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Characteristics and needs of the adult distance learner: A case study

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Content CHARACTERISTICS AND NEEDS OF THE ADULT DISTANCE
LEARNER: A CASE STUDY
by
Leslie C. Reich
A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
December 2003
Copyright 2003 Leslie C. Reich
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UMI Number: 3133330
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University of Southern California
Rossier School of Education
Los Angeles, California 90089-0031
This dissertation written by
under the discretion of hP ^ Dissertation Committee,
and approved by all members of the Committee, has
been presented to and accepted by the Faculty of the
Rossier School of Education in partial fulfillment of the
requirements for the degree of
Doctor of Education
December 17. 2003
Dean
Dissertation Committee
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DEDICATION
This dissertation is dedicated to my mother, Phyllis Kesner, and to the
memory o f my father, Stuart Kesner. From early on, my parents encouraged in
the love of learning and the importance of striving for excellence, all the while
steadfastly inspiring me to follow my dreams. Without their love, respect, and
support, this project could never have come to fruition.
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ACKNOWLEDGMENTS
iii
This dissertation was made possible by the support, time, encouragement, and
understanding of many people, without whom I could not have completed this paper
and realized a life long dream.
To begin with, my heartfelt gratitude and respect goes to my committee chair,
advisor, instructor, and mentor, Dr. Edward J. Kazlauskas. He has graciously
supported and encouraged me through all the stages of my doctoral program. Over
the last 5 years, his generosities of time, interest and assurance have been enduring
and inspiring. The words “thank you” seem lackluster in the face o f his invaluable
advice and continual support. I feel privileged to have had the opportunity to
experience his wealth of knowledge and the depth of his concern. My association
with Dr. K will be forever appreciated.
I want to express gratitude to the other members of my committee, Dr. Larry
Picus and Dr. Michael Genzuk. First, I wish to sincerely thank Dr. Picus for his
accessibility, support, adorable sense of humor, and willingness to assist in any
manner. I am most appreciative to have had him as an instructor and as a member of
my committee. I also wholeheartedly thank Dr. Genzuk for his enthusiasm, positive
direction and advice. His esteemed support and participation as part of my
committee were instrumental and greatly valued.
I must express my immense gratitude to Dr. Forest Boyd— the scope of his
help was immeasurable. Dr. Boyd was more than willingly to share the benefit of his
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iv
experience, his statistical knowledge, and his wisdom regarding the dissertation
process. I am truly indebted to him for his guidance and kindness.
I cannot forget the contributions of my family. A very special thanks to my
daughters, Meredith and Alexis, for all their understanding, patience, support, and
for quietly enduring “creative” meals when I was busy with school.
My Grandma Bess, whose love, support, and enduring confidence have been
resolute over all these many years of schooling and life. My brothers and their
wives, always there to lend an ear and forever forgiving me for not having much
time to reciprocate. Being blessed with two Dads, I also want to express gratitude to
my Dad Earle Colman, and his wife Takako, for their caring, and understanding all
those times I had to study.
In respect to brevity, I will quickly thank all my friends for their support and
mention two specifically. I want to thank my dearest friend Susie for her loving
support, and for all the inspirational lunches— I know that without her I would never
have been able to realize this goal. I also want to extend my sincerest gratitude to
my friend Julie— without her caring and ongoing guidance, I would never have made
it to this point, and for this I am eternally grateful.
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TABLE OF CONTENTS
v
DEDICATION ii
ACKNOWLEDGMENTS iii
LIST OF TABLES vii
LIST OF FIGURES viii
ABSTRACT ix
CHAPTER 1: INRODUCTION 1
Background of the Problem 1
Purpose of the Study and General Goals 8
Research Questions 10
Specific Questions 10
Significance of the Study 12
Methodological Assumptions 12
Instrumentation 13
Data Analysis 14
Delimitations 15
Limitations 16
CHAPTER 2: LITERATURE REVIEW 17
Defining Distance Learning 18
The Evolution of Distance Learning 21
Adult Learning 24
Theories 24
Learning and Motivation 29
Learning Styles 32
Demographics 35
Experience with Technology 38
Learning Experiences 41
Prior Learning and Educational Outcome 41
Instructional Format 44
Principles of Instruction 44
Pacing of Assignments 46
Summary 47
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v i
CHAPTER 3: METHODOLOGY 50
Research Design 50
Participants 50
Instrumentation 51
Data Collection Procedures 56
Questionnaire 56
Focus Groups 56
Data Recording and Analysis 58
Chapter 4: RESULTS 60
Descriptive Statistics 61
Reliability Analysis 68
Qualitative Analysis 70
Online Focus Groups 73
Summary 74
CHAPTER 5: FINDINGS, CONCLUSIONS AND IMPLICATIONS
FOR FUTURE RESEARCH 79
Summary 79
Conclusion 91
REFERENCES 93
APPENDICES 107
1: Questionnaire 107
2: Independent Samples Test 111
3: Online Focus Group Questions and Protocol 116
4: Extensive Correlation of Data 117
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v ii
LIST OF TABLES
Page
1. Student’s Computer Skill and Prior Technological Experience 52
2. Students’ Prior Distance Learning and Other Learning Experience 53
3. Instructional Format 54
4. The Instructors’ Selection of Blackboard Format 55
5. Distribution of Age 62
6. Distribution of Gender 62
7. Distribution of Marital Status 63
8. Distribution of Occupation 64
9. Distribution of Job Title 64
10. Distribution of Present Major 65
11. Distribution of Past Major 66
12. Distribution of Class Standing 66
13. Correlations 70
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v iii
LIST OF FIGURES
Page
1. Reliability Coefficients (Alpha) Scores for RQ2-RQ5 69
2. Summary of Responses to Open-ended Questions 42 and 43 72
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ABSTRACT
In order to effectively design and deliver adult distance learning courses, it is
necessary to understand the collective needs of the adult or professional student.
Studying the characteristics and the needs of the adult distance learner allows
instructors to effectively develop, improve and provide the academic and support
services considered necessary to optimize the many facets of distance learning.
The purpose of this study is to examine the process and students’ preparation,
and communication practices that maybe assessed and enhanced. By looking at the
experiences of these adult graduate distance-learning students, the understanding of
instructional concerns, issues and student preparation and communication practices
can be assessed and enhanced.
The sample population of this study was composed of one group. The
subjects (approximately n=25) studied were professional, graduate level distance
learners and were selected from a School of Education at a major research university.
The students studied were enrolled in a course on Technology in Contemporary
Education and Training.
The study population consisted of working adults, enrolled in this program
for career advancement, most of which were women with an estimated mean age of
34.
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The evaluation questionnaire (developed through a review of elements
identified in an extensive literature review) was used to gather data on the following
areas: characteristics and needs of the adult distance learner, gender, student
demographics, prior computer and distance learning experience. Asynchronous
communication, or delayed communication, was a predominant feature in this
particular course.
The demographic findings in this one course study closely paralleled that
found in the literature. Although the size and homogeneity of the participants needs
consideration, the findings provided valuable information that may guide further
study and success in the area of adult distance learning.
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1
CHAPTER 1
INTRODUCTION
Background of the Problem
The rapid expansion of the Internet coupled with a multitude of
technological advances (interest for better online delivery, cost effectiveness,
etc.) has resulted in a tremendous proliferation in distance learning. The World
Wide Web provides an alternative means for the delivery of courses and
services, and offers learners an extraordinary range of options; thus, proving
itself an indispensable educational tool.
The Internet has rapidly become a primary distance learning delivery system,
a very powerful means of communication. As of 2001, an estimated 377 million
persons were using the Internet (California Post-secondary Education Commission,
2001). Global demand for higher education is forecast to reach 160 million students
in 2025. “The Internet is bringing us closer than we ever thought possible to make
learning— of all kinds, at all levels, any time, any place— a practical reality for every
man, woman and child” (e-testimony to the Web-based Education Commission,
2000).
In addition, the developments of educational technologies have accelerated
dynamically, and have continued to rise at the rate of 30% a year (Network
Wizards, 1997). Today’s distance learners have a host of media options available to
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them, (e.g., video conferencing, computer programs, email, Listservs, and
electronic bulletin boards). Educational technologies are not single technologies but
a complex combination of hardware and software. These technologies can utilize a
combination of a video, audio, graphics or text. Even though technological
applications are often characterized in terms of their most obvious hardware feature
(e.g., computer), from the standpoint of education, it is the nature of the instruction
being given that is of much greater importance than the equipment delivering it.
“Throughout the history of human communication, advances in technology
have powered paradigmatic shifts in education” (Frick, 1991), and this shift is
occurring in higher education (Roberts, 1997). According to Judith S. Eaton, (1998)
current president of the Council for Higher Education Accreditation, this shift
represents “a change of magnitude comparable to the establishment of the land
grants institutions, the GI bill and community colleges.” Some scholars predict that
distance learning will be the norm (Strauss, 1998). James J. Duderstadt (1997),
president emeritus of the University of Michigan, opines, “that higher education
must evolve rapidly to engender a new learning culture.”
Educators and analysts predict that the popularity of online learning will
explode in the coming years (Kokmen, 1998; Strauss & White, 1999). The National
Center for Educational Statistics in the Department of Education (NPSAS) estimated
that in the 1999-2000 school year about 1.5 million of the 19 million students
involved in post-secondary education took at least one electronically transmitted
distance course.
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In 2002, students enrolled in distance education as a percentage of total
post-secondary enrollments tripled to almost 15% from just 5% in 1998 (Technology
Daily, 2000). In 2001, about 75% of all post-secondary institutions offered some
distance education courses (Texas Guaranteed, 2001 Annual Conference
Presentation on Distance Learning). The Power of the Internet for Learning, in their
2001 report, noted that 15 % of all students in post-secondary education are taking
courses through distance education. NPSAS also reported that an estimated 84% of
four-year institutions offered distance courses in 2002. It is expected that by the year
2007, nearly half of all adult learners enrolled in post-secondary education will take
some of their courses through distance learning formats (Kascus, 1997).
International Data Corporation projected that by the end of last year (2002), the
number of students enrolled in distance learning programs reached 2.2 million, with
strong growth coming from online courses.
Approximately 500 virtual universities are reputed to be in existence today,
with more than 6,000 accredited courses offered online. The total higher education
market of $1.2 billion in 1999 will reach $7 billion by the close of 2003 or,
according to a more conservative estimate, $4 billion by 2005 (Forum Futures,
2002). The California State University (CSU) System is going full force, and this
year (2003) has launched an initiative to speed the creation and use of online
teaching tools in higher education. By virtue of the sheer number of students, each
day it becomes exceedingly important to know the expectations and needs of this
very large student community.
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Data indicate that the adult student population is the fastest growing
segment of higher education market, and the older students constitute the majority of
that market. Americans over 40 are pursuing higher education in peak numbers.
The Digest of Educational Statistics reported that in the year 2001 more than 15
million adults are enrolled either full or part-time in higher education. These adult
learners are being identified as the foremost force in restructuring post secondary
education.
According to the National Center for Education Statistics (NCES)
characteristics that typically define non-traditional students are often:
■ delayed enrollment into post-secondary education
■ part-time attendance
■ financial independent of parents
■ working full-time when enrolled
■ having dependents other than a spouse
■ often a single parent
NCES estimates that over 60% of students in U. S. higher education can be
characterized as non-traditional. “Nontraditional” students are the fastest growing
segment of the post-secondary population: 40.9% of college students are over 25
(DiFiore, 2001) and nearly 12% over 40.
To restate, distance learners, are typically older than the average traditional
student (medium age of 36), the majority is women, employed full time and have
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personal commitments that compound efforts to further their education. Students
who have enrolled for online education courses in the past have tended to be working
females (Moore & Kearsley, 1996). The changing demographic of higher education
is placing novel demands on educators and institutions, causing them to look beyond
traditional classroom methods.
Distance learning technology, according to Garrison (1990), “clearly has the
potential and capability to extend opportunities for learning and addressing the
problems adult students experience in conventional programs in higher education.”
The distance-learning format moderates the traditional educational concerns of class
scheduling, transportation, timing, inflexible schedules, childcare, and/or physical
challenges. For some adult learners just “the necessity of balancing a job, family,
community, and academic responsibilities can be a major challenge” (McNulty,
1992). “Technologies of the information age have the potential to bring education to
each person by allowing individuals to take more responsibility for their learning and
achieve independence of thought and action” (Saba, 1997).
The boom in distance learning has not only affected higher education but also
K-12, the government, the military and segments of the private sector. Investors are
spending millions, soon to be billions, in the online market. Conservative estimates
from analysts at Thomas Weisel Partners, a merchant bank in San Francisco,
approximate that there will be a $10 billion virtual higher education market by 2003
and an $11 billion corporate learning market by the same year. John Chambers, the
CEO of Cisco Systems, calls online education the “killer opp” of the Internet.
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Although distance education mitigates many adult student concerns, it is
imperative to realize that “while distance education is already a fact of life for
most universities and an increasing number of community colleges, knowing
the intrinsic problems and overcoming them will be critical to successful
implementation of distance programs on a larger scale in the future” (Galusha,
1998). Educators need to be keenly aware of student success and failure
factors in this anywhere, anytime learning environment.
Some experts believe that the educational literature has not produced
validated instruments for assessing success factors among distance learners.
These researchers indicate that students’ attitudes and frustrations with distance
learning have not been fully explored, especially on the secondary level
(Dominquez & Ridley, 2001). Hara and Kling (1999) alluded that students
may not have had the opportunities to express their frustration with distance
education courses. There are relatively few actual studies of the comparison of
academic achievement of online students versus traditional, face-to-face
students (Snell & Mekies, 1999). Maggie McVay, author o f How to be a
Successful Distance Student: Learning on the Internet, believes that, “the
entire area of distance learning assessment is wide open for doctoral work. It is
something every school is clamoring to evaluate, but few have the time or
opportunity to spend extensive research on” (Me Vay, 2000). Roger Hiemstra
(1998) sees online learning environments as “uncharted waters.” Recognizing
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the need for research in the area of adult distance learning is the first step in
navigating these concerns.
But what we do know about adult learning is that “each adult learner is
different from other learners.. .each possess different beliefs, values, needs,
attitude, self-concepts, and past experiences that must be considered in
planning for the learning experience process” (Verduin & Clark, 1991).
Specific to distance learning, we recognize that not all learners are equally
predisposed to engage in self-direction in an open learning environment and
that asynchronous remote learning isn’t for everyone” (Ehrman, 1990; Kokmen
etal., 1998).
Knapper (1988) postulated that when distance learners are compared to
traditional students distance learners they are more likely to have insecurities
about learning. These insecurities are founded in personal and school related
issues, such as financial costs of study, disruption of family life, perceived
irrelevance of their studies and lack of support by employers (Sweet, 1986).
Pitfalls encountered by the distance learner fall into several distinct categories:
costs and motivators, feedback and teacher contact, student support and
services, alienation and isolation lack of experience, and training (Galusha et
al., 1998). The research repeatedly indicates that there is great need to explore
I
I
and understand the collective needs of the adult distance learner. By studying
the characteristics of the adult distance learner, educators can more effectively
develop, improve, and provide the academic and support services necessary to
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optimize the adult distance learning experience. “Good distance education
pedagogy is a good pedagogy in any classroom” (Schlosser & Anderson,
1994).
Purpose of the Study and General Goals
The intent of this study is to examine the process and students’ actual
experiences with distance learning. By examining the experiences of adult graduate
distance-learning students and exploring their attitudes and concerns, current
instructional practices can be assessed and enhanced.
The ability of educational institutions to fulfill their
responsibility of appropriately serving a diverse population of
distance learners will depend both on the knowledge gained
from further student centered research and on the flexible
programming and learner support systems made possible by
current and emerging education technologies (Thompson,
1999).
This research examines the effectiveness of distance learning by exploring
variables, such as student opinions, and student demographics. “Knowing student
characteristics and demographics helps to understand potential barriers to success,
and allows us to plan distance education to optimize student performance, retention
and success” (Wood, 1996). Knowles (1980) writes that learner behavior is
influenced by a combination of the learner’s needs in addition to the learner’s
situation and personal characteristics.
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The overall objective of this study is to reveal the attributes of professional
graduate level distance learners in asynchronous distance-learning courses. In this
paper the working definition of asynchronous distance learning is an Internet-based
course that provides interaction of learner and instructor and instructor to learner via
computer technology (email, Blackboard Course Management, etc.), asynchronously
(at different times). Students and instructor interact and communicate continually
but rarely at the same time.
The online course being studied utilizes Blackboard as its course
management system (CMS). Blackboard is a web-based course management system
which is designed to allow students and the instructors to participate in an online
course delivery format classes and also through the use of online materials.
Blackboard enabled the instructor to provide students with an online environment for
storing course information and materials as well as providing a set of faculty-student
communication tools, such as class discussion groups or virtual chat rooms, e-mail,
and bulletin boards to post course information.
The structure of distance learning does give the professional graduate student
control over time, place and pace of their education, it is not for every student. As
educators, we need to know, for whom distance education is the appropriate and
productive choice.
Although there are a multitude of attributes associated with independent
learning there are also concerns for frustration, isolation, anxiety, and/or confusion.
“Learning in a remote, asynchronous and mediated environment, albeit within the
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context of an intuitionally sanctioned curriculum, requires skills that transcend
learning aptitude and academic content” (Melburg, Lettus & Bonestell, 1993). Not
all learners thrive educationally in a self-directed open-ended learning environment.
A majority of researchers agree that not all adults are self-directed learners (Candy,
1991; Lowry, 1989). Along with the positive aspects associated with adult distance
learning this research study must also consider the obstacles that can detour the
distance-learning student from attempting, completing or continuing along the
distance-learning path.
Research Questions
This study poses the following questions:
Overall Question:
What are the characteristics and needs of the adult distance learner in a
predominantly asynchronous computer mediated communication-teaching format
course?
Specific Questions
1. What are the identified student demographics, including the variables of age,
family status, gender, employment and educational status in a predominately
asynchronous computer mediated communications teaching format course?
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2. What are the identified student characteristics, including computer skills
and prior experience with technology, prior distance learning and other
learning experiences, in a predominately asynchronous computer mediated
communications teaching format course?
3. What are the students’ reaction to the type o f instructional format, and
use of Blackboard in a predominately asynchronous computer
mediated communications teaching format course?
4. What is the relationship of student demographics to students’ computer skills
and prior experience with technology in a predominately asynchronous
computer mediated communications teaching format course?
5. What is the relationship of student demographics to prior learning and other
learning experiences in a predominately asynchronous computer mediated
communications teaching format course?
6. What is the relationship of student demographics to type of instructional
format (pacing and use of instructional modules) in a predominately
asynchronous computer mediated communications teaching format course?
7. What are students’ reactions to the instructor’s selection of the Blackboard
Course Management System (CMS) with its format and features for the
mediated communications teaching format course?
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Significance of the Study
As the needs and demands for the adult distance learner continue to grow, it
becomes exceedingly import to understand the traits and requirements of this large
student population. This study increases familiarity with the traits of the adult
distance learner in order to optimize student performance, retention and success.
Methodological Assumptions of the Study
Research Design:
This proposed study collected data by utilizing a post-course evaluation
design on one course in a School of Education, at a major research university. This
design allows for non-random assignment of a group. In this particular experiment
the pre-assembled group is as homogeneous as availability permits. The group was
asked to fill out a post course evaluation questionnaire, which was distributed and
returned on the last day of the class. A small sample of the students was involved in
focus group interviews.
Sample Population:
The subjects (n=25) studied are professional, graduate level distance learners
selected from one course in a School of Education, at a major research university.
The adult graduate students studied, were predominantly
traditional learners, over the age of 24. This was a homogeneous group,
although individual computer competency levels varied.
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The sample being studied was enrolled in a distance-learning course that
incorporates a predominantly asynchronous university-supported Blackboard course
management system as the vehicle. The students form a virtual community, where
course content (Blackboard Course Documents) and assignment instructions
(Blackboard Assignments) are available online; students submit their work to the
instructor via email (or in some instances load their work into Blackboard for all
class members to review) and receive feedback from the instructor; teacher and
students can contact each other through email, any time of the day or night.
Asynchronous communication, or delayed communication, was a
predominant feature in this particular course, being studied. The use of a chat room
(Blackboard Virtual Classroom) allowed students to communicate/work with each
other and communicate with the instructor in real time.
Instrumentation
Subject variation by condition was assessed through the use of a post-course
evaluation, presented in class, to the students enrolled in the course. A questionnaire
developed through a review of elements identified in an extensive literature review was
used to gather data on the following areas: characteristics and needs of the adult
distance learner, gender, student demographics, prior computer and distance learning
experience, and instructional format. The questionnaire was pre-tested during Summer
2002, with a sample of students similar to those in the test population. Focus group
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questions were based on factors identified in the literature and emphasized in the
survey results.
Responses to some of the specific questions in the regular USC course
evaluation data also proved useful.
Information was also gathered through the use of focus groups. These online
focus groups were designed in order to obtain more in-depth information, on selected
variables.
Data Analysis
Demographic statistics, prior experience with computers and distance
learning, and the investigation of student needs and characteristics are the key areas
of concentration.
The survey data and online focus group responses were examined to identify
patterns of needs and characteristics among respondents. The data were also be
analyzed to determine if these are significant differences in responses based on age,
family status, gender, employment and educational status, in the distance learning
course being studied.
Methodological Assumptions:
The following methodological assumptions are implicit in this study:
1. The graduate students selected were representative of the mature distance
learner.
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2. The design and data processing procedures used were appropriate to the
intent of the investigation.
3. The post-course evaluations used for the study were a reliable and valid
measure of the data.
4. The post-test design was the most accurate and appropriate design
selection.
5. The various controls for internal validity were in place during the duration
of the study.
6. The data were accurately recorded and analyzed.
7. Subjects answered the questions honestly and accurately, and their
responses reflected their actual experience.
Delimitations
The following delimitations were noted:
1. This study is designed to measure the characteristics and needs o f adult
distance learning students. It solely surveys, graduate students over the age of
25.
2. The participants of this study were limited to a select group of graduate
students in a School of Education at the major research university.
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Limitations
The following limitations are noted:
1. The sample might not be significantly large enough to extrapolate the
results to generalize findings.
2. The respondents in this study were not representative of a cross section of
all mature distance learners, nor were the sample randomly drawn.
3. This study is bound by the general limitations of using questionnaires to
generate data. Questionnaires might evoke “response sets” where the
respondents tend to agree with positive statements or questions.
4. The general limitations of using a post course questionnaire to measure
dependent variable attitudes apply to this study, which may compromise
validity and reliability.
5. The particular selection of the various adult distance learners’
characteristics and needs incorporated into the experimental section o f the
study might influence the findings.
6. To the degree that methodological assumptions set forth in the study were
not met, the validity of the study would be compromised.
7. Respondents might have interpreted questions differently than intended;
this could jeopardize the validity of the study.
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CHAPTER 2
LITERATURE REVIEW
17
To ascertain the significant needs and characteristics of the adult distance
learner it is necessary to first try to define distance learning, explore adult learning
and then carefully examine student demographics, prior experiences with technology
and learning and instructional format. Distance learning is a student centered
learning: thus, knowing the characteristics and demographics of the learner is
essential in identifying potential successes and barriers. The awareness of student
characteristics and motivators are striking indicators of who is likely to participate
and excel in distance education. Student characteristics and life circumstances
appear to have the greatest impact on participation (Kerka, 1986). Careful analysis
of the adult distance learning population establishes a firm foundation for effective
distance education.
A point of distinction, as evidenced in the literature (and implemented in this
paper) is that distance learning and distance education are terms used inter
changeably, to a variety of programs, providers, audiences and media. Before trying
to identify the characteristics and needs of the adult distance learner, it is necessary
to establish a working definition of distance learning.
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Defining Distance Learning
Although an in depth investigation of the literature revealed several key, and
reoccurring elements of distance learning, there was not one consistent definition. As
technology evolves and expands so does the definition of distance learning. In the
words of Shale, (1990) “distance education is beset with a remarkable paradox - it
has asserted its existence, but it cannot define itself.” Technological innovations are
continually emerging, thus allowing and demanding distance education to advance
along with these strides.
In 1972, educational theorist Michael Moore, defined distance learning as:
“the family of instructional methods in which the teaching behaviours are executed
apart from the learning behaviours so that communication between learner and the
teacher must be facilitated by print, electronic, mechanical or other devices.” “Its,
[distance learning], hallmarks are the separation of teacher and learner in space
and/or in time (Perraton, 1988) the volition control of learning by the student rather
than the distant instructor (Jonassen, 1992), and noncontiguous communication
between student and teacher, mediated by print or some form of technology
(Garrison & Shale, 1987; Keegan, 1986). Instructional theorist, Willis (1993)
explains it, “at its most basic level, distance education takes place when a teacher
and student(s) are separated by physical distance, and technology (i.e., voice, video,
data and print) is used to bridge the instructional gap.” In 1995, Cantelon expands
the definition of distance education to “not merely meaning a geographic separation
between learner and instructor but also including cultural, emotional and pedagogical
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distance.” He felt that “what is truly unique about distance education is the site of
learning is transformed from a place to a process.”
For instructional technologists, Moore and Kearsley (1996), distance
education is “planned learning that normally occurs in a different place from
teaching.” It also requires special techniques of course design, special instructional
techniques of course design, special instructional techniques, special methods of
communication by electronic and other technology, well as special organizational
and administrative arrangements.
It is not just individual educators or theorists who try to craft definitions and
hypothesis in order to explain the nature of distance learning, numerous associations
and business have taken on the challenge. The California Distance Learning Project
(CDLP) characterizes distance learning (DL) as
an instructional delivery system, which connect learners with
educational resources. DL provides educational access to
learners not enrolled in educational institutions and can augment
the learning opportunities of current students. The
implementation of DL is a process, which uses available resource
and will evolve to incorporate emerging technologies.
The United States Distance Learning Association (USDLA) defines distance
learning as “the delivery of education or training through electronically mediated
instruction including satellite, video, audio graphic, computer multimedia technology
and other forms of learning at a distance.” The USDLA further clarifies its position
by stating that distance learning refers to teaching and learning situation in which the
instructor and the learner are separated geographically and must rely on electronic
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devices and print materials for instructional delivery.” USDLA definition
encompasses distance teaching or the instructor’s role in the process; and distance
learning or the student’s role in the process.
Another noted organization The Association of Education Communication
(AECT) defined instructional technology, in 1994 as the theory and practice of
design, development, utilization, management and evaluation of processes and
resources for learning. This was a their more streamlined version.
Definitions for distance learning can be broad and too vast to touch on all of
them. When asked to define instructional technology Gentry (1987) cited in Cutshall
(1999) stated, "it is possible to see that meaning depends considerably on what part
of the elephant is being touched and by whom!” What can be best gleaned from the
select literature is a compilation of the key elements. The most significant features
are:
1. the separation of teacher and learner during at least a majority of each
instructional process;
2. the use of educational media to unite teacher and learner and carry course
content;
3. the provision of two-way communication between teacher, tutor, or
educational agency and learner;
4. separation of teacher and learner in space and/or time;
5. Volitional control of learning by student rather than distance instructor.
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These five major elements are widely recognized in the distance
learning, and do represent some essential areas in distance education. But
for this researcher, the definition of distance learning goes much deeper
and must incorporate the instructor’s and student’s role in the process.
Identifying the fundamentals of distance learning affords us a basic
understanding. It is almost an impossible task to try and define something that is
continually revolutionizing. To further understand the dynamics and characteristics
of adult distance learning it is important to first explore its origin.
The Evolution of Distance Learning
The history of distance learning is rich and extensive; the medium has
changed from pen and paper correspondences to real-time Internet courses. There
are multitude of ideas and theories that offer explanations as to when and where this
mode of learning originated. One source stated that distance learning could be traced
as far back as the first century, when the Apostle Paul wrote to the early Christian
churches, teaching them about religion from a distance (from his prison cell). The
evolution of distance learning is sometimes classified in “generations” as in the
adaptation of Garrison’s (James & Gardner, 1989) distance learning model.
Historically, the first generation of distance learning can be traced lack to the
1700’s and the beginnings of print-based correspondence study in the U.S. In the
late 1800’s correspondence courses had gained international popularity. In the early
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1890’s, universities and private schools offered correspondence courses to
elementary, secondary, higher education, and vocationally oriented students.
In 1886, Pennsylvania State University was of the first universities to deliver
distance learning in an organized manner. To communicate with its distance
learners, Pennsylvania State used “the state of the art” technology of the day, the
U.S. mail. This was the accepted norm for distance learning until the 1950’s.
Instructional media proceed from print, to instructional television, to the current
interactive technologies. Often contact with instructors was limited to the grading of
tests and papers which students would complete and return by mail. Interaction was
infrequent and slow. These types of courses still exist today.
In the 1950’s, (the second generation), instructional radio and television
became popular. According to Margaret Cambre (1991), in the late 1950's and early
1960's, television production technology was mostly confined to studios and live
broadcasts, where master teachers conducted widely viewed broadcast classes. The
large problem was although teachers might be experts in subject matter; many were
unable to engender mass audience appeal. In the early 1970's, the emphasis turned
from bringing master teachers into the classroom to taking children out of the
classroom into the outside world. This trend was reversed later in the 1970's, as
professionally designed and produced television series introduced students to new
subject matter that was not being currently taught, it was considered a significant
complement to the core curriculum. Educational shows like Mr. Wizard were
examples of this type of programming format. The major production expenses were
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an issue. Also during this time, professionally designed and produced television
series introduced adult learners to videotape programs focused on basic skill
improvements, English as a second language and GED preparation. There were
drawbacks due to “the lack of two-way communications channel between teacher
and learner” (Fleischman, 1998).
Realizing the problem of the lack of a 2-way communication between teacher
and student, a limited number of major universities began to research and provide
distance-learning opportunities through the combined use of innovative technology
and home study techniques. Cable TV and videoconferencing became more widely
available in the 1980s; and attempts to integrate technology with print resources
became more involved in the 1980’s (Willis et al., 1993).
As more sophisticated interactive communications technologies became
available, distance educators adopted them, and entered the third generation of
distance learning. Presently, the most popular media are computer-based
communication including electronic mail (e-mail), bulletin board systems (BBSs),
and Internet and intranet; telephone-based audio conferencing; and ideoconferencing
with 1- or 2-way video and 2-way audio via broadcast, cable, telephone, fiber optics,
satellite, microwave, closed circuit or low power television (Fleischman et al., 1998).
This third generation has the potential o f expanded out reach, highly interactive
programming, the creation of supportive learning communities, and access to reach
libraries of material.
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Realizing the educational and financial possibilities, universities,
corporations and the private sector are sprinting to become part of the distance
learning growth. Opinions do differ on the soaring popularity of distance education.
A recent American Federation of Teachers (AFT) task force reported that too little is
known about the effectiveness of distance learning and that more independent
research is needed (Twigg, 1996). AFT and Twigg are just a few examples, found in
the literature, that indicate that distance learning providers need to be keenly aware
of the significant issues that affect successful adult distance learning. Knowing the
needs and characteristics (e.g., adult learning styles, demographics, academic
preparedness, academic experiences, etc.) of the distance learner is paramount to
understanding the triumphs and barriers to this type o f learning.
Adult Learning
Theories
To realize and maximize the educational outcomes in distance learning, there
must be an awareness of how adults learn and what motivates them to do so. By
examining the prominent adult learning theories, and giving great consideration to
the distinct and unique characteristics, motivations, and learning styles of the adult
learner, puts us closer to the goal of successful learning.
The most recognized, and current theory of adult learning is based on the
work of Malcolm Knowles (1980) who coined the term Andragogy. Knowles, in his
theory of Andragogy, endeavored to differentiate the way in which adults learn (in
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relation to children). Knowles theorized that adult learners have distinct and
unique characteristics, motivations and learning styles. Knowles (1980) believed that
the learner’s, needs, situation and personal characteristics influenced learner
behavior, so knowing these characteristics is tantamount in implementing successful
learning.
Knowles posited that adults are self-directed and adults expect to take
responsibility for decisions, and that learning situations must accommodate this
essential aspect. He felt that instruction for adults needed to focus more on the
process and less on the content being taught, and that instructors should adopt a role
of facilitator rather than lecturer or grader.
Knowles applied the principles of Andragogy to the design of personal
computer training (1984, Appendix D) and found:
1. There is a need to explain why specific things are being taught (e.g., certain
commands, functions, operations, etc.)
2. Instruction should be task-oriented instead of memorization — learning activities
should be in the context of common tasks to be performed.
3. Instruction should take into account the wide range of different backgrounds of
learners; learning materials and activities should allow for different levels/types of
previous experience with computers.
4. Since adults are self-directed, instruction should allow learners to discover things
for themselves, providing guidance and help when mistakes are made.
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Evidence in the literature, bears out that these assumptions are at the very
core of a successful distance education.
Stephen Brookfield (1992) distinguished authority in adult learning, argued
that chronological age is a less defining principle, and that theory of Andragogy
should place greater value on the variables of ethnicity, personality and political
character. He felt that “to construct an exclusive theory of adult learning- one that is
distinguished wholly by its standing in contradiction to what we know about learning
at other stages in the lifespan - is a grave error.” Brookfield and his associates
(1992) postulated that adult learning should be investigated through the four
following major research areas: self-directed learning, critical reflection,
experimental learning and learning to learn. The research again supports that the
four areas Brookfield sites are fundamental tenets of effective distance education.
Kearsley (1986) examined the theory of Andragogy and then interpreted its
practical meaning for distance education. He agreed with Knowles, and stated that
instruction for adults needs to focus more on the process and less on the content, and
that instructors should adopt a role of facilitator or resource rather than lecturer or
grader (Kearsley et al., 1986). Adult learning is best facilitated when the teacher
can give up some control over teaching processes and planning activities and can
share these with the learners (Brundage & MacKeracher, 1980). Distance
learning does just that, it emphasizes self-directed learning and shifts the
role of the instructor from “sage on the stage” to “guide on the side”
(Saba, 1997).
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The majority of adult learning experiences have been in a
traditional classroom setting, with books, and instructors who lecture and
grade, not facilitate as Kearsley (1996) suggested. The traditional student
has be likened to a “passive receptacles for information that the instructor
relays” (Jonassen, 1996), as alluded to in Carroll’s (1990) treatise against
the systematic approach to learning and instruction. Carroll, in his work
The Numbers Funnel, described this legendary funnel, which
supposedly had the power to make people wise, by quickly pouring
knowledge into them. While facts and information must be presented,
students’ minds are not simple vessels needing to be filled with
knowledge, but rather channels that analyze and explore knowledge and
that serves as the conduits to build on what already has been learned and
is known (Viau, 1993).
Paulo Freire (1970) in the Pedagogy o f the Oppressed writes that
education thus becomes an act of depositing, in which the students are the
depositories and the teacher is the depositor. Instead of communicating,
the teacher issues communiques and makes deposits, which the students
patiently receive, memorize and repeat... individuals cannot be truly
human. Knowledge emerges only through invention and re-invention.
Carroll’s 10 years of empirical research revealed that “the commonly
used systems approach to instructional design performs horribly at
producing effective instruction and the newer method based on
constructivism and other cognitive theories perform much better”
(Carroll et al., 1990).
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In most learning environments, the importance of asking a question
and getting an answer is fundamental to the process. For thousands of years,
the Socratic method has endured as a key component in learning and
teaching. Critical inquiry and inductive reasoning rely on raising the
appropriate questions, and arriving at the correct answers. Regardless of
discipline, subject matter, or mode of delivery good teachers will create the
environment in which the right questions are explored.
Vygotsky (1978) posited that problem solving and the construction of
knowledge was the essence of the learning process. He defined the learning
process as the establishment of a “Zone of Proximal Development” in which exists
the teacher, the learner, and a problem to be solved. The constructivist perspective
learning is determined by the complex interplay among students existing knowledge,
the social content and the problem to be solved (Ertmer & Newby, 1993). The
teacher provides an environment in which the learner can assemble or construct the
knowledge necessary to solve the problem. Specific to distance education, this
translates into presenting problems and learning situation to which the adult learner
can relate, as well as providing the informational resources to solve the problems. In
the words of 20th century poet and scholar Theodore Roethke, “I learn by going
where I have to go.” Technologies of the information age have the potential to bring
education to each person by allowing individuals to take more responsibility for their
learning and achieve independence of though and action (Saba, 1997).
Distance education approaches to learning are based on the belief that
“individuals construct their own understanding of the world as they acquire
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knowledge and reflect on experience” (Kerka, 1996). The Internet has helped to
open up the world of self-directed learning; it supports the context of hands on,
student centered learning via the Internet. Instructional systems in distance
education are learner-centered which differentiates them from curriculum centered
and instructor centered forms of learning (Saba et al., 1997). A technology-based
environment will tend to be more:
■ Learner centered, rather than teacher centered
■ Case based rather than content based
■ Contextualized, rather than abstract
■ Democratic, rather than elitist
William Draves (1997) asserts that the Internet has “exploded” the traditional
method of teaching into two parts: cognitive learning and affective learning.
Cognitive styles are the information processing habits of the individual. These
represent an individual’s typical mode of perceiving, thinking, remembering, and
problem solving. Learning style is the composite of characteristic cognitive, affective
and physiological factors (Keefe, 1991).
Learning and Motivation
An integral component of learning is motivation. Motivation makes a direct
contribution to learning by focusing students on certain desired learning goals and
increasing the effort they expend on reaching those goals (Newby, 2000). In order
to build a successful teaching environment, no matter the medium, it is prudent to
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understand what motivates an individual to want to learn, achieve, and excel.
Simply put, instructors aware of the possible motivations behind student enrollment
can better shape their instruction and instructional materials, toward a positive end
for both student and teacher. Motivational theory provides a valuable theoretical
framework for developing specific strategies that could prove supportive in a
distance- learning environment.
Cyril O. Houle conducted one of the most famous studies on what motivates
learners. He identified three subgroups to categorize motivational styles:
(1) Goal-oriented learners use education to accomplish clear-cut objectives.
(2) Activity-oriented (social) learners take part mainly because of the social contact.
Houle wrote, “their selection of any activity was essentially based on the amount and
kind of human relationships it would yield.”
(3) Learning-oriented learners seek knowledge for its own sake. “For the most part,
they are avid readers and have been since childhood.... and they choose jobs and
make other decisions in life in terms of the potential for growth which they offer.”
Allen Tough (1979) simplified Houle's motivational model by suggesting that
adults learn because of (1) an increase in self-esteem, (2) a sense of pleasing and
impressing others, and (3) certain pleasures or satisfactions. Knowing and
incorporating motivational theories into teaching methods and course design
motivates and supports adult students in an online or traditional learning
environment.
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Motivation is an internal state that leads people to choose to work toward
certain goals and experiences. It defines what people will do rather than what they
can do (Keller, 1983). Motivation is a common influence on human activities, and it
is, in turn, influenced by variables, some internal, such as perception, wants and
personal goals, and some external such as opportunities and rewards.
Rogers (1969) distinguished two types of learning: cognitive (meaningless),
and experiential (significant). Cognitive applies to academic knowledge and
experiential applies to applied knowledge, “which addresses the needs and wants of
the learner” (Rogers et al., 1969). An example of experimental or affective learning
might be a person interested in becoming wealthy might seek out books or classes on
economics, investments, accounting, etc. “Such an individual would perceive any
information on this subject in a much different fashion than a person who is assigned
a reading for class” (Rodgers et al., 1969).
Adults also have different motivations for learning, as evidenced in the
Rodgers and his associates (1969) quote and pointed out by Cantor (1992);
■ To make or maintain social relationships
■ To meet external expectations
■ Learn to better serve others
■ Personal advancement
* Escape or stimulation pure interest
Thus, realizing the possible motivations for student interest and achievement
not only allows for a more thorough understanding of what makes distance learning
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attractive to adult and professional students but also helps to enhance learning. In
other words, theory informs practice. Being knowledgeable in the theoretical
foundations of learning assists educators in the selection of the tools and techniques
that will work best with specific students in achieving specific learning goals.
Understanding the motivation to learn is as important as understanding learning
styles and characteristics of adult learners.
Learning Styles
People, specifically adults, learn in different ways. In order to be effective,
distance educators need to understand various learning styles. Distance learners’
benefit from having a variety of training techniques built into each course, appealing
to a variety of learning preferences. Learning style theory posits that learners can be
characterized by how information is preferentially perceived (sensory or intuitive),
organized (inductive or deductive), and processed (active or reflective), by what
modality is preferred (visual, verbal, or tactile), and by whether progression toward
understanding follows a logical, sequential progression of small steps or global, a
more holistic progression (Berg & Poppenhagen, 1985; Butler, 1988; Felder, 1993;
Hartman, 1995; Lawrence, 1982). Learning types complex interactions of learner’s
histories and personalities (Caffarella & Barnett, 1994) are thus composites of
cognitive, affective, physiological, and psychological factors.
Buell and Buell (1987) studied the relationship of adult modality preferences
for learning and found that there is support for the concept that learning style is an
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important consideration in adult learning situations. The concept of learning style
originated in the study of individual differences. Not only are there striking
differences in the way people learn and process information, but there are significant
differences in how learning styles are defined and measured. Kolb (1986), a noted
theorist, felt that learning styles should be seen on a continuum running from:
■ concrete experience: being involved in a new experience
■ reflective observations: watching others or developing observations about
own experience
■ abstract conceptualization: creating theories to explain observations.
■ active experimentation: using theories to solve problems and make
decisions.
Multimedia technologies can support learner-centered instruction by giving
them choices among arrange of learning styles and modalities. Using technology
also allows adult learners to control the pace, scope and sequence of information.
The adult learning style continuum parallels the basic precepts of adult distance
learning.
Identifying the definitive adult learning theory is not nearly as crucial as
recognizing that individual learning style is an important variable that influences
adult learning success. Here, the importance lies in making instructors and
instructional designers acutely aware of differing adult learning styles. As the
literature reiterates, each adult learner possesses different beliefs, and varied needs
and attitudes. For instruction to be effective and learning to take place, on or offline,
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student characteristics must be recognized and accommodated. The implication
being that “teachers should try to insure that their methods, materials and resources
fit the ways in which their students learn and maximize the learning potential o f each
student” (Sarasin, 1998). The recognition of student learning styles has the potential
to significantly and positively impacts the design, delivery and effectiveness of adult
distance learning.
As consistently noted in the literature, learning styles are characteristic
cognitive, affective and physiological behaviors that serve as relatively stable
indicators of how learners perceive, interact with and respond to the learning
environment. An expert strategist, Winston Churchill, once stated, “Personally, I am
always ready to learn although I do not like always being taught.” Knowing student
characteristics helps the educator to understand potential barriers to success, and
allows us to plan distance education to optimize student performance, retention and
success (Wood, 1996). Although not specific to distance education, centuries old
wisdom and Confucius dictate, “All wisdom is rooted in learning... when things are
properly identified, they fall into natural categories and understanding becomes
orderly.”
Moreover, if a student is aware of their preferred learning style, they are
better skilled to handle any incongruities, which may surface due to their
expectations for distance education and the instructional tools and strategies. “The
illiterate of the 21st century will not be those who cannot read and write, but those
who cannot learn, unlearn and relearn” (Alvin Toffler, n.d).
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As more adult and professional learners select distance education,
instructional strategies are being challenged in new and unique ways. It has become
increasingly important to recognize and develop educational strategies that are
sensitive to adult student differences.
Demographics
In order to be able to distinguish the needs and characteristics of the adult
distance learner it is not only essential to understand how adults learn but also it is
imperative to know the demographic of this sizable student population. Targeting and
identifying this large student population best serves their diverse needs. It is vital to
recognize the differences and similarities in the demographics of those who choose and
succeed in an online learning over a more traditional learning experience.
It is fundamental when designing any academic program to determine whom
the students will be. When any academic program is designed there are considerations
regarding the basic characteristics of students, including their age, interest, skill levels,
academic preparedness and career goals (Picciano, 2001). With respect to distance
learning, these very same areas need and must to be considered.
Before reviewing the statistical research on adult student demographic it is
necessary to first recognize an individual students’ contextual situation. Knox (1977)
as evidenced in the literature, points out that that family, work, community roles,
physical condition, personality and earning interests all affect the adults’ ability and
willingness to participate in adult education. A multivariate analysis indicates that, in
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many cases, changes in educational or career goals, finances, time constraints or
family obligations all contribute to decisions to defer one’s education (Picciano et. al.,
2001).
Although adult distance learners are viewed as a diverse population,
surprisingly the research indicates that they are not to be regarded as a homogenous
group (Holmberg, 1995). However, many distance learners do share extensive
demographics and situational similarities, which provide the basis for profiles of the
“typical” distance learner in higher education. These shared characteristics, as noted in
the literature, have generally reflected some combination of demographic and
situational variables as age, gender, ethnic background, disability, location, and life
roles (Thompson et al., 1998).
According to Purnell, Cuskelly and Danaher’s (1996), students in distance
learning courses are “of mature age, have demanding family and work commitments,
and have had a long break since their last formal study.” According to Wallace
(1996) the demographic of an adult learner is a student over the age of approximately
25 years old. In the United States, the “typical” distance-learning students are
between the ages of 25 and 50. Two thirds of them are female, and most are married
and work full-time (National Center for Education Statistics, 1997).
Although there is no exact statistical information to indicate the number of
females enrolled in distance learning courses in America, Wallace and associates
(1996) indicate, “there is a widespread agreement that female students outnumber
males.” When doing their distance university studies, many {women} face the
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additional pressures from housework (Purnell, Cuskelly & Danaher, 1996)
childcare and earning a living. Over 70% of recent graduates who studied by distance
were in full-time employment while they were involved in the learning process (Wood,
1996). It was in the 1980s when the student populations underwent this dramatic shift
from the single, residential student between the ages of 18 and 23 to a more non-
traditional student.
Hanson (1997) provided a review of the literature on adult distance learners
and found that there was little difference on gender or age, other than the fact that
attrition occurs more frequently over the age of 25. Wang and Newlin (2001) concur
and note that gender and age are not reliable predictors of online student performance,
although according to Rekkedal (1983), students over 50 appear to have higher course
completion rates.
Halsne (2002) conducted research-using MANOVA (Multiple Analysis of
Variance) in which he compared the demographic characteristics of the traditional and
non-traditional student. The results of his research indicated that there were significant
differences between students who participated in online classes and those who
attended more traditional classes. He found that online learners tended to be more
visual and spend more time on class work than their traditional counterparts. The
demographics o f this particular study also indicated that these students were white,
approximately 30 years of age, and had a medium income of $40,000 per year. What
was most about this study, according to Halsne and associates (2002) were the
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recognition that instructional delivery must take into account individual
differences by offering a wide variety instructional of options.
Experience with Technology
When discussing prior computer and technological experience, the discussion
needs to be addressed from both sides of the podium, student and instructor. The
experiences of each impact the other. A concern encountered by some distance
education students is the lack of technical training. Although computer use is
expanding rapidly, many adult students are not well acquainted in the uses of
technology, such as the Internet, Blackboard, email, etc. “Using electronic medium
in distance learning can inadvertently exclude students who lack computer or writing
skills (Galusha et al., 1998). Research suggests computer anxiety appears to
dissipate in direct proportion to the amount of contact individuals have with
computers; experience with computers improves attitudes toward computers (Ursich-
Lensker, 1990).
Even courses that require only a very basic level of computer competency
can be problematic for some students. At the minimum, these students need to be
familiarized with the fundamentals of the operating system used in their distance
education course. An experienced instructor knows to address these needs early on,
thus, minimizing any technical barriers. Often, the practiced instructor attends to the
basic technological issues at the beginning of the course, possibly in a face-to-face
lab type class. The instructor models the technology, which “allows students to
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observe how to use it; a direct teaching technique which enhances student
confidence in using technology” (Brand, 1998).
The majority o f distances learning courses use an electronic delivery system
(as did the course used in this study), and those students who have had little or no
prior computer experience might feel a bit intimidated by this new media. Capable,
experienced distance educators are more likely to be able to mitigate student
discomfort with technology and identify and the various types of technology
necessary to support a distance education course The variety o f technology most
often includes: course authoring software, communication technology such as e-mail,
chat rooms, Listservs, browsing the Internet or accessing electronic resources.
For students to be “comfortable and effective,” their instructors need to
become "comfortable and effective" with all the technology used in their [distance
education] course (Parker, 1997). Me Kenzie (1998) asserts that many schools suffer
from “screen ‘savers’ disease,” where even though the schools have new computer
networks, the teachers don’t know how to use them. Typically, substantial quantities
of electronic-based information are used in a distance-learning course, and only an
experienced instructor can direct the distance learner in how to manage their study
time, and the coursework. “Most professors come to distance education with
traditional teaching experiences and find that the theoretical-based assumption that
worked successfully in face-to-face instruction does not translate well into
technologically mediated instruction”(Schieman, Taire & McLaren, 1992).
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The skills required to design and implement a distance education course do
vary with each course. Some courses with multi-media elements, which include
sound and video clips and video and audio-conferencing activities, might require
more expertise than text and graphics based materials. Here, again, the issue of prior
technological experience of the teacher and even that of the student would enhance
course success.
A distance educator may benefit from employing other general computer
competencies like file management. File management allows the instructor to keep a
record of each student’s contributions to class discussion through e-mails, bulletin
board or chat room messages, thus giving a clear picture of student involvement.
Among other factors affecting student success, according to Billings (1989), is “the
need for feedback and relief from a sense of isolation.” Schmidt and Faulkner
(1989) join the list of experts that warn “one limitation is the effectiveness of
distance education for some students who need direct interaction with a classroom
teacher and with other students.” “To know someone here or there with whom you
can feel there is understanding in spite of distances or thoughts expressed, can make
of this earth a garden, Goethe.”
An instructor who can devise a method of organizing and responding to
messages without spending all of their time engaged in and tracking the
communications within the course, can be more efficient and effective and have
more time for other educational responsibilities. Technical competency for
instructors is more than knowing how to run software; it also includes a willingness
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to be innovative in using different technologies and combinations of technologies
(Alley, 1996).
Some technologies present ergonomic problems that can hinder learning. For
example, those distance programs that employ video conferencing techniques, the
physical environment and equipment set up is important. Classrooms can be noisy,
sensitive microphones and equipment and rooms with poor acoustical quality can
seriously diminish sound quality. Poor lighting and bad camera placement can
reduce video quality. There is instructional concern but not relevant in regards to the
course used in this study.
There is more to distance learning than learning to use technology; it is also
learning additional and diverse ways to teach. Some experts suggest that the change
to this delivery format also engenders a change in teaching and learning styles
needed to make full use of the delivery technology (Brown, 1996).
Distance education has the opportunity to foster a student centered learning
process and the responsibility to retrain students within this new model o f instruction
but this opportunity can only be realized when the distance education student (and
the instructor) is comfortable with the technology (Parker, 1997),
Learning Experiences
Prior Learning and Educational Outcome
The prior skills and knowledge that instructors and student bring with them to
the distance learning experience can only help to mitigate the difficulties and barriers
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42
encountered. One of the major challenges for distance learners and educators is
the re-orienting of student and instructor to this “different” way of learning. In a
citation from Tinto (1975), Keegan hypothesized that students who did not receive
adequate reintegration measures such as electronic or telephone communication,
would be less likely to experience complete academic and social integration into
institutional life. Therefore, such students are more likely to drop out (Sheets, 1992).
Acquiring the competencies to teach web-based courses requires time for
training and for the integration of training into teaching practice. One-shot training
sessions have little impact on instructional practice. It is much more academically
effective to have an experienced instructor, who is building upon prior skills, not
“winging it” along with the class (Brand et al., 1998). An experienced instructor is
able to initiate and recognize opportunities for learner-centered activities, at a
distance. The fundamental difference between a traditional and online course is the
combination of learner-centered learning activities and the potential for technology-
facilitated interaction and enhanced accessibility to information through Internet-
based technologies. In order to take advantage of the possibilities for synchronous
and asynchronous communication distance education courses, instructors need to be
able to design and implement learning activities that integrate these interactive
elements into the course. Interaction in distance education is essential to student
achievement. Academic preparation has been determined to be an important factor
in online success. One study (Eisenberg & Dowsett, 1990) indicated that students
with little (one course) or no distance education experience comprised nearly one
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43
quarter o f student who dropped out. Additionally, Eisenberg and Dowsett found
that students who had completed two or more distance education courses contributed
to only 12.5% of the total dropout. In a variation of this study, Reed and Sork (1990)
indicated that more classes a student completes, the more comfortable and confident
the student becomes with the distance-learning format. Students who do not see
themselves as independent learners or who have not had prior distance learning
experience can become discouraged.
For the first time student, their perceived lack o f student instructor interaction
can be detrimental in distance learning. Slow instructor feedback can also lead to
feelings of inadequacy and insecurity, and a lack of confidence in their own abilities
(Wood, 1996).
Conversely, there are those experts that believe that not even the lack of
previous or recent education is necessarily a stumbling block, despite the initial lack
of confidence (McCahon, 2000). If effective support and appropriate encouragement
were offered at the onset, the lack of previous education and familiarity with this
type of learning diminishes as an area of concern (McCahon et al., 2000).
Educational level prior to enrolling in a distance education course has been
found to significantly relate to persistence (Rekkedal et al., 1983). In 2002, Wang
and Newlin furthered Rekkedal’s earlier findings and reported that students who
have achieved higher levels of education, who have higher grade point averages, or
who have already successfully completed a distance education course are more likely
to succeed. Osborn (2001) has shown that the number of previous learning courses
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44
taken by students reliably discriminates between students who drop out compared
to those who remain in Web-based or videoconferencing courses. This is attributed
to students’ prior experience with distance learning courses, which increase their
familiarity with the technological demands of the virtual classroom. These students
have developed confidence in their ability to take advantage of the learning
opportunities available to them in this type of learning environments. Osborn also
concluded that students who remain in distance learning course take a greater
number of college courses and have higher college GPA’s compared to those
students who drop out of these courses.
Instructional Format
Principles of Instruction
Instructors involved in distance learning course design and delivery require
competencies that can be different than in a face-to-face and print based distance
education context. The instructor’s personal attitudes towards teaching and learning,
knowledge of and capabilities in using technology, the time required to develop a
successful course and the instructor’s relationship with students greatly influence the
development and delivery of a distance learning course. “A teacher who clearly
understands the possibilities of his or her teaching style can make consistent
judgments about how best to use the medium” (Grasha, 1996).
Some instructors may lack the understanding of the basic principles of
instruction, and technological competence alone is not enough to facilitate effective
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45
technology integration. “The challenge of translating knowledge through the
visual, non-linear hypermedia of technology” requires an entirely different pedagogy
from which [instructors]... learned to implement” (Deal, 1998). It is essential for the
distance educator to not only “be able to assist with the use of the technology, but
also help with the revision of the instructional design” (Parker et al., 1997).
Instructors of distance learning courses need to carefully plan and have a
focused understanding of course requirements and student needs and learning styles.
Distance educators need to be able to design and clearly communicate the specific
course objectives to their students. Designing or re-designing a course for distance
delivery requires not only rethinking the content but also adopting a new and quite
probably a constructionist view of teaching and learning. “The syllabus must become
the road map and the student the driver when instruction is mediated by technology”
(Parker et al., 1997). The danger in not having clear goals, and pedagogical
objectives is that technology will be acquired but not truly integrated into the
teaching, learning, and research of the school (Horgan, 1998). A well-structured
distance-learning course places instructional objectives foremost. The technology
should be as invisible as possible — just another tool that teachers can use to
effectively convey the content and interact with students.
Careful consideration must be given to the special needs of students
undertaking distance education for the first time. Of particular importance is the
design of study materials for distance students. Study materials must take into
account the significant proportion of students who enroll with little or no experience
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46
of distance study. “The students are at risk of dropping out unless they develop
study survival skills as rapidly as possible (Wood et al., 1996), and course content
has been found to affect student persistence. Moore and Kearsley (1996) discussed
the importance of a set of general design principles or success in distance delivery
courses. These general principles included good structure, clear objectives, small
units, planned participation, stimulation, variety, feedback and continuous
evaluation.
Different coursework designs have more favorable results than others. “The
course content itself cannot be ignored in any theoretical or practical consideration of
distance education attrition” (Bullen, 1996). Poorly designed course work can be
extremely detrimental to the distance learning process. Presenting content material
in modules is a way of pacing the class and engages and re-engages the student.
Students who actively participate in a timed/structured series of relevant and
interactive online activities are more likely to experience the maximum benefits of
the instructional environment.
Pacing of Assignments
Another critical consideration, in course design, is the use of pacing
techniques. An informed instructor is aware that pacing material presented to
distance education students appears to have a positive effect on course completion
rates. A study on completion rates found that universities, which used pacing
techniques, had completion rates that more than doubled those institutions in which
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47
the courses were open-ended (Coldeway, 1986). Even when the course work and
delivery methods are similar, the student whose work was more effectively was less
likely to drop the course.
In 1996 Moore and Kearsley developed a set of six variables, which they
judged the effectiveness of a distance education course. The fourth variable was
pacing. Tailoring modules to fit a particular content area has resulted in positive
effects on learning. Pacing is very much connected with quality and quantity of
participation on the parts of both the instructor and the student. Online
communication and learning depends on the visibility of the student, and pacing is
one of the ways instructor knows that the student is in attendance. The students also
need to know the instructor is there and part of the class. When it comes to pacing
and instruction participation, the rule is simple: If you are not participating (i.e.,
providing input to the class) and talking in this asynchronous classroom, you are not
there (White & Weight, 2000). By including structured activities, such as timelines,
deadlines and feedback helps to motivate students and provide them the framework
to function in a flexible environment.
Summary
In essence, the goal of this literature review was to try to identify the
characteristics and needs of the adult distance learner, in hopes of affecting a positive
distance learning experience. This is no small task, and there were a plethora of vital
considerations. To begin understanding the adult distance learner a working
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48
definition o f distance learning needed to be established in order to create some
perimeters and a sense of commonality when discussing this educational medium.
Next, it was essential to examine of the origin of distance learning. In
knowing the genesis of distance learning, this gives a clearer picture of its evolution
and its effectiveness over the years. As indicated in the literature, there are differing
opinions regarding the successes of distance learning. In order to maximize
educational outcomes and minimize setbacks in the distance education arena, there is
a necessity, almost an obligation, to understand the how’s and why’s o f adult
learning and the who’s of the distance learner.
Just examining the volumes of adult learning theories is not enough. The
research needs to go beyond basic theory and explore motivation, learning styles and
learning style preference— all in the context of distance learning. With a workable
definition of distance learning, a clear understanding of its origin and a considerable
perspective on adult learning only then can we begin to examine the specific
characteristics needs of the adult distance learner.
Technology has the potential to transform teaching but only when in
partnership with good teaching (Armstrong & Yetter-Vassot, 1994). Good teaching
here means being able to identify the characteristics and needs of the adult distance
learner thus insuring the effectiveness and meaningfulness of a distance education
course. Planning for the introduction of a major innovation like instructional
technology is further assisted by learning organizational concerns (Bandura, 1997;
Harris 1997; Rogers, 1995). Optimizing a strong understanding of the supports and
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49
concerns required by distance learners provides a firm foundation for the creation
of successful distance learning environments.
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50
CHAPTER 3
METHODOLOGY
This study was designed to identify the characteristics and needs of the adult
distance learner, in a predominantly asynchronous computer mediated
communication teaching format. This study surveyed the attitudes and other self-
reported data of adult distance learners. Participants (graduate students in Education
from a major research university) were measured (after completing the course) on
their personal demographics, prior computer and technology experience, prior
learning and distance learning experience, and the type and combination of
instructional format (modules, pacing, and selection of Blackboard, etc.) in a
distance learning course.
This was a descriptive research study, in which the research methods
included both the research methods including both quantitative and qualitative data.
Quantitative data were provided from the post course survey. Qualitative data was
collected from open-ended questions, numbers 42-43) in the student post-course
evaluation survey, and from the online focus groups.
Research Design
Participants
The group in this study consisted of graduate students enrolled at a major
research university during the 2002-2003 academic year. The course had an
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51
enrollment of 25 students, 21 (84% response rate) were present when the post
course evaluation was administered.
The participants were adults with an estimated average age of 33.6 years old.
The majority of the participants were women. O f the participants surveyed, the
majority was single. Most participants had years of professional experience, and
were enrolled in this program for career advancement. A large percentage of the
participants were educators.
The online focus groups consisted of select students from the course being
studied. The focus groups were conducted after reviewing the post-course
questionnaire. The questions were guided by the five research questions in this
paper. The online focus groups took place in the class virtual chat room, one of the
features of the Blackboard instructional format. This researcher (see focus group
protocol in appendices) directed the online focus group question and answer session.
The printed dialogue of each of the focus groups was printed at the end of each
session.
Instrumentation
There were two types of data collection tools used in this study: a
questionnaire conducted onsite, and three online focus groups. The five page
questionnaire was developed by the researcher, and its content and structure were
guided by the five-research questions. The survey questionnaire was piloted, tested
and revised during the semester prior to its fall semester 2002 administration.
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52
Participants were asked to respond to 41 Likert type items that were divided
into 5 areas covering student demographics (see Appendix A), prior computer and
technological experience, prior educational experience, instructional format and the
use of Blackboard. The respective scores of questions 10-41 are given in the
following tables. In the case of all Likert type questions: 0= none, l=very low, 2=
low, 3= average, 4=high, and 5= very high.
Table 1 - Student’s Computer Skill and Prior Technological Experience
Items 10-15
Scoring 1
10. PRIOR TO THIS Numeric scores recorded as entered by foe i i
| CLASS your level of participant |
ii computer experience
11 PRIOR TO THIS Numeric scores recorded as entered by foe
i | CLASS your level of | participant |
i s Internet experience
:: 12. PRIOR TO THIS
ii: CLASS your level of | Numeric scores recorded as entered by foe | i |
i f experience in using | participant
i i electronic technologies to
i f communicate
13 PRIOR TO THIS Numeric scores recorded as entered by foe i|
i j CLASS, your level of participant |
i i exposure to Blackboard
i i 14. Importance you place Numeric scores recorded as entered by foe |
i | on training to access/use participant |
i i the required technolog} m
| this course.
ii
!| 15. The level to which |
Numeric scores recorded as entered by foe |
i i your computer competency $
i i affected academic i i
participant |
| | performance in this class. |
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53
Table 2 - Students’ Prior Distance Learning and Other Learning Experience
Items 16-21
j Item Scoring
; 16. PRIOR TO THIS
\ CLASS your level of | Numeric scores recorded as entered by the
\ exposure to online/ non- participant
\ traditional learning
5 17. PRIOR TO THIS
i ; CLASS your comfort level | Numeric scores recorded as entered by the
in an online instructional participant
j 18. AFTER TAKING |
I THIS CLASS your level of j :
; comfort in an online j ;
\ instructional setting. j :
lb The lc\cl in which
\ your prior experience in an |
| online setting affected the |
j educational outcome in |
i this course. \
i : 20. The importance you > :
j place on practice and non- |
| threatening learning |i
s opportunities provided |
\ before actual online course |
\ experience.
; 21. The importance you
1 place on clearly stated
j learning goals and
s objectives in an online
j environment.
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
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Table 3 - Instructional Format (e.g., modularization, pacing, etc.)
Items 22-35
122. The importance you
I place on activities being
; directly related to learning
; goals and objectives.
j 23. The importance you
j place on the use of design
I elements to engage the
j online student.
i 24. The level of importance
| you place on course structure
j that consistently reinforces
| learning.
Numeric scores recorded as entered by the
participant
: Numeric scores recorded as entered by the i
participant
Numeric scores recorded as entered by the
participant
j 25. The level of importance
i you place on online content
j divided into reasonably sized
j chunks.
Numeric scores recorded as entered by the
participant
j 26. The level of importance
j you place on the required
I interaction during each
j content module.
127. The importance you
i place on the schedule of
I benchmarks and assignments
\ that structure the pace of the
I course
ii28. The importance you
\ place on learner control.
Numeric scores recorded as entered by the j
participant
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
j 30. The importance of
I timeliness in which written
j assignments were graded and
1 returned.
Numeric scores recorded as entered by the ;
participant
j 31. The importance of
\ timeliness of instructor’s
; (e.g., email) response.
Numeric scores recorded as entered by the
participant
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Table 3 (con’t)
? 32. Level of importance of a , , , , ,, ,, :
;. 4 4 Numeric scores recorded as entered by the :
: instructor s overall 4 . . J
participant
I accessibility. 3
; 33. Level of importance of . , , ,,
4 4 , , , i Numeric scores recorded as entered by the ;
5 contacts between teacher and s : .. • :
. participant
i you the learner. %
34. Level of importance of 1 xr . , , ,, i
. , 4 4 4 4 n Numenc scores recorded as entered by the :
ctnnpnt_tr»_otn/r l^ n t J
| student-to-student
I interaction.
participant
: .35. Level of importance of | Numeric scores recorded as entered by the
I student collaboration. participant
Table 4 - The Instructors’ Selection of Blackboard Format
Items 36-41
; Item
5 36. AFTER THIS CLASS
1 your personal comfort
j level with Blackboard.
Scoring
Numenc scores recorded as entered by the
participant
137. The level to which the
i use of “Blackboard”
5 enhances the online
I academic experience.
\ 38. Level of ease of use of
[Blackboard.
; 39. The level to which use
\ of email positively affects
5 course outcome.
1 (Blackboard feature)
5 40. The level to which the
1 use of chat rooms
I enhances course outcome.
| (Blackboard feature)
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
V .' . V . V . V . W M ' . W . ' . W . V
Numeric scores recorded as entered by the
participant
Numeric scores recorded as entered by the
participant
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56
Table 4 (con’t)
| 41. The level to which the |
; use of discussion forums ^ Numeric scores recorded as entered by the I
enhanced the online | participant
experience. (Blackboard
feature
Data Collection Procedures
Questionnaire
Each questionnaire was personally distributed and collected from each o f the
21 of the 25 potential participants. All students attending the final class o f the course
being studied were represented. The return rate of completed questionnaires was
100% of those participants present on the final class meeting.
Focus Groups
Online focus groups were another assessment tool selected in this study. The
interview was guided by a structured question format. Focus group research was
conducted to gain a more complete understanding of a person’s motivations,
feelings, and ideas abut a topic (Krueger, 1998). The focus groups were conducted
to gain more information and a better understanding of the needs and characteristics
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57
of the adult distance learner. The impetus for creating these groups was to elicit
further clarification and elaboration of the information that emerged when reviewing
the questionnaire.
Bobrow (1997) describes focus groups as being descriptive, subjective,
explanatory and approximate. Research has shown that individuals tend to offer
their view more freely in a group than they do in a one-to-one situation, especially if
they are speaking with an individual with who they are not well acquainted (as was
the case with this researcher and the participant focus groups) (Morgan, 1993). The
questions designed for the focus groups were exploratory in nature. Using Krueger’s
(1998) format, each focus group had an opening, introductory, transition, key and
ending statements. Each focus group was conducted in a similar manner in to order
to insure consistency and uniformity of the questions and facilitation.
There were online focus groups (N=4 for each group), which took place the
week following the completion o f the post-course questionnaire. The focus groups
were held on three separate occasions: 12/05/02 from 7:22-8:23 pm, 12/09/02 from
6:57-7:05 (interviewer experienced computer problem) restarted on 7:20-8:04 pm
and on 12/09/02, from 8:08-9:03 pm. Immediately following each focus group, an
electronic copy of the session was generated from the class Blackboard archives.
Although the focus groups were initially mixed with male and female
participants due to attrition, the second group was made up of all females,
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58
and the last group was made up of all male participants. Reminder notices were
sent prior to each of the focus groups, but prior notification did not insure that all the
participants were present or on time.
The focus group protocol and research questions were designed prior to the
online meeting. At the onset of the focus group participants were made aware that
their responses were being recorded. The researcher had prior experience with online
focus groups.
Data Recording and Analysis
The data for the study were analyzed to address each of the seven research
questions. The survey data collected on the questionnaire were recorded on an Excel
spreadsheet (questions 1-41), and then transferred to the Statistical Package for the
Social Sciences (SPSS) 11.5 for statistical analysis. A number of rules were
established prior to the coding and entry data that maintained consistency o f scoring
and integrity of the data.
Descriptive statistics were obtained for each item and each subscale. A
Cronbach’s alpha was used to determine interterm reliability for each of the scores;
bivariate correlation was used to examine the correlation between age, gender, and
instrument scores.
Analysis of the focus group discussions included sequencing of questions and
coding of data. Data were also compared between focus groups. For each group,
N=4. This was done to identify patterns and make comparisons and contrast one
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59
group with another (Krueger, 1998). Responses of the participants in each group
were coded and analyzed from the printed notes generated at the end of each session.
Suggestions, ideas, and opinions from each group were compared with the other
groups.
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CHAPTER4
RESULTS
The chapter presents the results of the data collected from the responses to
the survey questionnaire presented to the target audience for the purpose of
identifying the characteristics and needs of the adult distance learner in a
predominantly asynchronous computer mediated communication teaching format.
The study gathered information through the use of a post-course questionnaire, and
online focus groups.
The overall objective of this study was to reveal the attributes of professional
graduate level distance learners in distance-leaming course. Gaining an
understanding of the demographic and other variables related to adult distance
learning can only aid in identifying and addressing issues, which can insure
academic success.
All the students in attendance (21) returned completed forms to the
researcher. The respondents comprised the sample group, and the information they
supplied provided the data for this study. Participants were asked to sign up for
online focus groups. One week after reviewing the data, three focus groups took
place.
Before discussing the research questions, it’s essential to determine the
reliability of the instrument used. For this reason, the reliability analysis is presented
first. Results of the descriptive statistics computations are then presented followed
by correlation analysis.
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61
Based on the descriptive, internal consistency measures and the results of
factor analysis, poor items were identified and removed, this resulting in reduced
number of items. In the prototype study, during the summer semester, items were
carefully eliminated so that there was no significant reduction in the reliability or
validity indices of each subscale.
The data were analyzed using two distinct methods. The first method
gathered all the survey responses to each question, with the exception of 42 and 43,
and the focus group data. The data were then entered on to an Excel spreadsheet and
then inputted on to a database to be examined for correlations, frequencies and
percentages. In addition to the statistics, frequency distribution for each of the
statements (except items 42 and 43), are displayed in the tables. The responses for
the open-ended questions 42 and 43, online focus groups and instructor records were
examined qualitatively, looking for commonality in responses and viable solutions to
student concerns.
The chapter is organized in the following four sections: descriptive statistics:
correlation, demographics, qualitative analysis, and summary.
Descriptive Statistics
The demographic findings in this study are almost consistent with the literature.
Again, according to National Center for Education Statistics (1997) in the United
States, the “typical” distance-leaming students are between the ages of 25 and 50. The
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findings specific to this study find the average age of the class to be 33.6 years
old, with a range of 24-54 years old.
Table 5 -Distribution of Age
Valid
Missing
Total
Frequency Percent Valid
Percent
Cumulative
Percent
24 2 9.5 10.0 10.0
26 3 14.3 15.0 25.0
27 2 9.5 10.0 35.0
28 1 4.8 5.0 40.0
29 1 4.8 5.0 45.0
30 1 4.8 5.0 50.0
31 14.3 15.0 65.0
32 1 4.8 5.0 70.0
36 1 4.8 5.0 75.0
44 1 4.8 5.0 80.0
47 1 4.8 5.0 85.0
48 1 4.8 5.0 90.0
50 1 4.8 5.0 95.0
54 1 4.8 5.0 100.0
Total 20 95.2 100.0
No 1 4.8
response
21 100.0
The majority of the respondents, 57.1% were women. So far the target
audience in this study has been found to be a majority of female students over the
age of 24 and with the average age of 33.6 years old.
Table 6 - Distribution of Gender
Frequency Percent Valid Cumulative
Percent Percent
Valid Male 9 42.9 42.9 42.9
Female 12 57.1 57.1 100.0
Total 21 100.0 100.0
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The only clear difference in this study as opposed to the literature was that
the majority of the participants were single.
Table 7 - Distribution of Marital Status
Frequency Percent Valid Cumulative
Percent Percent
Single 13 61.9 61.9 61.9
Married 8 38.1 38.1 100.0
Total 21 100.0 100.0
Most participants had professional experience, and were enrolled in this
program for career advancement. The large proportion of the participants, nine of
them, were teachers or in the education field (approximately 43%). The other
12 participants were employed as follows: 5 participants (approximately 24%) were
students, 2 were in the medical field (approximately 9%), 2 were self-employed
(approximately 9%), 2 were in various aspects of private industry, and 2 students
(approximately 9%) declined to answer.
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Table 8 - Distribution of Occupation
Frequency
Missing No 2
response
Valid Analyst 1
Ed. Adm. 1
Faculty 1
Lecturer 1
Nurse 1
Project 1
Director
Student 5
Systems 1
Admin.
Teacher 6
Writer 1
Total 21
Percent Valid Cumulative
Percent Percent
9.5 9.5 9.5
4.8 4.8 14.3
4.8 4.8 19.0
4.8 4.8 23.8
4.8 4.8 28.6
4.8 4.8 33.3
4.8 4.8 38.1
23.8 23.8 61.9
4.8 4.8 66.7
28.6 28.6 95.2
4.8 4.8 100.0
100.0 100.0
Many of the respondents, 14 of them, had jobs that were associated with
education (e.g., teachers, administrators, students, lecturer, etc.).
Table 9 - Distribution of Job Title
Frequency Percent Valid
Percent
Cumulative
Percent
Missing No 3 14.3 14.3 14.3
Response
Valid Admin. 1 4.8 4.8 19.0
Bilingual 1 4.8 4.8 23.8
Teacher
Director 1 4.8 4.8 28.6
Instructor 1 4.8 4.8 33.3
Inter 1 4.8 4.8 38.1
national
Analyst
MD 1 4.8 4.8 42.9
Senior 1 4.8 4.8 47.6
lecturer
Student 5 23.8 23.8 71.4
Teacher 5 23.8 23.8 95.2
Writer 1 4.8 4.8 100.0
Total 21 100.0 100.0
Total 21 100.0 100.0
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Of the participants surveyed, 95.2% were presently education majors.
Table 10 - Distribution of Present Major
Specialized
Area of
Education
Frequency Percent Valid
Percent
Cumulative
Percent
Valid Education:
Learning &
Instruction
8 38.1 38.1 42.9
Education:
Administration
3 14.3 14.3 57.1
Education;
Bilingual
1 4.8 4.8 61.9
Education:
Leadership
1 4.8 4.8 66.7
Education:
Policy
4 19.0 19.0 85.7
Education:
Counseling
1 4.8 4.8 90.5
Missing No response 2 9.6 9.6 95.2
Undecided
Total
1
21
4.8
100.0
4.8
100.0
100.0
Only 38% of the participants had initially chosen education as their prior major.
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Table of 11 - Distribution of Past Major
Valid
Frequency Percent Valid
Percent
Cumulative
Percent
No response 2 9.5 9.5 9.5
Business 1 4.8 4.8 14.3
Economics 1 4.8 4.8 19.0
Education 33.3 33.3 52.4
Engineering. 1 4.8 4.8 57.1
Humanities 1 4.8 4.8 61.9
Information.
Systems
1 4.8 4.8 66.7
Lang. 1 4.8 4.8 71.4
Medicine 1 4.8 4.8 76.2
Management 1 4.8 4.8 81.0
Political
Science
1 4.8 4.8 85.7
Psych. 1 4.8 4.8 90.5
Public Health 1 4.8 4.8 95.2
Physical Ed. 1 4.8 4.8 100.0
Total 21 100.0 100.0
The class standing calculated as follows: 66.7% Ed.D. students, 23.8%
Masters students, 4.8 were unspecified and 4.8 % declined to answer.
Table 12 - Distribution of Class Standing
Frequency Percent Valid Cumulative
Percent Percent
Valid Masters 5 23.8 25.0 25.0
Ed.D 14 66.7 70.0 95.0
Other 1 4.8 5.0 100.0
Total 20 95.2 100.0
Missing No response 1 4.8
Total 21 100.0
Total 21 100.0
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Many researchers have attempted to explore the myriad of variables in
distance education, including student demographics, motivation, cognitive styles,
gender, achievement, and learning styles (Biner, 1995; Bork, 1997; Diaz & Cartnal,
1999; Dominguez; 1999; Gee, 1990; Honey, 2001; Matthews, 1999). Numerous
studies have been conducted to explore the comparative effectiveness of distance and
traditionally delivered instruction (Jeffries, 1995; Keegan, 1996; Khan, 1997; King,
Hamer & Brown, 2000; Lowery, 1995; Phipps & Merisotis, 1999; Porter, 1997;
Rossman & Rossman, 1995; Valenta, Therriault, Dieter & Mrtek, 2001; Verduin &
Clark, 1991; Willis, 1994). Thompson (1990) reviewed a variety of the research
findings from the 1980s through 1990s and concluded that “distance delivered
instruction could be as effective as traditional learning if the delivery methods
selected were based on the appropriateness of the content being delivered, cognitive
style of the learner, and background and experience level of the student” (p. 82).
Phipps and Merisotis (1999) claimed, “There is wide variance of achievement and
attitudes within the groups, which indicates that learners have a variety of different
characteristics. The factors influencing these differences could include gender, age,
educational experience, motivation, and others” (p. 5). They also emphasized that
further research needed to focus on how individuals leam, rather than on how groups
leam. Wentling, Waight, Gallaher, Fleur, Wang and Kanfer (2000) had a similar
advocacy, “Clearly the effective learner is the person who adapted his or her learning
style to the demands of the situation. Very few studies have examined this issue” (p.
15). Wentling and his associates suggested that learning style was clearly affected by
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factors within the technology-rich environment. Learners’ perceptions about the
characteristics of instructional delivery media and their ability to leam using these
media had been shown to be key determinants in predicting student motivation and
success in distance education courses (Coggins, 1988; Gee, 1990).
Although some researchers (Keegan, 1986) believe that descriptive findings
regarding demographics of distance education students provide information about
who participates in distance education, they also note that such studies alone cannot
disclose what factors are related to educational outcomes of distance education
participants. But this research has demonstrated that by identifying the
characteristics and needs of the adult distance learner can only improve and enrich
the success of these students.
Reliability Analysis
In order to evaluate the research questions, it was first necessary to create an
index in which to analyze the data. The research questions were divided into the
following areas: items 1-9 demographics, items 10-15 (AlphaRQ2) prior computer
skills and experience, items 16-21 (AlphaRQ3) prior learning and distance learning
experience, items 22-38 (AlphaRQ4) instructional format (e.g., pacing and modules)
and items 39-41 (AlphaRQ5) Blackboard instructional format (questions 42 and 43
were open ended, and scored qualitatively).
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Figure 1 - Reliability Coefficients (Alpha) Scores for RQ2-RQ5
GROUPS AREA OF STUDY ITEMS NUMBER OF
ITEMS
ALPHA SCORE
RQ2 Prior Technology Experience 10-15 N = 6 .4889
RQ3 Prior Learning Experience 16-20 N=5 .7648
RQ4 Instructional Format 21-36 N=16 .8373
RQ5 Use of Blackboard 37-41 N=5 .7896
The results indicate that, except for the questions on Prior Technology
Experience (RQ2), there was high reliability of the instrument of each of the survey
sections.
Correlation Analysis
Correlation analysis was run on all items (see Appendix 3) but significant
correlation at the 0.05 level (2 tailed) were discovered only among RQ2, or the items
16-21, on prior learning and distance learning, and gender and marital status.
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Table 13 - Correlations
RQ3 Gender Marital Status
RQ3 Pearson
Correlation
1.000 -.502 -.308
Sig. (2-tailed) . .020 .175
N 21 21 21
Gender Pearson
Correlation
-.502 1.000 .481
Sig. (2-tailed) .020 . .027
N 21 21 21
Marital Pearson -.308 .481 1.000
Status Correlation
Sig. (2-tailed) .175 .027 .
N 21 21 21
* Correlation is significant at the 0.05 level (2-tailed).
Qualitative Analysis
After reviewing the quantitative part of this study, this researcher believed
that much could be gleaned from a qualitative review of the data. Data were
gathered from questions 42 and 43 of the post-course questionnaire, the online focus
groups, and information taken from the standard university evaluation report.
A review of survey questions 42 and 43, which related to the instructor’s
selection of the Blackboard instructional format, provided the area of the data for the
qualitative analysis. Question 42 asks what attributes of Blackboard did you find
most useful in affecting a positive distance learning experience? Question 43 asks
what pitfalls? if any? Did you encounter using Blackboard?
Students’ felt there were far more attributes than pitfalls to using the
Blackboard format. The respondents, when describing this instructional format, used
words like accessibility, convenience, and flexibility. Most students felt it was easy
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to navigate, and was well organized. Some students felt that Blackboard
facilitated them keeping up with assignments more easily, and they also appreciated
seeing the progression of the modularized assignments online. Many liked the idea of
seeing the direction of the class, and skipped ahead to see what was expected of them
over the time of the course. Some students stated they felt more connected to the
instructor, their peers and to the course itself because of the Blackboard instructional
format.
The majority of negative issues stated, in regard to Blackboard, were
technical concerns, for instance the server was down, or it took a week to get a
password, or that it was hard to print back to back, which had little to do with the
Blackboard instructional format itself. There were a few students that didn’t know
how to post work or utilize the chat room and felt they needed to know more about
the functionality of Blackboard. The overall concern here was more in regard to
their technical skills than the instructors’ selection of Blackboard. When asked,
“why didn’t you ask the instructor how to post work?” The student remarked that she
did not want to bother him. This female student’s reticence to ask for help was the
issue here, she still was positive about the use of Blackboard in this course. The
online focus group data was in agreement with the findings in questions 42-43 but
expounded upon the information presented (see online focus group section).
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Figure 2- Summary of Responses to Opened-ended Questions 42 and 43
Positive Attributes of Blackboard Pitfalls of Blackboard
Accessibility to documents Hard to post work (did not want to bother
the professor”)
Accessibility to the Instructor
Accessibility to peers Went down several times
Accessibility to other students work Not able to see other students’ grades
Accessibility to information Needed more references to websites
relating to content areas
Convenience Long time to download files-needed to be
in pfd form
Convenience to email addresses Took over a week to get password sent
Work at own pace Could not print back to back
Communication with proof Needed to know about all the functions of
Blackboard
Flexibility Went down several times
Well organized in general Organization of materials needed to be
clearer
Well organized in terms of goals
Easy to navigate Interface issues navigating Blackboard
site.
Central place to access assignments
and materials
Easy to keep up on weekly
assignment and materials
Information not current
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Online Focus Groups
The three online focus groups allowed for a more in depth treatment of the 7
questions examined in this paper. O f those interviewed 50% were women and 50%
were men, 83% of the participants were in the Ed.D program and 17% were in the
Masters program, in education. O f those that participated in the focus groups, 83%
had prior computer experience and 17% did not but stated, “it was easily picked up,
67% of the participants had prior distance education experience, and 33% did not.
All the students, except for one female student, expressed their satisfaction with this
type of format and would take another course of this kind. This female student said
she would not purposely pick an online class, she was the same student who initially
had some trepidations over the technology used in the course.
All the students were pleased with the instructional design; they found the
class to be systematic and well organized. They appreciated the prompt feedback
since most mentioned they did miss the face-to-face interaction of a more traditional
classroom. But then again, they enjoyed the freedom and flexibility that is part of
the distance education format. They also remarked about the connectivity and
structured of the modules and how the final projected tied all the modules together of
them.
When discussing the Blackboard instructional format, the students were
positive in their remarks. They liked the freedom and flexibility of this format. They
found the site easy to navigate. The words “phenomenal” and “exciting” were used
by one of the male doctoral students to describe his experience with Blackboard.
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There were no real negatives cited by these groups, only one student mentioned
unclear due dates. The students appreciated the instructor’s choice o f Blackboard-
they felt it added to the success of the class. Almost every student interview
mentioned they missed facto face interaction, and Blackboard helps students feel in
touch with the other students, the instructor and the course itself.
Summary
In terms of the research questions, the following may be reported.
What are the identified student demographics, including the variables of age, family
status, gender, employment and educational status in a predominately asynchronous
computer mediated communications teaching format course?
Distance learning is student-centered and knowing the characteristics and
demographics of the distance learners enables educators to build on student strengths
and avoid potential barriers to learning. Knowing students' characteristics may not
guarantee success but may contribute to it. Additionally, knowing the specific
student characteristics and motivators may give a clearer understanding of who is
likely to participate in distance education.
Knowles (1980), postulating on the advantages of knowing the learner, stated
that learner behavior was influenced by a combination of the learner's needs plus the
learner's situation and personal characteristics. Knowing the student population
may help drive program planning, a key factor in participation and success in
distance learning.
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The demographic data collected in this one course study closely paralleled
the information found in the literature. The literature did provide a profile for the
“typical” distance learner but on the whole they are an extremely diverse group.
The average age of the students’ in the study was 33.6 years old. The
majority of the participants were women, (57.1%) and single. Most of the
participants, at least 76.2% of those surveyed were full time employees, with
professional experience. Married or single with a full time job, and a multitude of
adult responsibilities makes attending school even more of a challenge, and should
be duly noted by distance educators
At least 66.7% of the participants were teachers or associated with the field
of education. The majority of the participants, 95.2% were education majors
enrolled in this course and program for career advancement. This information
indicates student motivation and experience level, thus giving the instructor vital
information which may help to insure course success. The findings in this study
have provided valuable information and can help guide further study, the size and the
homogeneity of the participants need to taken into consideration.
What are the identified student characteristics, including computer skills and prior
experience with technology, prior distance learning and other learning experiences,
in a predominately asynchronous computer mediated communications teaching
format course?
No significance was found in the quantitative and minimal significance in the
qualitative data, thus suggesting that prior technological experience did not affect the
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students’ ability to leam or complete the course. The literature does site that these
variables do have significance and the distance educator does need to be aware that
they might impinge on the successful outcome of an online course. The data in this
study was based on graduate students and cannot be generalized due to the small and
limited number of respondents.
There was a significant correlation between prior learning and distance
learning and gender and marital status. Qualitative analysis found that 80% of all
those surveyed had prior experience. O f those respondents that had indicated they
had no prior learning experience, 20% said that having that experience would have
enhanced their distance learning experience. Quantitative analysis found
significance in the area of prior learning and distance learning experience.
What are the students’ reaction to the type of instmctional format, and use of
Blackboard in a predominately asynchronous computer mediated communications
teaching format course?
Both the qualitative and qualitative data in this study found that instmctional
format strongly related to the outcome of an adult distance learning class, and the
selection of Blackboard was an integral part of the format. The inclusion of
structured activities, such as timelines, deadlines and feedback not only motivated
students but also offered them the framework to function in a flexible environment.
All the students surveyed expressed the importance of feedback; the
Blackboard instmctional format provided them with a stronger sense of
connectedness with the class format, the other students, and the instructor.
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All the students surveyed expressed the importance of feedback; the
Blackboard instructional format provided them with a stronger sense of
connectedness with the class format, the other students, and the instructor.
What is the relationship of student demographics to students’ computer skills and
prior experience with technology in a predominately asynchronous computer
mediated communications teaching format course?
No significant correlation was discovered. There was no statistical difference
encountered in the data. Here again the literature most be considered due to the
limited number of respondents. This suggestion does not diminish the importance of
the data collected but suggests further studies on the factors that affect the adult
distance learner.
What is the relationship of student demographics to prior learning and other learning
experiences in a predominately asynchronous computer mediated communications
teaching format course?
A significant correlation was discovered between prior learning and distance
learning and gender and marital status. The quantitative data in this study indicated
there was a correlation between prior learning and gender and prior learning and
marital status. The literature conversely indicates that the significance in this case
was only statistical. The differences between the data and the literature suggest this
is an area of distance learning that would benefit from further research.
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What is the relationship of student demographics to type of instructional format
(pacing and use of instructional modules)in a predominately asynchronous computer
mediated communications teaching format course?
No significant correlation was discovered, there was no statistical difference
but again the literature indicated there was a significant. Since there was a disparity
between the literature and the data compiled in this one course study
there is the indication for further study and consideration in this area of distance
learning.
What are students’ reactions to the instructor’s selection of the Blackboard
Course Management System ('CMS') with its format and features for the
mediated communications teaching format course?
No significant correlation was discovered in the data. The open ended
questions in the survey indicated that there was favorable reaction to the instructors
choice o f Blackboard. The majority of the students felt that it enhanced their
learning experience and allowed them freedom to work when convenient and made
them feel that they had accessibility to the instructor. Further study into the use of
course based management systems, and specifically Blackboard may be
advantageous to the distance learner and educator.
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CHAPTER 5
FINDINGS, CONCLUSIONS AND IMPLICATIONS FOR FUTURE RESEARCH
Summary
The rapid technological changes in the last decade especially the fast
proliferation in the use of the Internet and the World Wide Web have indeed
transformed the way we live, work communicate, and leam. Adult learners are
becoming higher education’s new majority, with different needs than traditional
students (Bane & Lear, 1994). Many believe that technology has the potential to
enhance the teaching and learning process as well as create new delivery modes
(King, 1995). Within colleges and universities, continuing higher education is one
area preparing to meet the growing demand for higher education (Kohl, 1998;
Walshok, 1998). The evolution of new information and communication technology
is contributing to the need for continued learning as well as creating new tools and
resources for learning (Partnership Roundtable, 1998).
This is especially true in California where this study took place The
California State University (CSU) have made major strides towards implementing
online education. In 2001-2002 CSU have doubled over a three year period the
number of course selections requiring use of web based technologies as have the
number of students enrolled in web assisted courses and the number of faculty
teaching them. In 2000, faculty reported that 48% of the classes taught required use
of the Internet by 2002, that percentage had increased to 61%. Almost all the
campuses (20 of 22) report that they have established a central faculty for
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instructional technology development. (Measures of Success, Nov. 2002). Lou
Zweier, director of the California State Universities Center for Distributed Learning
echoes the very concerns addressed in this study state, “Faculty and staff who are on
the cutting edge of applying new technologies to teaching and learning process need
support for their efforts.” The importance of knowing the needs and attributes of the
distance learner is being recognized not only in California but worldwide.
There is the widespread observation among distance education researchers
that the majority of students taking course by distance education are adult learners.
The distance education literature confirms this view of distance education students as
adult learners (e.g., Bates, 1989; Coldeway, 1986; Courtney, 1992; Hardy & Olcott,
1995; Holmberg, 1995; Thompson, 1989; van Enckevort, 1986). The principles and
rationale of higher distance education are essentially those of adult education. Adults
are the primary audience we serve and the methods we have adopted have
historically respected the voluntariness of adult learning. (Garrison & Shale, 1990).
The writings of adult learning theorists (e.g., Knowles, Knox, Coldeway & Keegan)
provide frameworks, which can be utilized in trying to comprehend the potential
relationships between distance learner characteristics and the outcomes of learning
experiences. “Most distance education is concerned with the education of adults and
it seems fairly obvious that our research plans should be informed by the theories
and research about learning in adulthood, adult development, program planning,
instruction and evaluation in adult education” (Moore, 1985).
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To further develop a theoretical base of understanding in distance
education, data on participants should be linked to other variables, (e.g.,
demographic data). The literature illuminates significant demographic differences
existing between traditional and nontraditional students served by colleges and
universities. Comparisons of distance and conventional students can provide useful
information about participation especially regarding participants’ time constraints
and personal learning preferences. Because of the differences in age, sex, college
classification, marital status, and enrollment status, it would be wrong to treat both
populations in similar ways (Leverenz, 1981). The literature does confirm the long
standing view that distance learners are predominately adults who are pursuing a
university education on a part-time basis (Holmberg, 1995; Jevons, 1990).
Demographic studies, on the distance learner, tend to indicate that most
distance learners are adults looking to return to school after an absence or to obtain a
credential useful in furthering their careers. Increasing numbers of distance learners
are also elderly, minority, disabled and/or English-as-a-second-language students.
Studies of distance education student demographics (National Center for Education
Statistics, 1998) indicate that a majority (approximately 75%) of adult distance
learners are female, are older than traditional students, and live more than 51 miles
from the originating campus (Thompson, 1997). In addition, they may have family
and work responsibilities that cause them to leam differently, perform differently,
and have different perceptions and expectations about the courses they take than
traditional students (Sheets, 1992).
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Understanding the attributes and concerns of the adult distance learner,
their reasons for involvement in distance education, and the outcomes of their
participation is essential, not only to explain and predict the participation event itself
but also to determine consequences related to program planning, learning activities,
program evaluation and all the other aspects involved in this mode of learning and
teaching. Before educators can determine how best to serve the adult distance
learner, it is essential to know more about this population and the likelihood for their
success in pursuing distance education.
The intent of this study was to examine the process and students’ actual
experiences with distance learning in order to assess and enhance all aspects of adult
distance learning. The importance of individual characteristics and needs of the
adult distance learner may be observed in a model of distance education proposed by
Coldeway and Associates (1986). In Coldeway’s model, and in this paper, success is
a function of the combination of four factors: personal characteristics, including
contextual factors of background and experience; motivations for enrollment;
institutional factors, such as pacing requirements and delivery method; and course
factors, including course design and delivery. Using Coldeway’s model, success can
be measured in one of two ways, either determined by students’ persistence in a
course or measured according to individual growth and development. Although
students’ characteristics and needs may not account completely for success in a
distance learning education course, according to Coldeway’s (1986) model, it is
possible that these factors contribute to success.
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The overall objective of this study was to reveal the attributes of
professional graduate level distance learners in distance-learning courses. This goal
was accomplished qualitatively and quantitatively. Individual responses to a
questionnaire were recorded, and online focus groups were analyzed and the data
were coded to identify patterns and make comparisons. Students were interviewed in
focus groups, as to their experience with technology, distance learning, instructional
format and the instructors’ selection of Blackboard.
The study was guided by seven research questions:
1. What are the identified student demographics, including the variables
of age, family status, gender, employment and educational status in a
predominately asynchronous computer mediated communications
teaching format course?
2. What are the identified student characteristics, including computer
skills and prior experience with technology, prior distance learning
and other learning experiences, in a predominately asynchronous
computer mediated communications teaching format course?
3. What are the students’ reaction to the type of instructional format, and
use of Blackboard in a predominately asynchronous computer
mediated communications teaching format course?
4. What is the relationship of student demographics to students’
computer skills and prior experience with technology in a
predominately asynchronous computer mediated communications
teaching format course?
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5. What is the relationship of student demographics to prior learning
and other learning experiences in a predominately asynchronous
computer mediated communications teaching format course?
6. What is the relationship of student demographics to type of
instructional format (pacing and use of instructional modules)
in a predominately asynchronous computer mediated
communications teaching format course?
7. What are students’ reactions to the instructor’s selection of the
Blackboard Course Management System (CMS) with its format and
features for the mediated communications teaching format course?
This was a descriptive research study, which identified the characteristics and
needs of the adult distance learner in a predominantly asynchronous computer
mediated communication-teaching format.
The setting of the study was a major research university located in Southern
California. The data were compared from three sources, which enabled the
researcher to gather data from a subset of a population, summarize the data and draw
inferences about the sample to a defined population.
The sample consisted of 21 graduate students, who were predominantly
traditional learners, over the age of 24. This was a homogeneous group, although
individual computer competency levels varied. The sample studied was enrolled in a
distance-learning course that incorporates a predominantly asynchronous university-
supported Blackboard course management system as the vehicle.
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85
An extensive review of the literature was utilized when developing the
post-course questionnaire. The design implementation and analysis was directed by
a pronounced review of current distance education literature. The review of the
selected literature help to guide the structure, content, scope and purpose of each area
of distance education to be investigated.
The post-course questionnaire was the first data collection tool utilized in the
study and it consisted of five sections: 1) demographics, 2) prior computer and
technological experience, 3) prior learning and distance learning experience,
4) instructional format and 5) the use of Blackboard.
Data from the post course questionnaire were analyzed to address the
aforementioned areas. Data from the questionnaire were entered onto an Excel
spreadsheet and then inputted into the Statistical Package for the Social Sciences
(SPSS) Version 11.5, for statistical analysis to be examined for correlations,
frequencies and percentages. In addition to the statistics, frequency distributions
were calculated for each of the statements on the questionnaire except 42 and 43,
which were open-ended
After the data from the questionnaire were reviewed, three online focus
groups were conducted. The focus group discussion touched on all the areas in the
questionnaire and expounded upon each issue. Data from the online focus groups
were analyzed and compared with the post-course questionnaire. Many
characteristics and needs of the adult distance learner were identified which allowed
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86
this researcher to postulate a number of conclusions and suggested implications as
a result of the data analysis.
Descriptive statistics were realized for each item and each subscale. A
Cronbach’s alpha was used to determine interterm reliability for each of the score:
bivariate correlation was used to examine the correlation between age, gender, and
instrument scores. Older students have been found to have higher course completion
rates (Rekkedal, 1983) as well as higher degree completion rates in graduate
programs (Lagenbach & Korhonen, 1988).
Although the numbers indicated a statistical correlation between prior learning
and the effect of gender, the only clear pattern, established in the data, was a greater
success rate for women in distance learning experiences. However, Carr and
Ledwith (1980, cited in Cookson, 1989) found that the course dropout rate of
housewives was less than half the overall rate, while the attrition rate for those who
listed manual trades as an occupation was 50% higher than the overall rate, possibly
indicating that gender and/or marital status have some significance. Among other
demographic variables, both gender and marital status have been found to be
insignificant in persistence studies (Langenbach & Korhonen, 1988; Langenbach &
Korhonen, 1986, cited by Coggins, 1988; Coggins, 1988). Lin and Chen (2000) in
their study found that with regard to sex (gender) there was no significant difference.
They also discovered that sex, marital status and semester scores did not affect
learning performance. This research study as well, demonstrated no clear
relationship between gender and prior experience, and marital status and gender,
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87
which led this researcher to believe that gender differences are statistically
significant but are of little or no consequence when compared with differences
between individuals. Further study in regard to the relationship between gender and
prior experience, and marital status and gender might be considered in future study.
When investigating the affect of students’ computer skills and prior
experience with technology no real significance was indicated. The majority of the
student’s interviewed indicated that the more they used the computer, the more
comfortable they became, and their initial lack of prior experience did not impede
their academic progress. Only one female focus group participant had any concerns
over her lack of computer experience, which she overcame and completed the course
successfully. Although prior experience in other aspects of distance learning may be
meaningful (see below), computer inexperience was not a serious deterrent or barrier
for the adult distance learner.
Keef (1992) reported that prior academic performance is a good indicator of
pass rates at a university. He further suggested that success in secondary education
is a good predictor of success tertiary education. Educational level prior to
enrollment in a distance course or program has been found to be significantly related
to persistence (Coggins, 1988; Lange Bach & Korhonen, 1986, cited by Coggins,
1988; Rekkedal, 1983), as has length of time since last educational enrollment
(Coggins, 1988; Rekkedal, 1983). Learners having high prior academic achievement
and recent educational experience may be more likely to persist because they have
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88
become "lifelong learners" who are accustomed to devoting and allotting their
time to educational activities.
The exploration of students’ prior distance learning and other learning
experiences, and its affect on the outcome of an adult learners’ performance, in both
the quantitative and qualitative analysis, a significant correlation was indicated. The
literature substantiates the findings that students who have had prior experience with
nontraditional education were more likely to persist than those with exclusively
conventional experience (Coldeway & Spencer, 1980, cited in Coldeway, 1986;
Lange Bach Korhonen, 1988; Rekkedal, 1983). The qualitative analysis found that
80% of those surveyed had prior experience but the of 20% who had no prior
experience said yes it made “somewhat” of a difference.
The qualitatively and qualitatively data in this study strongly reflects
Coldeway’s 1986 findings that “institutional pacing and delivery factors have a high
correlation with success.” The majority of participant’s felt that the instructional
format (e.g., pacing of assignments and use of instructional modules) was directly
related to the outcome of their distance learning experience.
Each student in the course and focus group felt that the structure was integral
to course success. The comments were as follows: “the structure was very helpful,
“clear and responsive,” “systematic and well organized,” “connected and structured”
and that the final project “tied it all together.” Planning for the introduction of a
major innovation like instructional technology is further assisted by organizational
concerns (Bandura, 1991).
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89
Another area of extreme import relation to instructional format is
student-teacher interaction. There is a plethora of literature attesting to the
importance of learner-instructor interaction. Case in point, Rekkedal (1983)
performed two experimental studies regarding interaction, which had significant
results. In one study, students who were mailed encouraging post cards and letters
following their failure to submit assignments responded at a rate o f 46%, versus a
31% response rate for the control group. In a second study, assignments of the
experimental group were graded by an onsite tutor; accordingly, turnaround times
were a median of 5.6 days, versus the 8.3-day median for the control group. Because
of the decreased turnaround times, completion rates in the experimental group were
91%, while the rate of completion in the control group was only 69%. All the
literature on instructor-student interaction stressed its importance and its affect on
student satisfaction, and course outcome.
The research data acquired in this study, quantitatively and qualitatively,
specified that the selection of Blackboard did affect the distance-learning course
studied. All the students survey expressed the importance of feedback, 80% of the
online focus group said they missed the personal interaction but many said the
convenience made up for it. Blackboard instructional format was described as
flexible, easy to navigate, comfortable and student’s felt they always knew what was
expected of them.
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90
The findings in this study suggest further investigation is warranted in
each of the areas examined. However, it is important to determine the relevant
questions for research. Future descriptive studies perhaps should focus on personal
and situational factors that go beyond the traditional questions of gender, age, and
educational background, and explore number of children and native language as
well.
There were also questions raised that were left unanswered. For example,
is student-learning style a pertinent variable in terms of outcome? What part does
self- regulation and motivation play in the success of distance learning? What other
factors (e.g., environmental, emotional, institutional) account for significant
variances in the outcome of an adult distance learning course? What defines
outcome?
Due to the limited sample in the present study duplication of the study with a
larger sample population is recommended. A larger population means not only more
participants but also possibly extending the sample outside the education major.
Although this study is important for a multitude of reasons, its sample was small and
limited. It would be advantageous to look a distance learning from a broader
perspective, possible nonhomogenous groups and in a variety of courses.
Thirdly, there is a need for additional investigations using different research
approaches or varied experimental designs. This study used a post-course survey
questionnaire possible future studies might entertain using a pre- and post-course
questionnaire.
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91
Conclusion
As computers continue to proliferate the classroom and home, the more
important it becomes to address the concomitant problems concerned with computer-
based learning. It is essential to recognize that social cognitive theory has provided
a valuable mode for discussing adult learning styles and preferences, motivation and
self-regulation in a distance-learning environment. In recognizing the importance of
considering social cognitive theory in distance learning provides an opportunity for
instructors to improve assignments, better define objective and enhance goal-setting
techniques.
Given the popularity ( to education, the military, private sector, etc.) and
benefits of distance learning, there is a necessity to strive for continued effectiveness
and efficiency. As evidenced by the data quality distance learning courses can make
a difference in outcome and performance. Although much research has been
conducted, there are a plethora of variables (technology, student and instructor
abilities, demographics, etc.) to consider in distance education. Impediments to
teaching and learning at a distance can be situational, epistemological, philosophical,
psychological, pedagogical, technical, social, and/or cultural (e.g., Espinoza et. al.,
1996; Kaye & Rumble, 1991; Lewis & Romiszowski, 1996; Sherritt, 1992;
Shklanaka, 1990; Spodick, 1996). What factors are perceived as influential may
also be influenced by the level of expertise the individual has regarding distance
education (Burge, 1998). There is a need for continued research to study current and
potential concerns in distance education.
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92
Distance education opens the door to many students, whose age; physical
disabilities, family obligations, or geographic location might otherwise have
prevented them from having a chance to further their education and/or careers.
Obviously, distance education has a multitude of benefits but it is essential to
continue to look for ways to increase its capabilities and by identifying the
characteristics and needs of the adult distance learn was a substantial step toward that
goal.
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93
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107
APPENDICES
Appendix 1
Questionnaire
STUDENT POST-COURSE EVALUATION SURVEY
UNIVERSITY OF SOUTHERN CALIFORNIA
EDPT 576 -Technology in Contemporary Education and Training
FALL 2002
Personal Information (PLEASE ANSWER THE FOLLOWING QUESTIONS BY
COMPLETING OR CHECKING THE APPROPRIATE INFORMATION)
1. Age:____
2. Gender: Male Female___
3. Marital Status: Single Married____
4. Occupation__________________ (If applicable)
5. Job Title__________________
6. Present Major______________
7. Past M ajor(s)___________________________ (In undergraduate and
graduate school)
8. # of units of units completed towards your present degree
(approximate)
9. Class Standing: Undergraduate Masters Ed.D PhD___
Other (e.g., employment related)
Self-Assessment (Please place an “X” in the box, to the right of the item that best
represents your opinion or response).
None Very Low
10. PRIOR TO THIS CLASS
your level o f computer
experience (e.g. using word
processing, spread- sheets,
etc.).
11. PRIOR TO THIS CLASS
! J your level o f Internet |
; experience, (e.g. searching the ;
web).
12. PRIOR TO THIS CLASS
your level o f experience in
: using electronic
technologies to communicate, ; :
e.g. using email, chat rooms, ’
etc.)
Low Average High Very High
R eproduced with permission of the copyright owner. Further reproduction prohibited without permission.
13. PRIOR TO THIS CLASS,
your level o f exposure to
Black-board.
14. Importance you place on
training to access/use the
required technology in this
course.
15. The level to which your
computer
competency affected
academic performance in this
class.
16. PRIOR TO THIS CLASS
your level of exposure to
online/ non-traditional
learning.
17. PRIOR TO THIS CLASS
your comfort level in an
online instructional setting.
18. AFTER TAKING THIS
j ’ CLASS your level o f comfort ij jj jj
in an online instructional i
setting.
19. The level in which your
prior experience in an online j '
setting affected the
educational outcome in this ‘
course.
20. The importance you place
on practice and non
threatening learning
opportunities provided before
actual online course
experience.
j 21. The importance you place
on clearly stated learning
goals and objectives in an
online environment.
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22. The importance you place
on activities being directly
related to learning goals and
objectives.
23. The importance you place
on the use o f design elements
to engage the online student.
24. The level o f importance
you place on course structure
that consistently reinforces
learning.
25. The level o f importance
you place on online content
divided into reasonably sized
chunks.
26. The level o f importance
you place on the required
interaction during each
content module.
27. The importance you place j
on the schedule of
benchmarks and assignments
that structure the pace o f the j;
course.
28. The importance you place
on learner control.
29.The import you place on
flexibility in an online course.
30. The importance of
timeliness in which written
j i assignments were graded and i . |
returned. ; ■ > ■ j
31. The importance of
timeliness o f instructor’s
(e.g., email) response.
32. Level o f importance o f ;
instructor’s overall
j accessibility. \ !
33. Level o f importance o f ; .
j contacts between teacher and || j j
you the learner. j ; !
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110
34. Level o f importance of
student to student interaction
35. Level o f importance of
student collaboration.
36. AFTER THIS CLASS
your personal comfort level
with Blackboard.
37. Level to which the use of
“Blackboard” enhances the
online academic experience.
38. Level o f ease o f use of
Blackboard.
39. The level to which use of
email
positively affects course
s outcome. >
(Blackboard feature)
40. The level to which the use ‘
of chat rooms enhances
course outcome. (Blackboard
feature)
41. The level to which the use
o f discussion forums
i; enhanced the online > jf
i : experience. (Blackboard i t i j I f i ! | |
feature). . : • ! l
Open Ended Questions
42. What attributes of Blackboard did you find most useful in affecting a
positive distance learning experience?
43. What pitfalls, if any, did you encounter using Blackboard?
R eproduced with permission of the copyright owner. Further reproduction prohibited without permission.
I l l
Independent S am ples Test
Appendix 2
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Marital
Status
Equal
variances
assumed
13.152 .002 -2.393 19 .027 -.47 .20 -.89 -5.92E-02
Equal
variances
not
assumed
-2.545 18.699 .020 -.47 .19 -.86 -8.34E-02
Class
Standin
g
Equal
variances
assumed
.296 .593 .809 18 .429 .25 .31 -.40 .90
Equal
variances
not
assumed
.709 9.255 .496 .25 .36 -.54 1.04
Prior
compute
r
Equal
variances
assumed
.001 .972 2.330 19 .031 .78 .33 7.91 E-02 1.48
Equal
variances
not
assumed
2.354 18.002 .030 .78 .33 8.37E-02 1.47
Prior
Internet
Equal
variances
assumed
.607 .445 2.947 19 .008 .89 .30 .26 1.52
Equal
variances
not
assumed
3.116 18.865 .006 .89 .29 .29 1.49
E-mail
Equal
variances
assumed
.411 .529 3.069 19 .006 .97 .32 .31 1.64
Equal
variances
not
assumed
3.126 18.396 .006 .97 .31 .32 1.62
Black
board
Equal
variances
assumed
.006 .941 -.037 19 .971 -2.78E-02 .76 -1.61 1.55
Equal
variances
not
assumed
-.037 17.598 .971 -2.78E-02 .75 -1.61 1.56
Impor
tance of
Equal
variances
.232 .635 -1.212 19 .240 -.64 .53 -1.74 .46
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112
training assumed
Equal
variances
not
assumed
-1.167 14.646 .262 -.64 .55 -1.81 .53
53
Q15
Equal
variances
assumed
.460 .506 .313 19 .758 .17 .53 -.95 1.28
Equal
variances
not
assumed
.327 18.997 .747 .17 .51 -.90 1.23
Q16
Equal
variances
assumed
.290 .597 1.144 19 .267 .81 .70 -.67 2.28
Equal
variances
not
assumed
1.150 17.724 .265 .81 .70 -.67 2.28
Q17
Equal
variances
assumed
.923 .349 2.394 19 .027 1.53 .64 .19 2.86
Equal
variances
not
assumed
2.496 18.996 .022 1.53 .61 .25 2.81
Q18
Equal
variances
assumed
2.020 .171 2.138 19 .046 .89 .42 1.87E-02 1.76
Equal
variances
not
assumed
2.261 18.865 .036 .89 .39 6.55E-02 1.71
Q19
Equal
variances
assumed
.821 .376 1.845 19 .081 1.22 .66 -.16 2.61
Equal
variances
not
assumed
1.870 18.160 .078 1.22 .65 -.15 2.59
Q20
Equal
variances
assumed
.109 .745 1.199 19 .245 .50 .42 -.37 1.37
Equal
variances
not
assumed
1.181 16.352 .255 .50 .42 -.40 1.40
Q21
Equal
variances
assumed
10.000 .005 1.584 19 .130 .39 .25 -.12 .90
Equal
variances
not
assumed
1.735 16.874 .101 .39 .22 -8.42E-02 .86
Q22
Equal
variances
assumed
1.357 .258 .737 19 .470 .17 .23 -.31 .64
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113
Equal
variances
not
assumed
.742 17.787 .468 .17 .22 -.31 .64
Q23
Equal
variances
assumed
.376 .547 .837 19 .413 .22 .27 -.33 .78
Equal
variances
not
assumed
.864 18.843 .399 .22 .26 -.32 .76
Q24
Equal
variances
assumed
.136 .717 .240 19 .813 5.56E-02 .23 -.43 .54
Equal
variances
not
assumed
.240 17.298 .813 5.56E-02 .23 -.43 .54
Q25
Equal
variances
assumed
.004 .949 .181 19 .858 5.56E-02 .31 ' -.59 .70
Equal
variances
not
assumed
.179 16.627 .860 5.56E-02 .31 -.60 .71
Q26
Equal
variances
assumed
3.048 .097 .065 19 .949 2.78E-02 .43 -.87 .92
Equal
variances
not
assumed
.062 13.339 .952 2.78E-02 .45 -.94 1.00
Q27
Equal
variances
assumed
1.357 .258 .612 19 .548 .22 .36 -.54 .98
Equal
variances
not
assumed
.630 18.802 .536 .22 .35 -.52 .96
Q28
Equal
variances
assumed
3.367 .082 -1.249 19 .227 -.50 .40 -1.34 .34
Equal
variances
not
assumed
-1.134 10.673 .282 -.50 .44 -1.47 .47
Q29
Equal
variances
assumed
.181 .675 .649 19 .524 .28 .43 -.62 1.17
Equal
variances
not
assumed
.642 16.589 .530 .28 .43 -.64 1.19
Q30
Equal
variances
assumed
.048 .829 .530 19 .602 .17 .31 -.49 .82
Equal
variances
.531 17.529 .602 .17 .31 -.49 .83
R eproduced with permission of the copyright owner. Further reproduction prohibited without permission.
1
not
assumed
Q31
Equal
variances
assumed
1.057 .317 .660 19 .517 .19 .29 -.42 .81
Equal
variances
not
assumed
.695 18.946 .495 .19 .28 -.39 .78
Q32
Equal
variances
assumed
5.552 .029 1.532 19 .142 .44 .29 -.16 1.05
Equal
variances
not
assumed
1.655 17.916 .115 .44 .27 -.12 1.01
Q33
Equal
variances
assumed
.003 .956 -1.222 19 .236 -.39 .32 . . -1-05 .28
Equal
variances
not
assumed
-1.196 15.832 .249 -.39 .33 -1.08 .30
Q34
Equal
variances
assumed
.425 .522 .703 19 .490 .39 .55 -.77 1.55
Equal
variances
not
assumed
.773 16.564 .450 .39 .50 -.67 1.45
Q35
Equal
variances
assumed
.323 .577 1.022 19 .320 .42 .41 -.44 1.27
Equal
variances
not
assumed
1.038 18.300 .313 .42 .40 -.43 1.26
Q36
Equal
variances
assumed
.544 .470 1.379 19 .184 .42 .30 -.22 1.05
Equal
variances
not
assumed
1.368 16.823 .189 .42 .30 -.23 1.06
Q37
Equal
variances
assumed
.028 .868 .909 19 .375 .39 .43 -.51 1.28
Equal
variances
not
assumed
.919 18.047 .370 .39 .42 -.50 1.28
Q38
Equal
variances
assumed
.397 .536 1.193 19 .247 .44 .37 -.34 1.22
Equal
variances
not
assumed
1.216 18.423 .239 .44 .37 -.32 1.21
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115
Q39
Equal
variances
assumed
1.631 .217 .091 19 .929 5.56E-02 .61 -1.22 1.34
Equal
variances
not
assumed
.086 13.053 .933 5.56E-02 .65 -1.35 1.46
Q40
Equal
variances
assumed
.432 .519 .154 19 .879 .11 .72 -1.40 1.62
Equal
variances
not
assumed
.156 18.270 .877 .11 .71 -1.38 1.60
Q41
Equal
variances
assumed
.050 .826 .901 19 .379 .64 .71 -.85 2.12
Equal
variances
not
assumed
.904 17.572 .378 .64 .71 ' -.85 2.13
RQ2
Equal
variances
assumed
.057 .813 1.373 19 .186
.3564814814
8148
.25963970
■ 623887
18695066
915597
.89991363
211893
Equal
variances
not
assumed
1.409 18.698 .175
.3564814814
8148
.25292511
831715
.17347638
292506
.88643934
588802
RQ3
Equal
variances
assumed
.134 .719 2.532 19 .020 .989 .391 .172 1.806
Equal
variances
not
assumed
2.545 17.695 .020 .989 .389 .171 1.806
RQ4
Equal
variances
assumed
1.495 .236 .853 19 .404 .159722 .187158 -.232004 .551448
Equal
variances
not
assumed
.885 18.940 .387 .159722 .180492 -.218133 .537577
RQ5
Equal
variances
assumed
.078 .784 .761 19 .456 .328 .431 -.574 1.229
Equal
variances
not
assumed
.747 16.113 .466 .328 .439 -.602 1.257
Reliability coefficients (Alpha)
RQ2 (Items 10-15) = .4889
RQ3 (Items 16-20) = .7648
RQ4 (Items 21-36) = .8373
RQ5 (Items 37-41) = .7896
R eproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Correlations
RQ3 Pearson
RQ3
1.000
Gender
-.502
Marital
Status
-.308
Correlation
Sig. (2- .020 .175
tailed)
N 21 21 21
Gender Pearson -.502 1.000 .481
Correlation
Sig. (2- .020 .027
tailed)
N 21 21 21
Marital Pearson -.308 .481 1.000
Status Correlation
Sig. (2- .175 .027
tailed)
N 21 21 21
Correlation is significant at the 0.05 level (2-tailed).
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117
Appendix 3
Online Focus Group Questions and Protocol
Interview/Online Focus Group Protocol
Date:
Time:
Group #:
Number of Participants
Names of Participants
Investigator: Leslie Reich
Site: Blackboard Virtual Classroom
Welcome, first, I would like to thank you again for volunteering
for this focus group interview. Just to let you know the focus of
my paper is on the characteristics and needs of the adult distance
learner.
The interview should only take approximately 20-25 minutes.
The discussion will be about your experience with distance
learning, predominantly your experience with EDPT 576.
I will be recording your responses, so if you agree that I may
record this interview we can proceed.
I would like to begin by asking you to introduce yourselves.
1. Please tell me your age, education and professional
background
2. What was your experience with technology prior to class?
3. Do you think your prior computer/technological
experience affected the success of your online
experience?
4. Have you ever taken a distance learning class or had any
prior distance learning experiences?
5. Did your prior learning experiences affect the outcome of
this class?
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6. Did your prior distance learning experience affect the
outcome of this class?
7. Describe the instructional format of the class. How did
the format enhance or detract form the distance learning
experience?
8. Did you have any prior experience with Blackboard?
9. What did you think of the Blackboard instructional
format? (pros and cons)
10. What do you think are the attributes and pitfalls of
the distance-learning format
11. Is there anything else you want to tell me about
distance education?
12. Is there anything else you think I should
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1
Appendix 4
Extensive Correlation of Data
u n its
A G E G E N D E R m a rita l s t c o m . Q 1 0 Q 11 Q 1 2 Q 1 3 Q 1 4 Q 1 5 Q 1 6
A G E P earson
C orrelation
1 .335
. 6 1 2 ( 0 . 5 5 8 0 -.231 -.258 -.399 -.148 .197 .070 -.319
Sig. (2-taiied)
.149 .004 .011 .327 .273 .081 .534 .404 .770 .170
N
20 20 20 20 20 20 20 20 20 20 20
G EN D Pearson
ER C orrelation
.335 1 . 4 8 1 0 .389 - . 4 7 1 0 - . 5 6 0 0 ) - . 5 7 6 0 ) .008 .268 -.072 -.254
Sig. (2-tailed)
.149 .027 .090 .031 .008 .006 .971 .240 .758 .267
N
20 21 21 20 21 21 21 21 21 21 21
m arital
St.
P earson
C orrelation
.612(**) . 4 8 1 0 1 .273 -.120 -.1 7 2 -.391 -.195 .016 .008 -.256
S ig. (2-tailed)
.004 .027 .245 .604 .455 .080 .398 .946 .972 .263
N
20 21 21 20 21 21 21 21 21 21 21
units
com .
P earson
C orrelation
.558(*) .389 .273 1 - . 4 7 5 0 - . 4 7 4 0 -.424 .342 .121 .058 .006
S ig. (2-tailed)
.011 .090 .245 .034 .035 .062 .139 .611 .807 .981
N
20 20 20 20 20 20 20 20 20 20 20
Q 10 P earson
C orrelation
-.231 - . 4 7 1 0 -.120 - . 4 7 5 0 1 . 9 6 5 0 ) . 7 6 8 0 ) .036 .099 .051 .297
Sig. (2-tailed)
.327 .031 .604 .034 .000 .000 .878 .670 .827 .191
N
20 21 21 2 0 21 21 21 21 21 21 21
Q U
P earson
C orrelation
-.258 -.560(**) -.172 - . 4 7 4 0
. 9 6 5 0
)
1 . 7 5 0 0 ) -.034 .078 .093 .279
S ig. (2 -tailed)
.273 .008 .455 .035 .000 .000 .885 .736 .689 .220
N
20 21 21 20 21 21 21 21 21 21 21
Q 12 P earson
C orrelation
-.399 - . 5 7 6 ( 0 -.391 -.424
. 7 6 8 0
)
. 7 5 0 0 ) 1 .221 .016 .231 .339
S ig. (2-tailed)
.081 .006 .080 .062 .000 .000 .335 .945 .314 .133
N
20 21 21 2 0 2! 21 21 21 21 21 21
Q 13 P earson
C orrelation
-.148 .008 -.195 .342 .036 -.034 .221 1 -.174 .088 .679(**)
S ig. (2-tailed)
.534 .971 .398 .139 .878 .885 .335 .449 .704 .001
N
20 21 21 20 21 21 21 21 21 21 21
Q 14 P earson
C orrelation
.197 .268 .016 .121 .099 .078 .016 -.174 1 .162 -.247
Sig. (2-tailed)
.404 .240 .946 .611 .670 .736 .945 .449 .483 .280
N
20 21 21 20 21 21 21 21 21 21 21
Q15 P earson
C orrelation
.070 -.072 .008 .058 .051 .093 .231 .088 .162 1 .031
Sig. (2-tailed)
.770 .758 .972 .807 .827 .689 .314 .704 .483 .893
N
20 21 21 20 21 21 21 21 21 21 21
Q 16 Pearson
C orrelation
-.319 -.254 -.256 .006 .297 .279 .339
. 6 7 9 0
)
-.247 .031 I
Sig. (2-taiied)
.170 .267 .263 .981 .191 .220 .133 .001 .280 .893
N
20 21 21 20 21 21 21 21 21 21 21
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120
Q 17 Pearson
C orrelation
Sig. (2-tailed)
-.350
.130
-.481(*)
.027
N
20 21
Q 18 Pearson
C orrelation -.200 -.440(*)
Sig. (2-tailed)
.399 .046
N
20 21
Q 19 Pearson
C orrelation
Sig. (2-tailed)
-.178
.452
-.390
.081
N
20 21
Q 20 Pearson
C orrelation
Sig. (2-tailed)
.165
.487
-.265
.245
N
20 21
Q21 Pearson
C orrelation
Sig. (2-tailed)
.017
.942
-.342
.130
N
2 0 2 )
Q 22 Pearson
C orrelation
S ig. (2-tailed)
.119
.618
-.167
.470
N
20 21
Q 23 Pearson
C orrelation .209 -.189
S ig. (2-tailed)
.376 .413
N
20 21
Q 24 Pearson
C orrelation
Sig. (2-tailed)
.448(*)
.048
-.055
.813
N
20 21
Q 25 Pearson
C orrelation
Sig. (2-tailed)
.165
.487
-.041
.858
N
20 21
Q 26 Pearson
C orrelation
Sig. (2-tailed)
.231
.327
-.015
.949
N
20 21
Q 27 Pearson
C orrelation
Sig. (2-tailed)
-.084
.726
-.139
.548
N
20 21
Q 28 Pearson
C orrelation
Sig. (2-tailed)
.320
.170
.275
.227
N
20 21
Q 29 Pearson
C orrelation
S ig. (2-taiied)
.024
.919
-.147
.524
N
20 21
R eproduced with permission of the copyright owner. Further
-.327 -.144 .408 .390
. 6 2 9 ( 0
.629(**
)
-.412 .355 . 6 6 6 ( 0
.148 .544 .066 .081 .002 .002 .063 .114 .001
21 20 21 21 21 21 21 21 21
-.136 -.012 .409 .422 .247 .120 .464( -.051 .432
.558 .961 .066 .057 .280 .605
)
.034 .825 .050
21 20 21 21 21 21 21 21 21
.181 .028 .038 .084 . 4 4 1 0 . 4 6 5 0 -.249 J 2 6 0 . 5 7 2 ( 0
.434 .905 .872 .718 .046 .034 .277 .014 .007
21 20 21 2) 21 21 21 21 21
.180 .102 .313 .278 .244 .233 -.049 -.291 .246
.435 .670 .168 .222 .286 .310 .832 .200 .282
21 20 21 21 21 21 21 21 21
.058 -.142 ,5 1 8 C ) . 5 7 4 ( 0 .371 -.190 -.048 -.171 -.090
.803 .551 .016 .007 .098 .409 .837 .458 .699
21 2 0 21 21 21 21 21 21 21
.283 -.444(*) •471(*) .420 .115 -.287 -.303 -.406 -.193
.214 .050 .031 .058 .619 .208 .182 .068 .403
21 20 21 21 21 21 21 21 21
.096 -.192 .300 .267 .000 .5S8(** .049 -.223 -.356
.679 .416 .186 .241 1.000 .009 .832 .331 .113
21 20 21 21 21 21 21 21 21
.159 .084 .234 .301 -.038 - . 4 6 5 0 .062 -.134 -.387
.491 .725 .308 .185 .870 .034 .791 .562 .083
21 20 21 21 21 21 21 21 21
.268 .196 .176 .226 -.0 2 9 -.0 4 2 -.197 -.351 -.2 0 0
.241 .407 .446 .324 .902 .857 .392 .119 .384
21 20 21 21 21 21 21 21 21
.238 -.154 .317 .323 .227 .228 -.042 -.021 .312
.298 .518 .162 .153 .323 .320 .857 .927 .169
21 20 21 21 21 21 21 21 21
.195 -.068 . 4 4 2 0 .427 .144 -.005 -.270 -.321 -.033
.398 .776 .045 .054 .533 .982 .237 .156 .888
21 20 21 21 21 21 21 21 21
.260 .110 -.195 -.267 -.275 -.003 -.068 -.127 -.480(*)
.255 .646 .398 .242 .228 .989 .768 .583 .027
21 20 21 21 21 21 21 21 21
.135 -.001 .125 .111 .183 .049 -.080 -.108 -.181
.559 .997 .589 .631 .427 .832 .729 .642 .432
21 20 21 21 21 21 21 21 21
reproduction prohibited without permission.
121
Q 30 P earson
C orrelation
-.017 -.121 -.417 -.044 -.085 -.110 -.028 .149 .273 -.254 -.125
Sig. (2-tailed)
.942 .602 .060 .853 .713 .636 .905 .520 .232 .267 .590
N
20 21 21 20 21 21 21 21 21 21 21
Q31 P earson
C orrelation
-.078 -.150 -.407 -.163 .091 .063 .030 .076 .293 -.365 .031
Sig. (2-taiied)
.743 .517 .067 .492 .696 .786 .899 .744 .197 .104 .892
N
20 21 21 20 21 21 21 21 21 21 21
Q 32 P earson
C orrelation
.109 -.332 -.028 -.054 .264 .318 .143 -.174 -.075 -.351 -.200
S ig. (2-tailed)
.649 .142 .904 .821 .248 .160 .536 .450 .746 .119 .384
N
20 21 21 20 21 21 21 21 21 21 21
Q 33 P earson
C orrelation
.458(*) .270 .183 .283 -.245 -.284 -.293 .109 .151 -.387 -.099
S ig. (2-tailed)
.042 .236 .426 .226 .283 .213 .197 .637 .514 . .083 .669
N
20 21 21 20 21 21 21 21 21 21 21
Q 34 P earson
C orrelation
.345 -.159 .189 .103 .338 .335 .110 -.129 -.145 -.399 .092
Sig. (2-tailed)
.136 .490 .411 .665 .134 .138 .635 .578 .531 .073 .692
N
20 21 21 20 21 21 21 21 21 21 21
Q 35 P earson
C orrelation
.186 -.228 -.155 -.116 .129 .173 .189 -.037 .121 .177 -.163
S ig. (2-tailed)
.432 .320 .502 .626 .577 .454 .411 .874 .601 .444 .480
N
20 21 21 20 21 21 21 21 21 21 21
Q 36 P earson
C orrelation
-.077 -.302 -.109 -.025 . 5 1 2 0 . 5 2 4 0 .222 .008 -.233 -.029 .287
Sig. (2-tailed)
.747 .184 .637 .916 .018 .015 .333 .972 .309 .901 .207
N
20 21 21 20 21 21 21 21 21 21 21
Q 37 P earson
C orrelation
-.274 -.204 -.243 -.035 .247 .279 .222 .258 -.285 -.102 .236
Sig. (2-taiied)
.242 .375 .289 .882 .280 .221 .334 .258 .210 .659 .303
N
20 21 21 20 21 21 21 21 21 21 21
Q 38 P earson
C orrelation
.048 -.264 .135 .179 .490(*) . 5 2 0 0 .205 .165 -.270 -.263 .229
S ig. (2-tailed)
.841 .247 .561 .449 .024 .016 .372 .474 .237 .250 .319
N
20 21 21 20 21 21 21 21 21 21 21
Q 39 P earson
C orrelation
-.146 -.021 -.361 .256 -.221 -.177 -.130 .082 -.354 -.134 .007
Sig. (2-tailed)
.540 .929 .108 .276 .336 .442 .576 .723 .116 .561 .977
N
20 21 21 20 21 21 21 21 21 21 21
Q 40 P earson
C orrelation
-.272 -.035 -.402 .131 .000 .037 .195 .302 .091 -525(*) .102
Sig. (2-tailed)
.246 .879 .071 .581 1.000 .873 .397 .184 .694 .015 .660
N
20 21 21 20 21 21 21 21 21 21 21
Q41 Pearson
C orrelation
-.352 -.202 -.535(*) .036 -.037 -.007 .231
.587(**
)
-.333 .240 .426
Sig. (2-tailed)
.128 .379 .012 .881 .872 .975 .314 .005 .140 .295 .054
N
20 21 21 20 21 21 21 21 21 21 21
** C orrelation is significant at the 0.01 level (2-tailed).
* C orrelation is significant a t th e 0.0S level (2-tailed).
R eproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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Asset Metadata

Creator Reich, Leslie C. (author)

Core Title Characteristics and needs of the adult distance learner: A case study

Contributor Digitized by ProQuest (provenance)

School Rossier School of Education

Degree Doctor of Education

Degree Program Education

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag education, adult and continuing,education, educational psychology,education, technology of,OAI-PMH Harvest

Language English

Advisor Kazlauskas, Edward (committee chair), Genzuk, Michael (committee member), Picus, Lawrence O. (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-495445

Unique identifier UC11335755

Identifier 3133330.pdf (filename),usctheses-c16-495445 (legacy record id)

Legacy Identifier 3133330.pdf

Dmrecord 495445

Document Type Dissertation

Rights Reich, Leslie C.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA