society for

Technology in Education, 21(3). [On-line]. Available:
http:/lwww.iste.org/L&Uarchivelvol27lno3lfeatures/dias/index.html

Dillon, CL. (1989). Faculty rewards and instructional telecommunications:
A view from the telecourse faculty. The American Journal of Distance Education,
3(2), 35-43.

 

Dillon, C.L. & Walsh, SM. (1992). Faculty: The neglected resource in
distance education. The American Jopmal of Distance Education, 3(3), 5-21.

Divelbiss, R.|. (1981). The @ekeeper function of agricultural new editors
and reporters at Midwestern land grant universities. Unpublished master’s
thesis. Michigan State University, East Lansing, Michigan.

Dukes. R.L, Ullman, J.B., & Stein, J.A. (1995 August). An evaluation of

D.A.R.E._(Drug Abuse Resistance Education). using a Solomon four—group
design wrth latent variables. Evaluation Review, 1_9_(4), 409-435.

94

Duning, 88., Van Kekerix, M.J. & Zaborowski, L.M. (1993). Reaching
learners through telecommunications. San Francisco: Jossey-Bass.

Eckhardt, K.W. 8 Errnann, MD. (1977). §g=ial research methgg
Perspective, theopi, and analysis. New York: Random House.

Eggen, D. (2000, April 7). Logging on to college. Washington Post, pp.
B1. [On-line]. Available: httpzllwww.washingtonpost.com

Erickson, F. & Shultz, J. (1982). The counselor as gatekeefir: Social
intemrction in interviews. New York: Academic Press.

Everhart, R.L. (2000, May). Enterprise systems and distance Ieaming:
Creating services for connected learners. Syllabus, 13(9), 48-51.

Farrington, G.C. ( 1999, July/August). The new technologies and the
future of residential undergraduate education. Educom priew, 341(4). [On-line].
Available: http://www.educause.edufrr/librarylhtmllerm9949.htrnl

 

F IDER accreditation guidelines (2000, August). (Available from the

Foundation for Interior Design Education Research, 60 Monroe Center NW, Suite
1318, Grand Rapids, MI 49503).

FIDER website (2000). [On-line]. Available: http://www.fider.org/

Fishbein, M. & Ajzen, l. (1975). Belief, Attitude, Intention, and Behavior:
An Introduction to Theom and Research. Reading, MA: Addison-Wesley

Fisher, R.V. (2000 October). Overcoming obstacles to multimedia for the
web. Syllabus, 13(3). 58-59.

Gandolfo, A. (1998. Winter). Brave new world? The challenge of
technology to time-honored pedagogies and traditional structures. In K. H.

Gillespie (Ed), The impact of technolpgyon faculg development, life, and work,
E (23-38). San Francisco: Jossey-Bass.

 

Gaud, W.S. (1999, December). Assessing the impact of web courses.
Syllabus, 13(4), 49-50.

Gay, LR. (1996). Educational research: Competencies for analysis and
application (5th ed.) New York: Prentice Hall.

Gillespie, F. (1998, Winter). Instructional design for the new technologies.

In K. H. Gillespie (Ed). The impact of technolpgy on faculg development, life,
Mk. 2.6. (39-52). San Francisco: Jossey—Bass.

95

Gist, M., Rosen, B., & Schwoerer, C. (1988). The influence of training
method and trainee age on the acquisition of computer skills. Personnel
mm. 11(2). 255-265. _—

Goldstein, LL. (1 989). Training and development in organizations. San
Francisco: Jossey-Bass.

Gueldenzoph, L.E., Guidera, S., Whipple, D., Mertler, C. & Dutton, L.
(1999). Faculty use of instructional technology in the university classroom.
Journ_a1 of Educationfial Technolpgy Systems, _2_3(2), 121-135.

Guernsey, L. & Young, JR. (1998, June 5). Who owns on-line courses?
The Chronicle of Higher Education, 451(39), A21-A23.

Gunawardena, C.N. (1992). Changing faculty roles for audiographics and
online teaching. American Journal of Distance Education, 3 (3), 58-71.

Haight, B.K., Michel, Y.M., & Hendrix, S. (1998). Life review: Preventing
despair in newly relocated nursing home residents short- and long-term effects.

International Journal on Aging and Human Development, 4_7(2), 119-142.

Harrison, J.K. (1992). Individual and combined effects of behavior
modeling and the cultural assimilator in cross-cultural management training.
Journal of Applied Psycholpgy, 71(6), 952-962.

lnnoVisions Canada and The Canadian Telework Association (1 993)-
Distance Education. [On-line]. Available: httpzllwww.ivc.ca/part10.htm|

IDEC website (2001). [On-line]. Available: http://www.idec.orgl
Johnson, C.M. & Darrow, A. (1997). The effect of positive models of

inclusion on band students’ attitudinal statement regarding the integration of
students with disabilities. JRME, 413(2), 173-184.

 

Jonasson, J. (1997, June). The internet - The educational medium of
today. Educational Mega International, _3_4_(2),88-93.

Karahanna. E., Straub, D.W., & Chervany, ML. (1999 June). Information
technology ad0ption across time: A cross-sectional comparison of pre-adoption
and post-adoption beliefs. MIS Quarterly, _2_3(2), 183-207.

Laaser. W. (1988). Some obstacles to implement new information
technologies in distance education. In D. Sewart & J.S. Daniel (Eds). World
Conference of the lntemational Council for Distance Education: Developing
distance education (pp. 288-290). Vamamo, Sweden: Falths Tryckeri.

 

96

Landstrom. M. (1995, Summer). The perceptions and needs of faculty in
distance education in a conventional university. Canadian Journal of Educational

Communication, 25(2) . 149-157.
Lawn, R.J. (1998, December). Integrating the arts and technology.

Educational Technology, m6). 56-59.
Layzell, OT (1996, Spring). Faculty workload and productivity:

Recurrent issues with new imperatives. The Review of Higher Education. 19(3).

267-281 .

Lowe, P. (1995). The management of technolpgy: Perception and

opportunities. London: Chapman and Hall.

Mani, G. (1988). Attitudes of external faculty towards distance education.
In D. Sewart & J.S. Daniel (Eds), World Conference of the lntemational Council

for Distance Education: Developing distance education (pp. 297-300). Vamamo,

Sweden: Falths Tryckeri.
Mason, R. (1999). The impact of telecommunications. In K. Harry (Ed),

Higher education through open and distance learning (pp. 32-47). London:

Routledge.
Messy, W.F. & Zemsky, R. (1995). Using information technology to
enhance academic productivity. Educause, Educom’s National Learning

Infrastructure Initiative (NLll). [On-line]. Available:
http:llwww.educause.edulnliilkeydocslmassy.html

Mathieson, K. (1991). Predicting user intentions: Comparing the
technology acceptance model with the theory of planned behavior. Information

Systems Research, 2(3), 173-191.

Matthews, D. (1999. September). The origins of distance education and
its use in the United States, THE. Journal, 2_7_(2), 54-67.

 

McCollum, K. (1998, June 26). A computer requirement for students
changes professors’ duties as well. The Chronicle of Higher Education, fi(42),

A22-A23.
Michel. Y. & Haight, B. (1996 Nov/Dec). Using the Solomon four design.

Nursing Research, 13(6), 367-369.
Millard, RM. 8. Bass, J. (1991). The technology threat. Today’s Mflhs

and Tomorrow’s Realities, 209-237.

97

Moore, GO 8: Benbasat, l. (1991). Development of an instrument to
measure the perceptions of adopting an information technology innovation.
lnforrnation S stems Research, _2_(3), 192-222.

Moore, MG. (1989). Effects of distance learning A summagy of the
literature. Washington DC: Office of Technology Assessment.

Moore, MG. (2000) (Ed) Technology-driven change: Where does it leave
the faculty? The American Journal of Distance Education, 11(1), 1-6.

Moran, L. & Myringer, B. (1999). Flexible Ieaming and university change.

In K. Harry (Ed.), Hi her education throu h 0 en and distance Iearnin (pp. 57-
71). London: Routledge.

Murphy, T.H. & Terry, H.R. Jr. (1 998). Faculty needs associated with
agricultural distance education. Journal of Agricultural Education, 33(1), 17-26.

Myers, MT. (2000, March 21). CyberU: What’s missing. Washington _
Post. pp. A25. [On-line]. Available: http:llwww.washingtonpost.comlcgi-
b. . . ni/print&articleid=A49560-2000Mar21

National Center for Education Statistics. (1999). Distance education at

postsecondagy education institutions: 19974993. [On-line]. Available:
httpzllncesedgov

Navarro, P. & Shoemaker, J. (2000). Performance and perceptions of

distance learners in cyberspace. The American Journal of Distance Education.
14(2). 15-31.

Nunns, C.G. & Bluen, SD. (1992 September). The impact of behavior
modeling training on self-reports of white supervisors in two South African mines.
The Journal of Applied Behavioral Science, EB), 433.444.

Olcott, 0., Jr. (1991,W1nterlSpring). Bridging the gap: Distance Ieaming
and academic policy. Continuing Higher Education Review, §_5_( 1 &2), 49-60.

Olcott, 0., Jr. & Wright, S.J. (1995). An institutional support framework for ‘
increasing faculty participation in postsecondary distance education. m
American Journal of Distance Education, 3(3), 5-17.

Otchet, A. (1998, October). www.$$$@online.education. (Virtual
classrooms). UNESCO Courier. [On-line]. Available:

http:/lweb51nfotrac.galegroup.com/itw. . . 588/675!

98

- d
Parker, DR. 1 997 . lncreasirl f la in teaching an
( ) Q aculty use of techno QY 5(2/3), 1 5-

teacher education. Journal of Technology and Teacher Education. _.

1 15.
"Vestig atorS

Parker, L. (2001 December 18). Anthrax probably domestic: '

focus on US. laboratories. USA Today. [On-line]. Availablei
htth/pqasbpqarcbiver.com/USAToday/
at behavior

F’arry, S.B. & Reich, LR. (1984 March). An uneasyzlook
6

modeling. Trainin and Develo ment Journal, 33(3), 57— -
(1998, September)-

. Principles and guidelines related to faculty workload . -
(Ayallable from the College of Human Ecology, 7 Human ECOlOQV Building.
Michigan State University, East Lansing, MI 48824).

roll .
a ) ‘

Plouffe. C.R., Vandenbosch, M. & Hulland, J. (2001 M
lnterrnediating technologies and multi-group adoption : A comlDal‘SC.m 0 ant
consumer and merchant adoption intentions toward a new electronic Pa

1§(2)’ 65-81 .

system. The Journal of Product Innovation Management,

. l
Rapoport. A. (1984 October). Architectural education, W

Record, 100-105.
. . . . g tee/93L-
Reltemeler, P.J. (1991). Ph SlClan inte ri and the role of ,itkmch’lgan.

Unpublished master’s thesis, Michigan State University, East Lansl .

Rickard, W. (1999, January/February). Technotogy, higher education, and
Educom Review, a”), 4245.

 

the changing nature of resistance.

Rogers, EM. (1983). Diffusion of innovations (3rd ed.) New York' The
Free Press. '

Rogers, EM. (1995). W (4“ ed). N .
Free Press. ew York. The

Rogers, EM. 8. Shoemaker. PF. (1971). 9%
a IOI‘Is

(2nd ed.). New York: The Free Press,

Romiszowski, A.J. (1988). WW
'8

(2"d ed). New York: Nichols.
cember). Barriers to the use of educationai

Rose, SN. (1982, De .
dations to promote and Increase their use

technologies and recommen

Educational Technolo , 22112), 1245.

99

W Rosner, B. (2001 September). Studying the world beneath the org chart.
°”<f°rce. M9). 64-68.

[on-line].

Russell. TL (1999). The no si nificant difference henomenonr

Available: httpzllteleeducation.nb.calnosigniflcantdifference/

al reality? M

Russell, G. 2001, March. I ' ' 'rtu
( ) SVlrtualschoollnga Vl Available

On: The Educational Technolo Journal, 10(6), [On-line]-
h“P-//fno.orglmar01/virtualschool.html _—

ehavioral sciences

Shavelson, R.J. (1996). Statistical reasonin for the b

(3rd Ed.) Boston: Allyn & Bacon.
. Sherron. G.T. & Boettcher, JV. (1997). Distance learnin : The nglft 1°
W (Paper 17). CAUSE Professional Paper Series. BOUlde" '

SE.

h behavior

ournal

Simon, S.J. &Werner, J.M. (1996). Computer training throu9 J
. /____.

modeling, self-paced, and instructional approaches: Afieid experimel'l -
of Applied Psychology, 3196), 648-659.

Dieter“:e

Smith. K.D., Eddy, J.P., Richards, T.C., & Dixon, RN. (2000). 6 American

education copyright, intellectual property, and antitrust concerns. 1'“

Journal of Distance Education, 1_4(2), 5-1 3,

Solomon, R.L. (1949). An extension of control group design-
Psychological Bulletin. 4.6. 137-149.

Spotts, T.H. & Bowman. MA- (1995. MarCh'ADriI). Faculty use of

instructional technologies in higher education. Educational Tech no! 35(2)
56-64. E '

Staman, EM. (1990. Summer). An aCth“ plan for infusin .
the teaching/learning process. Cause/Effect. 19(2)» 34-40. g teCh"°’°9Y Into

Stinehart, K. (1988). Increasing faculty involvement in disra

In D. Sewart & J.S. Daniel (Ed.). World Conference of the Internatigrfaei tgachirfg.
for Distance Education: Develo ln distance educatlon (pp, 412-415) vgunc"
° mamo’

Sweden: Falths Tryckeri.

Taylor, S. & Todd, PA. (1995 June). Understanding information
technology usage: A test of competing models. W
3(2), 144-176. search.

100

- TaYIOI’, J.C. 8: White, V.J. (1991 July), Faculty attitudes towards teaching
m the distance education mode: A" eXploratory investigation. W

W. .313). 7-11.
. . rt
1 The continurng challenge of instructional integration and usertngpo
("399 October). The Campus Computing Project. [On—line]. Avalla .
PJ/Wwwcampuscomputinghet/summariesn 999/indexhtml
e New York: John

Triandis, HQ (1971). Attitude and attitude chan -
‘3, Mongeau. C-

Wiley 8. Sons.
lied to moral

Vallerand. R.J.. Deshaies. P.. Cuerrier, J., Pelletier. LG-
(1992). Ajzen and F ishbein’s theory of reasoned action as app . ‘ P ch 0'0
behavior: A confirmatory analysis. Journal of Persoer
2(1), 98—109.
“mg web-b ased

Visser, J.A. (2000) . Faculty work in deveIOping and teach ‘ of
ffort. The American Jouma
the

distance courses: A case study of time and e
atment of

Distance Education. 11(3), 21-32.
Walton Braver. MC. & Braver, SL. (1988). Statistical tre , ‘Bulletin
Solomon four-group design: A meta-analytic approach. W
[On-

104(1),150-154.
. t.
Weiss. S. (2000, April 9). Virtual Education 101. W

line}. Available: http://www.washington postcom/cgi-
b. . .pnilprint&articleid =A4061 2—2000Apr8
). Hope and humor: Using the hOpe scale in

Westburg, N.G. (1999
outcome studies. Ps cholo ical Re ort, _8_4_(3). 1014-1 020,

What’s the difference? A review of contemPot‘ary researcp, on th
effectiveness of distance learning in higher education (1999, Apr") [Oneli 1
- - ne.

Available: httpzl/www.ihep.com
Is instructional teleVlSion educatio”
e?

Whittington, N. (1987). .
A research review. The Amefloawm 1(1) 47 5
I § , - 7.

Willis. 8. (1998). Effective distance education p'annlngi Lessons:
eamed_

Educational Technology, 1330), 57-59.

Wolcott, LL. (1997). Tenure. promotion. and distance education.

Examining the culture or faculty rewards. 1%

Education. um. 3-18.

101

    

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93 02

 

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