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A comparative study of motivational predictors and differences of student satisfaction between online learning and on-campus courses

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A comparative study of motivational predictors and differences of student satisfaction between online learning and on-campus courses

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Content STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS

A Comparative Study of Motivational Predictors and Differences of Student Satisfaction
between Online Learning and On-campus Courses
by
Jee Eun Kim

______________________________________________________________________________

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2015

Copyright 2015 Jee Eun Kim

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS ii
Table of Contents
Acknowledgements ........................................................................................................................ iv
Abstract ........................................................................................................................................... v
CHAPTER ONE ............................................................................................................................. 6
Background of the Problem ....................................................................................................... 6
Statement of Problem ................................................................................................................. 9
Purpose of the Study .................................................................................................................. 9
Research Questions .................................................................................................................... 9
Significance of the Study ......................................................................................................... 10
Methodology ............................................................................................................................ 10
Definitions of Terms ................................................................................................................ 11
Organization of the Study ........................................................................................................ 12
CHAPTER TWO .......................................................................................................................... 13
Online Learning in Higher Education ...................................................................................... 13
Impact of Online Learning ................................................................................................ 15
Challenges to Online Learning ......................................................................................... 16
Student Satisfaction ................................................................................................................. 20
Student Satisfaction in Online Learning ........................................................................... 21
Measuring Student Satisfaction ........................................................................................ 23
Importance of Student Satisfaction ................................................................................... 24
Contributing Factors to Satisfaction ................................................................................. 25
Conclusion ............................................................................................................................... 32
CHAPTER THREE ...................................................................................................................... 33
Research Questions .................................................................................................................. 33
Research Design ....................................................................................................................... 34
Population and Sample ............................................................................................................ 34
Descriptive Characteristics ...................................................................................................... 36
Instrumentation ........................................................................................................................ 38
Procedure and Data Collection ................................................................................................ 42
Data Analysis ........................................................................................................................... 42
CHAPTER FOUR ......................................................................................................................... 45
Results ...................................................................................................................................... 45
Demographic Analysis ........................................................................................................ 45
Analysis of Results ............................................................................................................. 48
CHAPTER FIVE .......................................................................................................................... 56
Discussion ................................................................................................................................ 56
Satisfaction by Delivery Method ....................................................................................... 56
Demographic Characteristics and Satisfaction .................................................................. 58
Self-efficacy, Voluntary Collaboration, and Help-Seeking Related to Satisfaction .......... 60
Implications ........................................................................................................................ 61
Limitations ......................................................................................................................... 63
Recommendations for Future Research ............................................................................. 64
Conclusion ............................................................................................................................... 65
References ..................................................................................................................................... 67

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS iii
List of Tables

Table 1: Sample Size of Institution and Course Delivery Method
........................................................
35

Table 2: Mean and Sample Size of Measured Variables by Institution
...............................................
36

Table 3: Demographic Characteristics of Participants
..............................................................................
37

Table 4: Age of Participants by Institution and Course Delivery
..........................................................
38

Table 5: Participants by Course Delivery Method and Reason for Selecting Delivery Method
.
38

Table 6: Research Questions, Variables, and Statistical Analysis Matrix
..........................................
44

Table 7: Demographic Characteristics of Participants by Course Delivery Method
.......................
47

Table 8: Means, Standard Deviations, and Intercorrelations Between Measured Satisfaction,
Self-efficacy, and Demographic Characteristics
........................................................................
49

Table 9: Means, Standard Deviations, and Intercorrelations Between Measured Satisfaction,
Two Subscales of Help-seeking, and Demographic Characteristics
....................................
50

Table 10: Means, Standard Deviations, and Intercorrelations Between Measured Satisfaction,
Voluntary Collaboration, and Demographic Characteristics
................................................
50

Table 11: Mean Student Satisfaction by Course Delivery Method
........................................................
52

Table 12: Mean Student Satisfaction by Employment and Relationship Status
................................
53

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS iv
Acknowledgements
My sincerest thanks to my committee, Dr. Kimberly Hirabayashi, Dr. Helena Seli, and
Dr. Melora Sundt for their guidance and encouragement throughout this process. I would like to
thank Dr. Hirabayashi, for providing continuous direction and advice; Dr. Seli for your support
and technical assistance; and Dr. Sundt for your thought provoking questions and feedback. I am
especially grateful to my chair, Dr. Hirabayashi for inspiring and mapping the course for this
study.

I
would
also
like
to
thank
my
research
colleagues
in
the
thematic
cohort
for
your

willingness
to
collaborate
in
collecting
the
data
and
support
throughout
this
process.

This

would
not
have
been
possible
without
your
assistance
and
openness
to
working
together.

Thank
you
for
the
moral
and
emotional
support.

I
am
grateful
to
all
my
long-‐time
friends,
new
colleagues
and
friends
I
have
met
the

past
three-‐years
at
USC,
and
work
colleagues
for
listening
and
encouraging
me
through
this

challenging
journey.

Lastly,
I
would
like
to
thank
my
family
for
your
continued
love
and

understanding.

I
could
not
have
done
this
without
the
positive
influences
of
all
of
you.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS v
Abstract
The higher demand for online learning has impacted the higher education institutions to
offer more online learning courses. The enrollment rates for online learning continue to increase
and the proportion of students taking at least one online course is at an all-time high. However,
the low retention rates of online courses are concerning higher education institutions. One of the
strongest determinants of student retention has been found to be student satisfaction. Therefore,
this study examines the literature surrounding online learning in higher education, student
satisfaction, and factors of student satisfaction. In particular, demographic characteristics, self-
efficacy, help-seeking beliefs and behaviors, and voluntary collaboration were studied in the
current research. This study compared these constructs between online and on-campus offerings
of a course across five different institutions and levels of higher education.
The study results indicated that there was a significant difference in student satisfaction
between the on-campus and online when participants in both asynchronous and synchronous are
considered together. However, since the sample sizes and design of the online learning were
different between the institutions, further analysis was conducted to investigate the difference in
student satisfaction by institutions. The results showed a statistically significant difference for
institutions that offered a completely asynchronous online course and no differences were found
in satisfaction for online courses that were synchronous. Overall, the study also yielded no
significant differences in student satisfaction based on some demographic characteristics and
found that self-efficacy and help-seeking were predictors of satisfaction. The implications of this
study can be valuable in the field of education as more higher education institutions create online
learning opportunities to reach a diverse student population.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 6

CHAPTER ONE
Technological advances have impacted the delivery method of higher education courses
with distance education evolving with the use of online technology. As more higher education
institutions provide online courses to meet the demand, there is an increased interest in
examining the differences between online and on-campus offerings. Allen and Seamen (2014)
found that institutions with no online offerings were a small minority composed of mostly
private institutions and there were virtually no public institutions among their survey respondents
that did not have online offerings. The chief academic officers in the study believed that the
number of students taking online courses would continue to grow and majority of all higher
education students would be taking at least one online course in the next five years (Allen &
Seamen, 2014).
One of the challenges with online learning offerings is the lower retention rates compared
to face-to-face courses (Brown, 2012; Picciano, Seamen, & Allen, 2010). Research findings
suggest a correlation between dropout rates and student satisfaction with online learning
(Arbaugh, 2000; Levy, 2007; Thurmond, Wambach, Connors, & Frey, 2002). Student
satisfaction has also been identified as the strongest predictor of a student’s intention to continue
enrollment. However, student satisfaction is a multivariate condition with various variables and
determining factors (Wichersham & McGee, 2008). Therefore, this study was designed to further
examine the differences in student satisfaction between online learning and on-campus courses
and the determining factors of satisfaction.
Background of the Problem

Online education has been identified as a critical long-term strategy for higher education
institutions (Allen & Seamen, 2014). However, majority of the higher education institutions
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 7
exclude it from their strategic plan. Although higher education recognized the increased
importance and the opportunities, there was resistance to online learning (Allen & Seaman,
2014). Higher education has identified issues related to online learning including the perception
that online learning was inferior to face-to-face and the low retention rates (Picciano, 2010).
One of the concerns with online learning courses was the low retention rate. There had
been many findings (see Brown, 2012; Picciano et al., 2010; Xu & Jaggars, 2011) that indicated
that online learning courses had significantly lower retention and higher attrition rates than the
on-campus. For example, Brown (2012) found that on average 2.15 students dropped web-based
courses, while 0.57 students dropped land-based courses. Although, online learning has
provided an opportunity for higher education to reach a diverse population and non-traditional
students due to flexibility in scheduling and convenience (Sundt, n.d.), the low retention rates of
online courses were a concern.
In addition, there were inconsistent findings on the quality of online learning. Online
learning was perceived as inferior to face-to-face learning by faculty (Picciano et al., 2010) and
chief academic officers (Allen & Seamen, 2014). However, they did not specify which type of
online learning since there are three types: synchronous, asynchronous, and hybrid (Allen &
Seaman, 2014). Sundt (2014) stated that distinguishing the types of online learning was
important since they had differing barriers, advantages, and outcomes. In addition, some studies
have found that achievement rates of students were not significantly different for online in
comparison to on-site programs (Campbell et al., 2008; Lou et al., 2006). However, there were
other studies that found a significant difference in the learning between students in on-site and
online programs. For example, Castle and McGuire (2010) found that onsite programs had the
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 8
highest reported learning, which was supported by Xu and Jaggars (2011) that students
performed better in face-to-face courses compared to online courses.
Student satisfaction is a mediator variable for retention (Artino, 2008; Chiu et al., 2007;
Lee, 2014; Luo et al., 2011; Palmer & Holt, 2008; Park & Choi, 2009; Shea & Bidjerano, 2008;
Wang, 2003) and learning outcomes (Bollinger & Martindale, 2004; Swan, 2001; Wang,
Shannon, & Ross, 2013). For example, Lee (2014) found student satisfaction to be the strongest
predictor of continuance intention and other studies correlated student satisfaction to dropout
rates in online learning (Arbaugh, 2000; Levy, 2007; Thurmond et al., 2007). In addition, Swan
(2001) had found that perceived learning and student satisfaction with the course were highly
correlated.
Factors that have found to affect student satisfaction included level of prior experience
and the how busy students were (McFarland & Hamilton, 2005) and student characteristics such
as age (Shea & Bidjerano, 2008), flexibility in schedule (Luo et al., 2011), and gender (Bequiri,
Chase, & Bishka, 2010; Shen et al., 2013). In addition, motivational factors such as student
self-efficacy (Palmer & Holt, 2008; Shea & Bidjerano, 2010; Shen et al., 2013), student
collaboration (Rabe-Hemp et al., 2009), and help-seeking (Karabenick, 2003; Karabenick &
Knapp, 1991) were found to determine student satisfaction.
In summary, higher education institutions understand the strategic importance of online
learning in maintaining relevance with the demographic changes of the student population and
demand for increased online learning programs. However, the inconsistent research findings
presented in this section related to student achievement and engagement, perceived quality of
online programs, and student attrition rates for online learning programs obstruct and restrict the
expansion of online learning programs. Student satisfaction has been identified as a key
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 9
mediator for continued enrollment and student attrition rates. Therefore, this study examined
factors determining student satisfaction of online learning and on-campus courses.
Statement of Problem

Higher education has increasingly offered more online learning opportunities to meet the
demands. However, there continues to be a significant gap in the research regarding online
learning compared to face-to-face courses. The perceived quality, inconsistent research findings,
and low retention rates of online learning courses have created a need to understand motivational
factors for student satisfaction.
Purpose of the Study

The purpose of the study was to examine the difference in student satisfaction between
online and on-campus delivery methods based on demographic factors and motivation variables.
This study also examined whether students’ self-efficacy, voluntary collaboration with peers,
utilization of help-seeking strategies, and student demographics are predictors of student
satisfaction.
Research Questions

Within this study, the following research questions were answered:
1. Are there differences in student satisfaction by delivery method?
2. Are there differences in students’ level of satisfaction based on their demographic
characteristics?
3. Does self-efficacy predict student satisfaction, controlling for delivery method?
4. Do voluntary collaboration beliefs and behaviors predict student satisfaction, controlling
for delivery method?
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 10
5. Do help-seeking beliefs and behaviors predict student satisfaction, controlling for
delivery method?
Significance of the Study
This study sought to answer the research questions and contribute to the existing body of
research on student satisfaction for online and on-campus courses. Also, the study examined the
difference in student satisfaction to determine influences on retention rates in addition to the
effectiveness of online learning. Since student satisfaction has been found to be a predictor of
student enrollment and continuance (Lee, 2014) and correlated to learning outcome,
understanding contributing factors that determine student satisfaction in an online learning
course was determined to be important. Furthermore, understanding student motivation as
predictors of student satisfaction could influence pedagogical design of online courses and also
influence retention and learning outcomes.
Methodology

Since the research questions sought to compare student satisfaction and motivation in two
different settings, online and on-campus, the researcher adopted a quantitative approach. The
quantitative approach determined whether statistical differences or predictive relationships
existed between the variables. Data were gathered via surveys that included valid and reliable
instruments such as student satisfaction and demographic questions. These questions were
included in surveys conducted by five other researchers within my thematic cohort with
community college, undergraduate and graduate students in courses offered both online and on-
campus. Therefore, the data were aligned with their studies. Surveys were administered online
utilizing a web-based survey tool. All data were analyzed in SPSS using statistical tests including
independent sample t-test, ANOVA, correlations, and multiple regressions as appropriate.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 11
Definitions of Terms

Asynchronous
Online learning that does not provide any opportunity for live interaction (Allen &
Seaman, 2010).
Help-seeking
An achievement behavior involving the search for and employment of a strategy to obtain
success (Ames & Lau, 1982).
Online learning
Have 80% or more of the course material delivered online without any face-to-face
meetings (Allen & Seaman, 2014).
Satisfaction
The perception of enjoyment and accomplishment in the learning environment (Sweeny
& Ingram, 2001).
Self-efficacy
Individual’s perceived capability to perform and achieve specific results (Bandura, 1993).
Synchronous
Online learning programs that mimic the face-to-face meetings where students and
instructors are brought together to interact live through the computer (Allen & Seaman, 2010).
Voluntary Peer Collaboration
Peer-to-peer collaborative activities that are not initiated or facilitated by the instructor or
required for the course or course assignments, such as creating study groups and peer reviews of
assignments.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 12
Organization of the Study

Chapter one in this study provides an introduction to the topic of online learning in higher
education and retention issues, in addition to an overview of the proposed study.
Chapter two provides an in-depth look at online learning, including a historical overview,
impact of online learning, and challenges to online learning. This chapter also examines student
satisfaction and factors that influence it. These factors include student characteristics, self-
efficacy, voluntary peer collaboration, and utilization of help-seeking strategies.
Chapter three describes the methodology used in this study. This chapter discusses the
sample used, instrumentation, research design, and data collection process. Also described are
the plans for data analysis and as well as the strengths and weaknesses of this study.
Chapter four is a description of the results from the data analysis. Chapter five is a
discussion of these results, in addition to the limitations of the study and suggestions for future
research.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 13
CHAPTER TWO
The purpose of this chapter is to provide a review of the literature on the impact of online
learning in higher education, student satisfaction and its key determining factors, and how it
relates to academic self-efficacy, voluntary peer collaboration, and utilization of help-seeking
strategies.
Online Learning in Higher Education
Online learning in higher education has increased and changed over time. According to
Bernard et al. (2009), the media through which instruction was delivered transformed with the
evolution of technology. They also noted that prior to the introduction of digital media, higher
education offered course content through correspondences delivered by the postal service, which
defined distance education. However, with the increased functionality of technology and the
introduction of the Internet, distance education moved from slow postal mail correspondences to
the high-speed access of online applications (Bernard et al., 2009). In addition, there was an
evolution in the terminology for distance education, which coincided with the developments in
technology. The term distance education evolved to online learning as more higher education
courses utilized the web and online technology to deliver course content (Bernard et al., 2009).
According to Bernard et al. (2009), the term distance education was utilized to describe
the program and courses delivered by postal mail services in higher education. They stated that
advances in technology have revolutionized instructional media and higher education has
progressed from the traditional distance learning of the past to providing online learning
programs (Bernard et al., 2009). Online learning was defined as those having at least 80% of the
course material delivered online without any face-to-face meetings (Allen & Seaman, 2010,
2014).
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 14
Online learning were further categorized into two types, asynchronous and synchronous
learning. Categorizing online learning to synchronous or asynchronous depended on the type of
medium utilized to deliver the course content. Synchronous learning occurs in real time and
allows students and instructors to interactive live (Allen & Seaman, 2010; Chambers & Lee,
2004; Means et al., 2010). The terms synchronous and asynchronous has been utilized to define
online learning program as well as online learning activities.
Since online learning programs have the potential to utilize different types of learning
activities, Allen and Seaman (2010) categorized online learning programs into three categories:
synchronous, asynchronous, and blended or hybrid. Online learning programs that mimic the
face-to-face meetings where students and instructors are brought together to interact live through
the computer were defined as synchronous or web facilitated (Allen & Seamen, 2014). An
example of synchronous instruction includes a live broadcast of a lecture where students have the
opportunity to submit questions through chat function (Sundt, 2014). On the other hand, they
distinguished asynchronous online learning as one that does not provide any opportunity for live
interaction and most or all of the content is delivered online (Allen & Seamen, 2014). In an
asynchronous online learning course, students access and submit material independently of other
students (Sundt, 2014). A synchronous online learning mimics face-to-face through the
computer, while the blended or hybrid online learning offers a mixture of online and face-to-face
activities (Allen & Seaman, 2010). Distinguishing between the three categories of online
learning programs were found to be important since they had different barriers, advantages, and
outcomes (Sundt, 2014).
The demand for online learning has increased over the years. Allen and Seaman (2010)
found that 74.5% of higher education institutions surveyed stated there was an increase in the
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 15
demand for online courses. An indicator of the increased demand of online learning was student
enrollment. Data have shown an increase of online learning education with the enrollment rates
of students in online education courses exceeding that of students in on campus programs (Allen
& Seaman, 2010; Picciano, Seaman, & Allen, 2010). According to Seaman and Allen (2010),
the most substantial growth in enrollment has been in online learning programs at higher
education institutions. While enrollment rates increased 2% overall in higher education, there
has been an increase of 21% in the number of students enrolled in online courses (Allen &
Seaman, 2010).
The number of online enrollment continued to increase, however the rate of growth has
decreased over the years. Allen and Seamen (2014) found that the number of students taking at
least one online course totaled 7.1 million, an increase of 6.1% from the previous year, which
was the lowest recorded growth rate. However, the proportion of higher education students
taking at least one online course was at an all-time high of 33.5% (Allen & Seamen, 2014).
Impact of Online Learning
Online learning programs have expanded the opportunity for higher education to reach a
diverse population. Picciano et al. (2010) found that the demographics of students who took
online courses differed from those that enrolled in face-to-face courses. Online courses were
more likely to be taken by part-time students and students from racial and ethnic minority
backgrounds (Picciano et al., 2010). The availability of online education has increased access to
higher education for non-traditional student populations (Chen et al., 2010; Picciano et al., 2010).
According to Picciano et al. (2010), traditional students were considered full time, resided on
campus, were between the ages of 18 and 22, and depended on financial support from parents.
They categorized non-traditional students as those who worked more than 20 hours a week or
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 16
had dependent children (Picciano et al., 2010). Additional characteristics of non-traditional
students included being older, living independently of parents or caring for older parents, and
returning to school after a long absence (Sundt, 2014).
The flexibility in scheduling permitted by online learning programs has increased access
for non-traditional students to pursue higher education. Online learning provided students with
flexible scheduling, which allows them to pursue higher education while employed and
maintaining family responsibilities (Picciano et al., 2010, Sundt, n.d.). According to Means et al.
(2010), one of the factors for the increased popularity of online learning was the flexibility of
access to courses independent of time and place. Therefore, the flexible schedule offered
through online learning programs provided an opportunity for non-traditional students to attend
higher education courses and diversified the student population.
Challenges to Online Learning
There are challenges that prevent higher education from maximizing the capacity of
online learning. The major challenges that will be discussed in this section are the perceived
quality of online learning courses, student attrition rates, and inconsistencies in the research
related to student achievement and engagement.
Quality of online learning. There has been a concern regarding the quality of the online
learning. There has been a perception that online learning was inferior to face-to-face. Although
there has been a tremendous increase of online courses offered, Picciano et al. (2010) found that
70% of faculty surveyed viewed online learning as inferior to face-to-face learning. They stated
that the perception of faculty was important since they were the judges of the quality of student
performance in a course. However, they also found that 56% of the faculty still recommended
online courses to their students since access to courses was more important and valued by the
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 17
faculty than their perceived inferiority of the courses (Picciano et al., 2010). Allen and Seamen
(2014) surveyed chief academic officers and found that more than two-thirds believed there are
continued concerns about the quality of online course. 26% of academic leadership surveyed
indicated that online learning outcomes were inferior to face-to-face instruction, which is an
increase of 3% since 2013. However, they reported that substantial use of student-directed, self-
paced components would continue in future online courses (Allen & Seamen, 2014).
Learning outcome was dependent on the instruction provided and not the delivery method
(Clark, 2004). There were key strategies for developing effective distance learning identified by
Clark (2004). In addition, the idea that more was learned through multimedia learning than in-
person, was refuted by Clark and Feldon (2005). They found that the assertion that learning was
increased with the utilization of multimedia because it provided distinctive instructional methods
for different learning styles was not supported (Clark & Feldon, 2005). Tamin and colleagues
(2011) suggested that the effectiveness of the course was not dependent on the mere utilization
of technology to deliver content, rather in depended on how it was utilized to support teacher and
students to achieve the desired instructional goals. Tamin et al. (2011) found that the utilizing
technology had more of a positive impact on learning, especially when used to support
instruction compared to technology that is utilized for direct instruction. They also found that
computer technology utilized to support cognition has a greater effect than technology used to
present the content, which suggests that the strength of technology relies on supporting student
efforts to achieve rather than as a tool for delivering content (Tamim et al., 2011). In addition,
learning outcomes were not a result of utilizing online tools alone, but required exploiting the
strengths of the tools and incorporating them with elements of good teaching principles (Ferrario,
Hyde, Martinez, & Sundt, 2013).
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 18
Picciano and colleagues (2010) stated that 85% of faculty indicated that developing
online courses took more effort and 64% of faculty reported that teaching online required more
effort than face-to-face courses. They noted that age was not an indicator since most experienced
faculty were teaching online at equivalent rates compared to less experienced faculty (Picciano et
al., 2010).
Inconsistent research findings. There are discrepancies in the research regarding the
effectiveness of online programs. Although many researchers have examined the effectiveness
of online in comparison to on-site programs, the results have been inconsistent. There were
some studies that indicated online learning was not a superior medium for content delivery and
there were no difference in the achievement rates (Brown, 2012; Campbell et al., 2008; Lou,
Bernards, & Abrami, 2006; Tamim et al., 2011). Campbell et al. (2008) found that the modality,
whether online or face-to-face did not determine student achievement. They found no difference
in the passing rates of students between face-to-face and online courses. Lou, Bernards, and
Abrami (2006) also found that students at remote and host sites achieved equally. They stated
that student achievement was affected by how the media was utilized to support learning. The
results of their study indicated that when the online and face-to-face course had the same
instructor, instruction, activities, and materials, there was no difference in student achievement
(Lou et al., 2006). Therefore, the media utilized to deliver the course was not a factor in student
achievement.
However, there are other studies that have found a difference in the reported learning of
students between on-site and online programs (Castle & McGuire, 2010; Xu & Jaggars, 2011).
Castle and McGuire (2010) found a significant difference in student learning between onsite,
hybrid, and online learning. They stated that onsite programs had the highest student self-
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 19
reported learning. This was also supported by the results from the study Xu and Jaggars (2011)
performed, where they also found that students performed better in the face-to-face course than
those in the online course. Therefore, the inconsistencies in the research findings were an
identified challenge to online learning.
There were also inconsistent research findings on the relationship between the use of
technology and student engagement. Picciano et al. (2010) found that students perceived online
learning to be beneficial and were more likely to utilize technology to communicate and engage
in the learning process (Chen et al., 2010). Studies also showed that students in online courses
were engaged in higher order levels of thinking and analysis in comparison to on-campus courses
(Robinson & Hullinger, 2008; Rabe-Hemp, Woollen, & Huminston, 2009). Robinson and
Hullinger (2008) found that technology increased the opportunities to stimulate higher levels of
thinking since it allocated more time for students, allowed communication through multiple
channels, and created a community of inquiry.
Student retention. Although online learning has increased enrollment and diversified
the student population in higher education, the low retention rates with online courses is a
concern. A total of 41% of chief academic officers surveyed reported that retaining student in
online courses was a greater problem than for face-to-face courses. This was a considerable
increase from the 28% reported in 2009 (Allen & Seamen, 2014). Results from studies indicated
that attrition was higher in online learning programs (Brown, 2012; Picciano et al., 2010;Xu &
Jaggars, 2011). Picciano and colleagues (2010) stated that online learning courses had a 58%
retention rate. This meant that little less than half of the students in the course withdrew from
the courses. Brown (2012) indicated that the retention rates of students in the land-based
courses were higher than the web-based course. They found that on average, 2.15 students were
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 20
dropping the web-based course, while only 0.57 students were dropping out the land-based
course (Brown, 2012). The study conducted by Xu and Jaggers (2011) also revealed similar
findings. They found that the attrition rate for online takers was 19% compared to the 10% for
face-to-face in an English gatekeeper course, while the math gatekeeper course had even higher
attrition rates at 25% for online versus 12% for face-to-face (Xu & Jaggers, 2011).
Student Satisfaction
Student satisfaction has been found to be a key factor in determining student’s
continuance and retention in online learning courses. Retention activities focus on keeping
students satisfied and returning (Elliot & Healy, 2012). Satisfied students have positive learning
experiences and outcomes, which influenced students’ intention and were motivated to continue
their studies (Aitken, 1982; Anderson & Shelledy, 2013; DeShields, Kara, & Kaynak, 2005;
Elliot & Healy, 2012). Aitken (1982) indicated that student GPA and satisfaction were important
in explaining retention. They found satisfaction as an important variable in determining retention
second to perceived GPA. There were also external factors, such as family or personal problems
as an indicator of retention and whether students were returning the following year. They found
that retention was predicted based on perceived and actual GPA, residential living and academic
satisfaction, and concerns with family (Aitken, 1982).
Satisfaction was related to goals and needs determined by the learner. Cassel (1968)
stated that learner satisfaction was derived from the perceived notion that the learner was
meeting their own needs and accomplishing self-imposed goals. The learner also derives
satisfaction from problem solving or discovering new relationships when challenged and less
satisfied when the activity was easy or familiar. Student participation and knowledge of
accomplishments was also a factor in satisfaction. Therefore, designing the course with various
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 21
planned activity that incorporates student participation, a sense of discovery, and structured
learning that progresses the learner towards achieving their goals would impact satisfaction
(Cassel, 1968).
Student satisfaction was defined as the perception of enjoyment and accomplishment in
the learning environment (Sweeney & Ingram, 2001). Student satisfaction has been associated
with various factors. Student satisfaction is a multi-dimensional condition dependent on factors
determined by the learner (Elliot & Healy, 2001; Hartman & Schmidt,1995; Wickersham &
McGee, 2008). Therefore, the key to measuring student satisfaction was determining the
important factors for learners. However, students identify different factors as important and may
consider factors unimportant to learning outcomes important to them (Elliot & Healy, 2001).
Student Satisfaction in Online Learning
The increased enrollment in online learning programs has provided higher education
institution with an opportunity to transcend geographic barriers and expand its reach to non-
tradition populations. One of the factors affecting the student’s choice to enroll in online
learning was satisfaction (Picciano et al., 2010). Sinclaire (2011) stated that student satisfaction
with online learning was linked to interaction and communication, course design, learning
environment, and individual computer self-efficacy and ability to control learning pace.
Sinclaire (2011) indicated that interaction and communication, course design, learning
environment, and individual computer self-efficacy and ability to control learning pace
correlated to student satisfaction.
One interesting finding was that the majority of factors affecting performance and
satisfaction differed between online and traditional courses (McFarland & Hamilton, 2005).
Bollinger and Martindale (2004) found that instructor variables such as communication and
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 22
teaching methods were the most important factors affecting student satisfaction in the online
environment. However, they also found technology and interactivity were two other factors that
linked to student satisfaction. Students needed to have access to reliable equipment that allowed
them to participate in the online environment and opportunities to participate in discussions to
feel involved and engaged during online learning (Bollinger & Martindale, 2004).
Many studies have found no significant difference in course satisfaction levels amongst
students taking courses utilizing different delivery methods (Abdous & Yoshimura, 2010;
Arbaugh & Duray, 2002). For example, Abdous and Yoshimura (2010) examined the
satisfaction of students taking the same course offered simultaneously in three delivery formats
by the same instructor. They found no statistically significant difference in satisfaction among
those enrolled in face-to-face, satellite broadcasting, and live video-streaming delivery methods.
A potential contributing factor to the results might be that there was a good fit between the
course delivery method and level of computer skills of the students (Abdous & Yoshimura,
2010).
Although Arbaugh and Duray (2002) also found no significant difference in perceived
course satisfaction levels, the students in the online course reported higher satisfaction with their
delivery method compared to those enrolled in the hybrid course, which supplemented online
with on-campus meetings. They associated the significantly higher satisfaction with the online
learning method with more experienced online students and schedule flexibility (Arbaugh &
Duray, 2002). A predictor of student satisfaction was the familiarity of students with the course
background and students who liked online courses and perceived online course as a suitable way
of learning were more satisfied with the online delivery method (Bequiri, Chase, &Bishka,
2010).
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 23
In a study conducted by Cole and colleagues (2014), students were surveyed regarding
reasons for satisfaction and dissatisfaction with online courses. Students reported convenience
as the greatest factor influencing satisfaction with online courses. The main source of
dissatisfaction was lack of interaction with instructors and peers. The students reported the lack
of communication with instructors and classmates in the online environment. The online course
structure and learning style were reasons for both satisfaction and dissatisfaction (Cole et al.,
2014).
Measuring Student Satisfaction
Researchers have identified various variables related to student satisfaction. Aitken
(1982) examined academic satisfaction as a function of academic performance, quality of
curriculum, instruction, and advising, student satisfaction with major field, and student
personality. The two determinants of satisfaction found by Douglas, McClelland, and Davies
(2008) were quality as measured by communication and responsiveness, and usefulness. The
two important factors of satisfaction for students discovered by Elliot and Healy (2001) were
academic advising and instructional effectiveness. In addition, they also found student
centeredness and campus climate as strong predictors of student satisfaction even though the two
were not ranked highly important by students (Elliot & Healy, 2001). Other researchers (Wang,
2003; Wickersham & McGee, 2008) also indicated the strongest predictors of student
satisfaction was instructional effectiveness, which included quality of program design and
interaction with instructor and peers. Guolla (1999) studied the factors that determined quality
and found learning had the greatest impact on course satisfaction. Although there were many
different variables and measures, one of the key determinants was instructional effectiveness.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 24
Another key factor related to satisfaction were student characteristics. Factors found to
affect student satisfaction included age (Shea & Bidjerano, 2008), flexibility in schedule
(Arbaugh & Duray, 2002; Luo et al., 2011; McFarland & Hamilton, 2005), gender (Bequiri et al.,
2010; Shen et al., 2013), and level of prior experience (McFarland & Hamilton, 2005). In
addition, motivational factors such as student self-efficacy (Palmer & Holt, 2008; Shea &
Bidjerano, 2010; Shen et al., 2013), student collaboration (Rabe-Hemp et al., 2009), and help-
seeking (Karabenick, 2003; Karabenick & Knapp, 1991) were found to correlate with student
satisfaction.
Importance of Student Satisfaction
A mediator variable for retention and learning outcomes was student satisfaction. Lee
(2014) found student satisfaction to be the strongest predictor of continuance intention and other
studies correlated student satisfaction to retention (Pervin & Rubin, 1967) and dropout rates in
online learning (Arbaugh, 2000; Levy, 2007; Thurmond et al., 2007).
Student satisfaction was identified as an important contributor to student’s intention to
reuse or re-enroll in online learning (Artino, 2008; Chiu et al., 2007; Lee, 2010; Luo et al., 2011;
Palmer & Holt, 2008; Park & Choi, 2009; Shea & Bidjerano, 2008; Wang, 2003). For example,
Lee (2010) found student satisfaction to be the strongest predictor of continuance intention,
while student dissatisfaction with online learning was a necessary condition for discontinuance.
Chiu et al. (2007) found that satisfaction was a significant contributor to the learner’s intention to
continue online learning enrollment. Since student satisfaction is a strong predictor of their
intention to continue, the ability to determine student satisfaction with online learning courses
was identified as an important factor for the continuance of online learning programs.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 25
Student satisfaction was also identified to be closely associated with learning outcomes.
Studies have shown a positive relationship between student satisfaction and learning (Bollinger
& Martindale, 2004; Swan, 2001; Wang, Shannon, & Ross, 2013). Bollinger and Martindale
(2004) stated that student satisfaction was a key variable in determining success or failure of
online learners, courses, and programs. Swan (2001) found that student satisfaction with the
courses and perceived learning was the most highly correlated variables. Wang et al. (2013)
stated that course outcome and satisfaction acted as a mediator between student motivation and
performance. They found that more satisfied students tended to earn higher grades (Wang et al.,
2013).
Contributing Factors to Satisfaction
A review of the research has also found that student satisfaction with online learning was
determined by different contributing factors (Palmer & Holt, 2008; Shea & Bidjerano; Shen et
al., 2013), which were largely dependent on student’s perceptions (Luo et al., 2011; Wickersham
& McGee, 2008). One of the key predictors of satisfaction was found to be instructional
effectiveness. Therefore, descriptive characteristics, academic self-efficacy, voluntary peer
collaboration, and help-seeking were selected for further research to determine the impact of
student’s perception in determining satisfaction with online learning courses.
Student characteristics. Online learning programs have created an opportunity for a
diverse population of students to pursue higher education. The convenience and flexibility of
online learning courses has provided accessibility for non-traditional population to pursue higher
education. The convenience and flexibility of schedules was found to positively correlate with
learner satisfaction (Luo et al., 2011). The flexibility in scheduling offered students a higher
level of control and independence, which led to higher satisfaction. Since majority of students
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 26
were found to be non-traditional, a review of the impact of age and gender on student satisfaction
was conducted.
The age of the student impacted their perception of online learning courses and
satisfaction. Shea and Bidjerano (2008) suggested that asynchronous online learning was
unlikely to satisfy the younger generation of students who have grown up immersed in media
and therefore would not be engaged by a text-based asynchronous online learning. In the study,
they categorized the participants into three age categories (greater than 18 to 25, 26 to 40 and
less than 40). The result of the study found that older students tended to report greater cognitive
presence in their online courses and greater satisfaction with the courses. However, they also
stated that other dimensions measured such as cognitive and teaching presence mediated the
effect of age on overall satisfaction (Shea & Bidjerano, 2008), hence age may not be a
determining factor of student satisfaction. In earlier studies, age had a moderate effect directly
and indirectly on student satisfaction (Liu & Jung, 1980). They also found that age was related
to GPA and educational benefits as older students were reported to be more eager to learn than
younger students. Analysis of the influence of GPA and perceived educational benefit on
satisfaction resulted in high effects (Liu & Jung, 1980).
Contradictory to earlier findings, Cole, Shelley, and Swartz (2014) found no significant
difference in levels of satisfaction based on age. Although, members of Generation X were more
likely to rate their experience with online courses satisfactory than the younger group of those
identified as Generation Y, there was no statistically significant difference found (Cole et al.,
2014).
There are inconsistent findings regarding the impact of gender on the satisfaction of
online learning courses. In the study by Shen et al. (2013), the majority of the participants were
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 27
female (74.1%). They found that gender was a significant predictor of self-efficacy (Shen et al.,
2013). According to the results from the Shen et al. (2013) study, gender predicted the self-
efficacy to interact with classmates for academic purposes, handle tools in a Course Management
System (CMS), and interact with instructors to complete an online course. Bequiri and
colleagues (2010) found a marginal significant difference between male and female student
satisfaction with online courses. The male students reported higher satisfaction with online
courses than female students (Bequiri et al., 2010). However, there were studies that have found
no significant difference between gender and satisfaction (Arbaugh, 2000; Cole et al., 2014;
McFarland & Hamilton, 2005).
There have been other demographic characteristics found to impact student satisfaction.
Bequiri et al. (2010) found a correlation between student satisfaction and academic status,
marital status, and distance from campus. They demonstrated that the student satisfaction was
better for graduate level than undergraduate level. They also found that married students were
significantly more satisfied with online courses in comparison with single students. In addition,
they found that students living more than 1 mile away from the campus were more satisfied than
those who lived close to or on campus (Bequiri et al., 2010).
Student self-efficacy. Self-efficacy is defined as an individual’s perceived capability to
perform and achieve specific results (Bandura, 1993; Pajares, 1996). Self-efficacy is domain
specific and related to specific tasks. According to Bandura (1993), self-efficacy beliefs were
determined by direct previous and vicarious experiences. In relation to previous experience,
Shen et al. (2013) found that the number of online courses completed was a significant predictor
of self-efficacy. They also found a significant correlation between self-efficacy and learning
satisfaction. Therefore, the more previous experience a student had with online learning courses,
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 28
the higher their self-efficacy and learning satisfaction (Shen et al., 2013). On the other hand,
Abdous and Yen (2010) found that the number of distance courses taken was not a predictive
factor of student satisfaction. They only found a weak relationship between the two variables.
The results from studies indicated that self-efficacy was a determining factor for student
satisfaction with online learning (Palmer & Holt, 2008; Shea & Bidjerano, 2010; Shen et al.,
2013). Since self-efficacy was related to specific tasks, there were various tasks identified as
indicators for student satisfaction. Since online learning involves the use of technology, Abdous
and Yen (2010) studied the relationship of technology related self-efficacy and student
satisfaction and found inconsistencies. They found that self-rated computer skills was negatively
related to student satisfaction, which means that students self-reporting higher computer skill
level were less satisfied than those with lower computer skill levels (Abdous & Yen, 2010).
Shen et al. (2013) found that several specific self-efficacy as significant predictors of
learning satisfaction. They found that student’s self-efficacy related to interacting socially with
classmates; instructors in an online course; interact with classmates for academic purposes; and
complete an online course were found to predict learning satisfaction (Shen et al., 2013). Shea
and Bidjerano (2010) found teaching and social presence to be correlated with student self-
efficacy. They also discovered that the relationship between teaching presence and self-efficacy
was more significant in blended online environments (Shea & Bidjerano, 2010). The most
variance in learning satisfaction correlated to self-efficacy to complete an online course and
therefore was the most significantly associated with learning satisfaction. This is supported by
the results from Palmer and Holt (2008), where they found the highest mean ratings for
statements related to student’s self-efficacy and their ability to communicate and learn online.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 29
Student interaction. The technological advances have improved the collaboration in
online learning courses. Online learning platforms have provided a shared space that enhanced
the potential for communication and gathering students to collaboratively work together (Rabe-
Hemp et al., 2009; Sher, 2009). The results of the study conducted by Sher (2009) indicated that
students valued more opportunities for meaningful interaction with other students. The
interactions and learning with peer students was found to be a key to collaborative learning
(Robinson & Hullinger, 2010). Robinson and Hullinger (2010) found that approximately 80% of
students collaborated on projects fairly frequently. They recommended that online curriculums
should engage students through opportunities for peer interactions by creating a collaborative
learning environment as well as with instructors (Robinson & Hullinger, 2010).
A determining factor of student satisfaction in online learning courses was found to be
interaction. Lou and colleagues (2006) indicated there were 3 dimensions for interaction:
student-student, student-instructor, and student-content. They found that student engagement
and perceived availability of the instructor impacted student satisfaction in online learning
courses. In addition, they found that student-student interaction was superior to individual
learning and positively impacted student achievement. Student-instructor interaction was a
strong factor for predicting student achievement (Lou et al., 2006), however, student-student
interaction also enhanced student learning and satisfaction (Bollinger & Halupa, 2012; Lou et al.,
2006; Sher, 2009). Sher (2009) found there was a positive association with both student
interactions with instructor and other students and student learning and satisfaction. In addition,
Swan (2001) found a relationship between interaction with classmates and student satisfaction as
well as learning. They discovered students who reported high levels of interaction with their
classmates also reported higher levels of satisfaction and learning (Swan, 2001).
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 30
Drouin (2008) indicated that student-to-student and student-to-instructor interaction was
correlated to a students’ perceived sense of community. She found a significant difference in the
perceived ability of students to communicate with their instructor versus with their fellow
classmates in an online course. While 77% of the students reported communicating with the
instructor “very often” or “always,” only 19% reported communication with their classmates. Of
the two interaction types, the student-to-student interaction was significantly related to sense of
community, which was significantly related to student satisfaction and not related to retention or
achievement (Drouin, 2008).
Bollinger and Wasilik (2012) questioned the importance of peer and instructor
interaction. They studied online courses that was not designed with student-to-student
interaction and had limited instructor-to-student interaction. In comparison to the on-campus
sections, the online students reported less interaction, however reported they were satisfied with
their online learning experience (Bollinger & Wasilik, 2012).
Help-seeking. Help-seeking is a self-regulatory behavior that is considered an alternate
route to achieving academic goals (Karabenick & Knapp, 1991). Those students who are more
motivated and strategic learners are more likely to seek help (Karabenick, 2003; Karabenick &
Knapp, 1991). Help-seeking has been categorized into two forms, executive and instrumental.
According to Karabenick and Knapp (1991), executive help-seeking is defined as the act of
seeking help in order to decrease the effort needed to complete a task, while instrumental help-
seeking is sought in order to gain minimum assistance needed to achieve the task independently.
There are two sources from which a student will seek help, formal from an instructor or informal
from peers. The researchers found that student’s intention to engage in instrumental help-
seeking was linked to more formal sources than informal sources (Karabenick & Knapp, 1991).
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 31
They also found a significant correlation between self-esteem and formal help-seeking. The
intentions of students to seek help were good indicators of actual behavior (Karabenick &
Knapp, 1991). Students who reported help-seeking was associated with need and it was the
tendency of the students who used more strategies for academic achievement, whether help-
seeking from formal or informal sources (Karabenick & Knapp, 1991).
The determining factor of whether the student help-seeking went to a formal or informal
source depended on the goal for help-seeking. Karabenick (2003) found that students needing
instrumental help sought it from formal sources, had higher levels of self-efficacy and mastery
approach goal orientation. The students reported that they would seek help more from formal
sources because it would yield in higher quality information.
The environment is important in encouraging help-seeking behaviors. Abdous and Yen
(2010) found self-perceived learner-to-teacher interaction was a strong predictor of student
satisfaction. The results indicated that an increased level of self-perceived learner-to-teacher
interaction was significantly related to positive learner satisfaction and associated with positive
learning outcomes (Abdous & Yen, 2010).
In summary, an important factor linked with the challenges of online learning was student
satisfaction. Student satisfaction was determined to be a multivariate construct and an important
factor of student continuance in online programs. In reviewing the literature, it was determined
that satisfaction was connected to quality of the program design, student interaction with
instructor and peers, and learner characteristics. Three other factors that contribute to student
satisfaction include self-efficacy, collaboration, and utilization of help-seeking strategies.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 32
Conclusion
In conclusion, the technological advances have provided higher education with an
opportunity to increase enrollment and accessibility to non-traditional students. Higher
education has indicated that online learning is a strategic priority to meet the demands of
students. However, the low retention rates of online learning courses have created a need to
further research the difference in student satisfaction between online learning and on-campus
courses and programs. Although, the existing research presented in this chapter has shown a
correlation between student satisfaction, student retention, and learning outcomes, there
continues to be a gap. The gaps identified while reviewing the literature were the limited
number of comparative studies conducted on online learning and face-to-face courses and
programs. Majority of the research found studied one specific course, which may limit the
generalizability to other courses. Also, the body of literature has found that student satisfaction
was related to challenges of online learning. As higher education transforms from the traditional
face-to-face and continues to incorporate technology to create more online learning
opportunities, it is important to better understand the factors that contribute to a positive learning
outcome. Therefore, this study is designed to address the gaps in the literature regarding the
contributing factors of student satisfaction.
This study will also contribute to the existing body of research and contributing
motivational factors to student satisfaction. Understanding student motivation as predictors of
student satisfaction can influence pedagogical design of online courses and programs and
influence retention and learning outcomes.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 33
CHAPTER THREE

The findings from the literature review show that more online courses are being offered
to meet the demands and increased enrollment of students. Although online learning research is
limited, one of the concerns is the low retention rate. The research findings support student
satisfaction as a strong determinant of student continuance. Therefore, examined in this study are
the differences in student satisfaction based on demographic factors and motivation variables. In
addition, this study examined whether student’s self-efficacy, voluntary collaboration with peers,
and help-seeking are predictors of student satisfaction. Discussed in this chapter are the research
questions, hypothesis of the researchers, and a description of the research methodology. The
latter included the sampling procedure and population of study, instrumentation, and procedures
that were utilized for data collection and analysis.
Research Questions

The following proposed research questions guided this study:

1. Are there differences in student satisfaction by delivery method?
2. Are there differences in students’ level of satisfaction based on their demographic
characteristics?
3. Does self-efficacy predict student satisfaction, controlling for delivery method?
4. Do voluntary collaboration beliefs and behaviors predict student satisfaction, controlling
for delivery method?
5. Do help-seeking beliefs and behaviors predict student satisfaction, controlling for
delivery method?

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 34
Research Design

The study was a quantitative, non-experimental design to examine correlational
relationships between demographic and motivational variables with student satisfaction from
self-report surveys. The independent variables of the study were demographic characteristics,
self-efficacy, voluntary peer collaboration, and academic help-seeking. The dependent variable
was student satisfaction. Data was collected from self-report surveys administered online with
students in online and on-campus course formats in community college, undergraduate and
graduate level courses. The data was analyzed for statistical significance.
Population and Sample

The study encompasses results from data collected collaboratively with five other
researchers of a thematic dissertation group. The population for the study included participants
from five different higher education institutions: two different community college courses; two
undergraduate level courses at two different four-year universities; and one graduate level course
at a four-year university in the Southern California area identified with both on-campus and
online offerings of the same course. The total respondents for the study were N=409, with 161
participants from the online course offering and 245 participants from the on-campus course
offering. Table 1 provides a summary of the type of institution and number of participants from
each institution. The participants from the Institution A were enrolled in an introductory
sociology course taken by students in the first year of college and participants from Institution B
were a diverse sample of first and second year students enrolled in an introductory information
technology concepts and application course. The participants from Institution C at the
undergraduate level were enrolled in a stress and family coping course open for upper division
college majors at a public four-year university. The participants from Institution D were enrolled
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 35
in an upper division, undergraduate level Leadership and Professional ethics course at a private,
non-profit four-year university. The participants from Institution E were enrolled in a graduate
level course. They were primary and secondary teachers enrolled in a fieldwork course towards
the end of a one-year intensive credential and master’s level program. The online course for
Institution A, B, C, and D was completely asynchronous, while the online course for Institution
E were synchronous since it had web-facilitated live sessions.
Table 1
Sample Size of Institution and Course Delivery Method
Course Delivery
Institution Type of Institution
Sub-Sample
Size
n
Online
n
On-Campus
n
Institution A 2-year Community College 171 51 120
Institution B 2-year Community College 126 44 82
Institution C 4-year Public Undergraduate 34 20 14
Institution D 4-year Private Undergraduate 30 16 14
Institution E 4-year Private Graduate 45 30 15

The survey items administered were not consistent across the five schools since the data
were collected collaboratively with five other researchers in a dissertation thematic group. The
variables collected and sample size are presented in Table 2. The demographic and student
satisfaction items were captured for all five surveys, however the self-efficacy, help-seeking, and
voluntary collaboration items were only administered at certain schools. Therefore, the sample
size varied for each of these scales.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 36
Table 2
Mean and Sample Size of Measured Variables (Likert Scale 1 – 5; 1=Strongly Disagree to
5=Strongly Agree) by Institutions

Institutions Measured Variable M SD n
A, B, C Self-efficacy 4.02 0.77 331
A, B, C, D General Help-Seeking 3.98 0.76 342
A, B, C, D Formal Help-Seeking 3.84 0.92 342
D, E Voluntary Collaboration 4.21 0.76 75
Descriptive Characteristics
The demographic characteristics of the participants who completed the survey are
summarized in Table 3. Majority of the participants were at the community college level (74%),
female (57%), Hispanic/Latino (41%), not working at the time of the survey (46%), and single
(80%). The mean age of the participants was 25. The median age of the participants in the on-
campus course at 21 years of age was lower than the mean. The online participants had a greater
age range (18-43) than the on-campus (17-35) when the outliers were excluded. The age of the
participants distinguished by institution and course delivery are summarized in Table 4. The
mean age of the participants from the online course offerings were older than those from the on-
campus offering except Institution D. Although Institution E was the graduate course and
expected to have an older student population, the oldest participants were from Institution D,
which was an undergraduate course with a mean age of 38.7 for the asynchronous online and
39.2 for on-campus offering. The participants who had previously taken an online course (51%)
were approximately equal to those who had never taken an online course. The mean number of
units participants were enrolled in was 11.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 37

Table 3
Demographic Characteristics of Participants (N = 409)

Characteristic n %
College Level
Community College 299 73
Undergraduate 65 16
Graduate 45 11
Gender
Female 231 57
Male 175 43
Ethnicity
Hispanic/Latino 164 41
Asian 85 21
White 73 18
Two or More Races 29 7
Black/African-American 22 5
Other 16 4
American Indian 11 3
Native Hawaiian/Other Pacific Islander 5 1
Employment Status
Not Working 190 46
Part-Time 140 35
Full-Time 77 19
Relationship Status
Single 325 80
Married/Domestic Partner 67 17
Separated/Divorced 14 3
Previous Online Course Experience
No 183 51
Yes 172 49
Note. Totals of percentages are not 100 for every characteristic because of rounding.
Table 5 summarizes the number of participants by course delivery and reason for
selecting the delivery method. The majority of the participants (n=245, 59%) were enrolled in
the on-campus course. Majority of the participants (68%) selected the particular course delivery
method due to schedule. The next two selected reasons for choosing the course delivery method
were due to quality of instruction (36%) and professional responsibilities (21%). Of the
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 38
participants enrolled in the on-campus course offering, 123 (50%) selected quality of instruction
as the reason for choosing the format.
Table 4
Age of Participants by Institution and Course Delivery (N=409)
Institution
Course Delivery
Asynchronous Online Synchronous Online On-Campus
Age (M) SD Age (M) SD Age (M) SD
A 23.8 7.63 -- -- 22.8 7.04
B 26.4 4.76 -- -- 22.5 5.55
C 24.2 5.27 -- -- 20.9 1.82
D 38.7 10.4 -- -- 39.2 10.8
E -- -- 30.2 8.31 26.2 4.78

Table 5
Participants by Course Delivery Method and Reason for Selecting Delivery Method (N = 409)

Characteristic n %
Course Delivery
On-Campus 245 60
Asynchronous Online 131 32
Synchronous Online 30 7
Reason for Selecting Course Delivery
Schedule 277 68
Quality of Instruction 146 36
Professional 85 21
Family Responsibility 71 17
Geography 63 15
Note. Totals of percentages are not 100 for every characteristic because of rounding.
Instrumentation

These research questions were answered by a 31-item metric composed of four survey
instruments and several demographic questions. The survey instruments were used to measure
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 39
student satisfaction (adapted from Arbaugh, 2000), self-efficacy (from Pintrich et al., 1991),
voluntary collaboration, and help-seeking (from Pintrich et al., 1991). The survey items utilized
for this research study was included in surveys distributed by other doctorate student researchers
at a total of five different higher education institutions.
Demographic questions. In order to understand the demographic composition of the
students, several demographic questions were asked on the self-report survey. Demographic
questions included age, gender, ethnicity, relationship status, employment status, parents’ level
of education, course load and reasons for choosing either the online or on-campus format of the
course.
Student satisfaction. A six-item survey was utilized to measure student satisfaction.
The original survey utilized by Arbaugh (2000) had 12 items and a Likert scale with seven
choices. The original scale had a Cronbach’s alpha of .96. Due to the high Cronbach’s alpha,
the five most relevant questions from the original 12 items were chosen for the survey.
Additionally, minor modifications were made by changing the wording “via the internet” to “in
this format” to improve the relevance of the questions to the study. One of the questions was
developed as a control item regarding the instructor (I would take another course with this
instructor). The Cronbach’s alpha of the new subscale utilized for this study was .88. Sample
items included: I am satisfied with my decision to take the course in this format; I feel the quality
of the course I took was largely enhanced by the format; I would take another course with this
instructor.
Self-efficacy. Self-efficacy was measured with the 8-item Self-Efficacy for Learning and
Performance subscale of the Motivated Strategies for Learning Questionnaire (MSLQ)
developed by Pintrich et al. (1991). The original subscale had a Cronbach’s alpha of .93. Minor
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 40
modifications were made to the subscale by changing the word “class” to “course” to improve
the relevance of the question to the population of the study. The Cronbach’s alpha of the
subscale utilized in the study was .97. Sample items included: I believe I will receive an
excellent grade in this course; I’m certain I can master the skills being taught in this course.
Help-seeking. Three different types of questions will be utilized to measure help-
seeking. A total of seven questions will be asked in the self-report survey to measure help-
seeking beliefs. Questions will also be asked to measure the student’s behavior, which will
include the frequency of help-seeking and the mode of contact used in help-seeking.
Beliefs. Two different subscales will be combined to measure help-seeking beliefs. One
of the subscales utilized will be from the MSLQ (Pintrinch et al., 1991), which consisted of 4
items and had a Cronbach’s alpha of .52. With the elimination of the reverse coded item (Even if
I have trouble learning the material in this class, it is important that I try to do the work on my
own, without help from anyone.), the Cronbach’s alpha for the study was .77. The subscale
measured general help-seeking beliefs. Sample items included: If I don’t understand the material
in this course, it is important that I ask another student in this class for help; It is important to
identify students in this class whom I can ask for help if necessary.
In addition, the informal versus formal help-seeking subscale from Karabenick (2003)
was included, which had 3 items and a Cronbach’s alpha of .66. The original help-seeking scale
(Karabenick, 2003) comprised of five subscales however, due to the focus of the study, only the
formal versus informal help-seeking subscale was utilized. In the study, one of the questions
were eliminated (I would prefer asking another student for help in this class rather than the
instructor) and resulted in a Cronbach’s alpha of .68.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 41
Frequency. The frequency of help-seeking behavior was measured utilizing a question
developed collaboratively with the other doctorate student researchers in the thematic
dissertation group, which was revised and approved by the two thematic dissertation group
faculty chairs. The questions gathered data on how often the student’s actually sought help
during the course from instructors, peers, and others. The answers were divided into five
categories of 1-2 times per semester, 1-2 times per month, once a week, and more than once a
week.
Mode of contact. In addition, the mode of contact utilized by the student’s to seek help
from instructor, peer, or other was asked. The methods of contacts provided were in-person,
phone, text, email, and discussion board.
Voluntary collaboration. A 5-item survey was developed collaboratively as a thematic
dissertation group under the guidance of the faculty chairs to assess student’s beliefs on
voluntary collaboration with peers, the frequency students voluntarily collaborated with their
peers, and the mode of contact used to voluntarily collaborate. The survey was developed since
the group was unable to locate a scale that measured voluntary collaboration.
Beliefs. The belief scale consisted of 3 items. Sample items include: It is important to
collaborate with my peers in this course even if it is not requires; I believe that teaching and
learning from each other is important to succeed in this course/program; It is important to both
give and receive peer feedback related to work in this course/program. The survey was piloted
in a graduate level education course, which resulted in a Cronbach’s alpha of .93. In the study,
the Cronbach’s alpha was .96.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 42
Frequency. The frequency of voluntary peer collaboration will be measured with a
question asked on the post assessment only. It will ask student’s to indicate the frequency they
voluntarily collaborated with peers during the semester.
Mode of contact. The survey included a question on the mode of contact utilized by the
student to voluntarily collaborate with their peers. They were asked to provide all mode of
contacts utilized to voluntarily collaborate with their peers.
Procedure and Data Collection
The questions specific to this study were included on surveys of five other researchers in
a thematic dissertation group conducting studies on differences between online learning and on-
campus courses. The surveys were conducted collaboratively with the other researchers and
included data collected for their study purposes. Therefore, approval from IRB was obtained for
the study by including a description for the framework of this study and listing the researcher as
a Co-Principal Investigator on the IRB application for each of the other researchers’ studies. The
researchers also obtained proper permission for data collection from the course instructors.
The data was collected at various times dependent on the duration of the course towards
the end of the course. An online survey tool was utilized to collect the data for both the online
and on-campus course offerings. The online survey was created utilizing Qualtrics and
administered through a link sent to the student’s email by the instructor. Participation in the
study was voluntary, however an opportunity drawing was offered as an incentive for those who
participated.
Data Analysis
The collected data was downloaded from Qualtrics and analyzed utilizing SPSS and
appropriate statistical tests. As shown in Table 6, the data was analyzed utilizing an
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 43
independent samples’ t-test, ANOVA, ANCOVA, correlation, chi square, and multiple
regressions dependent on the research question and variable measured. An independent samples’
t-test, ANOVA, or ANCOVA was utilized to analyze the difference in student satisfaction by
delivery method and demographic characteristics. Correlations were utilized to analyze
relationships between the interval variables and multiple regression analysis was conducted to
determine the attribution of the variance in student satisfaction by self-efficacy, voluntary
collaboration, and help-seeking, while controlling for delivery method.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 44
Table 6
Research Questions, Variables, and Statistical Analysis Matrix
Research Question IV(s) DV(s) Statistical Test
1. Are there differences in
student satisfaction by
delivery method?
Program delivery
method
Student
satisfaction
Independent samples’
t-test and ANCOVA
2. Are there differences in
students’ level of satisfaction
based on their demographic
characteristics?
Demographic
characteristics
Student
satisfaction
ANOVA or
Independent samples’
t-test
3. Does self-efficacy predict
student satisfaction,
controlling for delivery
method?
Self-efficacy Student
satisfaction
Multiple Regression
4. Do voluntary collaboration
beliefs and behaviors predict
student satisfaction,
controlling for delivery
method?
Voluntary
collaboration
beliefs &
behaviors

Student
satisfaction
Multiple Regression

5. Do help-seeking beliefs and
behaviors predict student
satisfaction, controlling for
delivery method?
Help-seeking
beliefs &
behaviors
Student
satisfaction
Multiple Regression

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 45
CHAPTER FOUR
This study examined the differences in student satisfaction between online and on-campus
delivery methods of courses based on demographic factors and motivation variables. The
research questions developed were based on the constructs: student self-efficacy, voluntary
collaboration, and help-seeking potentially related to student satisfaction. Specifically, this study
was designed to answer the following research questions:
1. Are there differences in student satisfaction by delivery method?
2. Are there differences in students’ level of satisfaction based on their demographic
characteristics?
3. Does self-efficacy predict student satisfaction, controlling for delivery method?
4. Do voluntary collaboration beliefs and behaviors predict student satisfaction, controlling
for delivery method?
5. Do help-seeking beliefs and behaviors predict student satisfaction, controlling for
delivery method?
Results
The purpose of this chapter is to report the findings of this study. The first section will
provide an analysis of the demographic characteristics of the respondents. This is followed by a
preliminary analysis of the data and results of statistical analyses organized by research question.
Demographic Analysis
Analysis of the demographic characteristics resulted in significant differences between
the course delivery methods. The demographic characteristics of the participants by course
delivery were presented in Table 7. The Pearson Chi Square test was utilized to further analyze
the categorical demographic characteristics of the participants in the three different course
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 46
delivery methods. The majority of the single participants (n=203, 64%) were in the on-campus
course and 61% (n=40) of the participants who were married or had a domestic partner were
taking either the asynchronous or synchronous online course. The majority of the participants
that were in the on-campus course were not working (n=129, 68%), while more than half of
those working full time (n=44, 57%) were enrolled in the online course. Of the participants who
were in the online course, 70% (n=90) had previously taken at least one online course, while
79% (n=143) of those who had reported never taking an online course were in the on-campus
course.
The chi-square test was performed to examine the relationship between demographic
characteristics and course delivery method chosen. The results of the analysis showed a strong
significant relationship between the course delivery method and the participants’ employment
status, X
2
(4, N=404) = 18.45, p<.001; relationship status, X
2
(4, N=403) = 21.08, p<.001; and
previous online course experience, X
2
(1, N=352) = 38.03, p<.001. Participants who would
more likely choose the online course delivery method were working or had previously taken an
online course, while students who were single were more likely to be in an on-campus course.
One-way ANOVA was utilized to analyze differences in age and units by course delivery
method. There was a significant difference found between the age of the participants between
the asynchronous online (M = 27, SD = 8.22), synchronous online (M =30, SD = 8.31) and on-
campus course (M = 24, SD = 7.52) delivery methods. The mean age of participants in the
asynchronous online course was 27 and 30 for the synchronous online, while the on-campus
course had a mean age of 24. The asynchronous and synchronous online course participants
were significantly older than those participants from the on-campus course (F(2,397) = 12.4,
p<.05). However, there was no significant difference in the mean age between the asynchronous
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 47
and synchronous online courses. Additionally, there was no significant difference in the number
of units participants were enrolled in between the different course delivery methods.
Table 7
Demographic Characteristics of Participants by Course Delivery Method

Online
On-Campus
Asynchronous Synchronous
Characteristics n % n % n %
Gender
Female 77 34 17 7 135 59
Male 53 30 13 7 108 62
Relationship Status
Single 96 30 17 5 210 65
Married/Domestic Partner 28 42 12 18 26 39
Separated/Divorced 5 36 1 7 8 57
Employment Status
Not Working 45 24 15 8 129 68
Part-Time 46 33 9 7 83 60
Full-Time 39 51 5 6 33 43
Previous Online
No 38 21 -- -- 143 79
Yes 90 53 -- -- 81 47

In summary, there were significant demographic characteristic associations and
differences found between the online and on-campus participants. The participants from the
online course were significantly older, married or had a domestic partner, more likely to be
working full-time, and previous experience with online courses.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 48
Analysis of Results
The data collected through self-report instruments for this study was analyzed to address
the research questions proposed in this study. A preliminary analysis of means, standard
deviations, and correlations were conducted on the measured construct variables. The results of
the preliminary analyses are presented followed by the findings organized by the five research
questions.
The results of a preliminary analysis of the mean, standard deviation, and correlations of
measured variables are presented in Tables 8, 9, and 10. A subset of participants from the
sample (n=331) were administered the items from the self-efficacy scale presented in Table 6.
Satisfaction was significantly correlated with self-efficacy, age, and previous online experience.
The results indicated that the older participants reported higher satisfaction. Self-efficacy and
previous online experience were positively related to satisfaction. The age of the participant had
a strong negative association with the number of enrolled units (r = -.350, p<.01) and a positive
association with previous online courses (r = .192, p<.01). The results shows that older
participants enrolled in fewer units, however, had previously taken more online courses. There
were no significant associations of age, units enrolled, and previous online courses with self-
efficacy.
The results presented in Table 9 are from the subset of the participant sample (n=368)
that answered the items for the help-seeking scale. The results showed a positive significant
correlation of satisfaction with general help-seeking beliefs (General HS, r = .127, p<.05), age (r
= .166, p<.01), and previous online course experience (r = .136, p<.05), indicating that
participants who were older, had higher general help-seeking beliefs, and more previous online
course experience reported higher levels of satisfaction. The general help-seeking beliefs were
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 49
significantly negatively related to age (r = -.118, p<.05), signifying that older participants had
lower help-seeking beliefs. There was a strong significant negative association between age and
number of enrolled units (r = -.350, p<.01) and a positive association with previous online
experience (r = .269, p<.01), consistent with the results found with the self-efficacy subsample.
There were no significant correlations found between satisfaction, formal versus informal help-
seeking beliefs (Formal HS), and enrolled units. Furthermore, formal versus informal help-
seeking beliefs had no significant association with any of the demographic characteristics and the
correlation between enrolled units and previous online experience was not significant.
Table 8
Means, Standard Deviations, and Intercorrelations Between Measured Satisfaction, Self-
efficacy, and Demographic Characteristics (n=331)

Measure M SD 1 2 3 4 5
1. Satisfaction 3.97 .88 - .534** .131* -.073 .114*
2. Self-efficacy 4.02 .77 - .024 .016 -.009
3. Age 23.3 6.40 - -.350** .192**
4. Units 11.8 3.46 - -.022
5. Previous Online 1.07 1.72 -
* p<.05 **p<.01

The results of the means, standard deviations, and intercorrelations from the subset of the
sample (n=75) administered the voluntary collaboration scale is presented in Table 10. There
was a significant negative correlation found between satisfaction and enrolled units (r = -.325,
p<.05), indicating that in this sample of participants, those who were enrolled in more courses
reported lower levels of satisfaction with the course. There were no significant associations
between satisfaction, voluntary collaboration, age, and previous online experience.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 50
Table 9
Means, Standard Deviations, and Intercorrelations Between Measured Satisfaction, Two
Subscales of Help-seeking, and Demographic Characteristics (n=361)

Measure M SD 1 2 3 4 5 6
1. Satisfaction 4.01 .86 - .127* .078 .166** -.073 .136*
2. General HS 3.98 .76 - .152* -.118* .106 -.060
3. Formal HS 3.84 .92 - .041 -.049 .046
4. Age 24.6 7.98 - -.350** .269**
5. Units 11.8 3.46 - -.022
6. Previous Online 1.20 1.83 -
* p<.05 *p<.01

Table 10
Means, Standard Deviations, and Intercorrelations Between Measured Variables Satisfaction,
Voluntary Collaboration, and Demographic Characteristics (n=75)

Measure M SD 1 2 3 4 5
1. Satisfaction 4.21 .76 - .191 .176 -.325* .006
2. Voluntary Collaboration 4.24 .81 - -.153 -.085 .110
3. Age 32.78 9.98 - -.184 -.006
4. Units 8.80 2.39 - -
5. Previous Online 3.04 2.22 -
* p<.05
Research question 1: Are there differences in student satisfaction by delivery
method? The student satisfaction items adapted from Arbaugh (2000) were utilized to collect
the data to determine whether there was a difference in the satisfaction across the course delivery
methods. The mean and standard deviation of the reported student satisfaction by course
delivery method is presented in Table 11. An analysis of covariance was conducted to
investigate student satisfaction differences in the three course delivery methods (asynchronous
online, synchronous online, and on-campus) by institution with a covariate of instructor
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 51
satisfaction. After adjustment by the covariate, satisfaction significantly varied by course
delivery method (F(2, 391) = 4.53, p<.01, partial n
2
=.035) and by institution (F(4, 391) = 3.57,
p<.05, partial n
2
=.023). The participants in the on-campus delivery method of the course
reported higher satisfaction than those enrolled in the online version of the course, when the data
from the asynchronous and synchronous online participates was combined.
The five different institutions participating in the study had differing sub-samples, course
levels, and online delivery methods. Therefore, an independent sample t-test was conducted to
determine if there were differences in student satisfaction between the online and on-campus
course at each institution. The results of the analysis found a significant difference in the student
satisfaction between asynchronous online and on-campus courses for Institution A (t(169) =
.114, p<.001), Institution B (t(123) = 2.69, p<.001), and Institution C (t(32) = 2.13, p<.05).
Although the mean of student satisfaction reported was higher for on-campus course than the
online course, there were no significant difference in student satisfaction found for Institution D,
which was an asynchronous online undergraduate course with participants that were significantly
older. Institution E, which was a synchronous online, graduate level course, also had no
significant difference in satisfaction.
Research question 2: Are there differences in students’ level of satisfaction based on
their demographic characteristics? The demographic characteristic data collected from the
participants (N=409) were analyzed to determine differences in student satisfaction. Table 12
presents the mean and standard deviation of the student satisfaction for demographic
characteristics found to have significant differences. One-way ANOVA was conducted with the
dependent variable of student satisfaction and independent variables of ethnicity, parent
education, and college level. There was no significant difference found in student satisfaction by
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 52
ethnicity, parent education, or college level. An independent sample t-test was conducted to
determine differences in student satisfaction by gender (t(400) = .681, p=.190) and previous
online experience (t(353) = 2.873, p=.331) however, no significant differences were found.
Table 11
Mean Student Satisfaction by Institution and Course Delivery Method (N=409)

Institution
Student Satisfaction
Online
On-Campus
Asynchronous Synchronous
M SD M SD M SD
A 4.04 1.13 -- -- 4.02 .66
B 3.76 1.01 -- -- 4.15 .59
C 3.21 1.39 -- -- 4.13 .98
D 4.33 .62 -- -- 4.56 .57
E -- -- 4.01 .69 4.16 1.07

In an effort to distinguish the reported student satisfaction between the course and
instruction, an analysis of covariance was conducted controlling for the covariate of instructor
satisfaction for employment status, and relationship status. After adjustment by the covariate,
there were no significant differences found in satisfaction by relationship status (F(2, 390) =
2.51, p=.082, partial n
2
=.013) and employment status (F(2, 390) = 2.29, p=.103, partial n
2
=.012).
This means that after adjusting the reported student satisfaction attributed to the instructor, there
was no significant difference based on employment or relationship status.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 53
Table 12
Mean Student Satisfaction by Employment and Relationship Status

Characteristic
Student Satisfaction
M SD n
Employment Status
Not Working 3.98 .808 190
Part-time 3.93 .954 143
Full-time 4.26 .763 79
Relationship Status
Single 3.93 .870 324
Married/Domestic Partner 4.38 .735 67
Separated/Divorced 4.20 .752 14

Research question 3: Does self-efficacy predict student satisfaction, controlling
for delivery method? In the preliminary analysis of the data presented at the beginning of this
section, there was a strong significant relationship found between self-efficacy and student
satisfaction. To further investigate the correlation, a multiple regression was conducted to
determine if self-efficacy was a predictive variable of student satisfaction controlling for course
delivery method. The regression results indicated that self-efficacy significantly predicted
student satisfaction, R
2
=.296, R
2
adj
=.292, F(2,326)=68.69, p<.001. This means that students with
higher self-efficacy were more likely to be more satisfied. Specifically, self-efficacy accounted
for 29.6% of variance in student satisfaction and course delivery accounted for 2.1%.

Research question 4: Do voluntary collaboration beliefs and behaviors predict
student satisfactions, controlling for delivery method? Although the preliminary analysis
showed no correlation of student satisfaction with voluntary collaboration beliefs, a regression
was conducted controlling for the delivery method to further investigate. The results of the
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 54
regression indicated that voluntary collaboration and delivery method were not predictors of
student satisfaction, R
2
=.058, R
2
adj
=.032, F(2,72)=2.22, p=.116. The delivery method accounted
for 2.3% of variance in satisfaction and voluntary collaboration beliefs accounted for an
additional 3.5% of variance while voluntary collaboration behaviors accounted for an additional
1.5%, which was not statistically significant. The behavior data was collected utilizing an item
on the survey that asked how often the participants collaborated voluntarily, however after
conducting one-way ANOVA, no significant difference in student satisfaction was found.
Research question 5: Do help-seeking beliefs and behaviors predict student
satisfaction, controlling for delivery method? The preliminary analysis found no significant
relationship between student satisfaction and either of the two help-seeking belief subscales.
Further analysis found a relationship between student satisfaction and help-seeking behavior
measured by how often the participant sought help from an instructor. One-way ANOVA
resulted in a significant difference in student satisfaction between participants who did not seek
help from an instructor at all and those who reported seeking help one to two times per week
from their instructor (F(4,351)=2.869, p<.05). The results show participants that seek help from
their instructor 1-2 times per week reported higher levels of satisfaction with the course. A
multiple regression was performed to investigate the predictability of satisfaction by measuring
help-seeking. The regression results indicated that an overall model of three predictors (general
help-seeking beliefs, formal help-seeking beliefs, and help-seeking behavior from instructor)
significantly predicted student satisfaction, R
2
=.039, R
2
adj
=.028, F(4,336)=2.906, p<.05. The
results showed that the when controlling for delivery method, the three help-seeking variables
significantly predicted 3.9% of the variance in student satisfaction.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 55
In summary, this chapter reported the results of the statistical analyses performed to
investigate the research questions proposed in this study. The results showed a significant
difference in the student satisfaction between the online and on-campus delivery methods.
The analysis of the demographic characteristics of the participants found that students in the
online delivery method were older, more likely to be married or have a domestic partner, and
work full-time. The same demographic characteristics: older, married or have a domestic
partner, and work full-time also reported higher levels of satisfaction, however the on-campus
delivery method had significantly higher levels of student satisfaction than the online delivery
method. The regression analysis identified self-efficacy and help-seeking beliefs and behavior
measures as significant predictors of student satisfaction. The implications of these results will
be discussed in the next chapter.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 56
CHAPTER FIVE
Discussion
This section begins with an overview and discussion of the results. The findings will be
examined to understand the impact of demographic characteristics and learning environments on
student satisfaction. The constructs of self-efficacy, formal and informal help-seeking, and
voluntary collaboration as measured in the study will also be discussed in relation to satisfaction.
The chapter will conclude with implications, limitations, and recommendations for future
research.
The purpose of the study was to examine student satisfaction in relation to course
delivery method, student demographic characteristics, and three constructs of instructional
effectiveness. The three motivational constructs included self-efficacy, voluntary collaboration
with peers, and formal and informal help-seeking. The research questions for this study were
developed to address the gaps identified from the literature review, inconsistencies in the
findings, and further the understanding of determining factors of student satisfaction as a
significant measure of retention. The following section provides a discussion of the results from
this study based on the research questions.
Satisfaction by Delivery Method
The study results indicated a significant difference in student satisfaction between the
online and on-campus delivery methods when synchronous and asynchronous online course
offerings were combined in the analysis. Also, the students in the on-campus delivery method
reported higher satisfaction than those enrolled online for the asynchronous offerings. This
finding is contradictory to previous research studies (Abdous & Yoshimura, 2010; Arbaugh &
Duray, 2002) that found no difference in course satisfaction based on delivery methods.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 57
However, the difference in satisfaction might be attributed to the differences in the design of the
online learning course offerings since there are three distinct types: asynchronous, synchronous,
and hybrid or blended online learning (Allen & Seaman, 2014) with differing barriers,
advantages, and outcomes (Sundt, 2014). The results of the analysis conducted in the study on
the difference of student satisfaction between online and on-campus by institution showed that
significant differences were only found in three of the institutions. The three institutions with
significant differences in satisfaction between the two different delivery methods of the same
course had an asynchronous online course. Sundt (2014) had noted that there were differences in
retention and outcomes between asynchronous and synchronous online courses. Since no
significant difference in satisfaction was found in the institution (E), which was a synchronous
online course, this result seems to support this statement. However, the other institution (D),
which had an asynchronous online course, also had no significant difference in student
satisfaction in comparison to the on-campus course offering. However, this might be attributed
to the significantly higher mean age of the participants and that they were registered in an online
program, which happened to offer an on-campus course.
Similarly, Clark (2004) attributed differences in learning outcome to instruction and not
the delivery method. Previous studies have reported concerns regarding the quality of online
courses. Picciano and colleagues (2010) indicated that even though more than half of the faculty
would recommend online courses to students, the majority (77%) thought they were inferior to
face-to-face courses. Student satisfaction has been found to be associated with learning outcome
(Bollinger & Martindale, 2004; Swan, 2001; Wang et al., 2013) and the finding of this study that
there is a significant difference in student satisfaction between asynchronous online and on-
campus courses might seem to support the perception that online learning is inferior to face-to-
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 58
face. In addition, the study found that a majority of participants who selected to take the on-
campus course also noted that instructional considerations (e.g., preferred method of instruction,
quality of instruction, access to instructor) were a reason for selecting the delivery method.
However, learning outcome was not measured in this study and there were other potential
contributing factors for the observed difference in student satisfaction.
The resulting difference in the satisfaction between the asynchronous online and on-
campus courses may also be attributed to the relationship found between certain demographic
characteristics and course delivery method chosen. The results showed a strong relationship
between the course delivery method and employment, relationship status, and previous online
course experience. Those that were married or had a domestic partner, working, or previously
taken online courses were more likely to choose to the online course delivery. There was a
significant difference in the mean age of those taking online courses compared to on-campus
courses. The online course participants were older than those from the on-campus course. This
was an expected result since online education has increased access for non-traditional students
(Chen et al., 2010; Picciano et al., 2010). Also, the majority of participants designated
scheduling as a reason for selecting the course format. This was expected since in previous
studies (Means et al., 2010; Picciano et al., 2010) convenience or flexibility in schedule was
found to be one of the key factors for selecting the online course. In addition, Arbaugh and
Duray (2002) had associated schedule flexibility with higher satisfaction with the online delivery
method.
Demographic Characteristics and Satisfaction
The demographic characteristics of the participants were analyzed for relationships to
satisfaction. There were significant correlations found between satisfaction and age and previous
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 59
online experience. The results indicated that older participants reported higher satisfaction. This
finding supports the results of Shea and Bidjerano (2008) and Liu and Jung (1980), where it was
also found that older students tended to report greater satisfaction with online courses. Although
Cole and colleagues (2014) had found no significant difference in satisfaction by age, they had
measured age by categorizing participants into generations. Therefore, the different measure of
age might account for the discrepancy found from this study.
In the study, older participants enrolled in less units, however, had previously taken more
online courses. Those enrolled in more courses reported lower levels of satisfaction.
Participants working full-time reported being more satisfied than those only working part-time or
not working at all. The participants in the relationship category single, reported lower levels of
satisfaction than those married or with a domestic partner. This was consistent with the findings
of Bequiri and colleagues (2010) that found that married students were significantly more
satisfied with online courses than single students. This finding might be related to the
convenience and flexibility of schedule that online courses offer, which Lou et al. (2011) had
found to be positively correlated with satisfaction. However, when the covariate of instructor
satisfaction was controlled, there was no significant difference in satisfaction found by
relationship or employment status. Therefore, the instructor satisfaction might attribute to the
difference in satisfaction found without the control.
This study found a difference in the student satisfaction between online (asynchronous
and synchronous) and on-campus courses. However, there was no significant different between
the two types of online courses. Further analysis by institution found that student satisfaction
from three (Institution A, B, and C) of the five institutions (two community colleges and one
public 4-year institution) were significantly different between their asynchronous online and on-
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 60
campus courses. Since all three of the online learning courses were asynchronous, this finding
was expected. Shea and Bidjerano (2008) suggested that younger generation students were
unlikely to be satisfied with asynchronous online learning because text-based courses would not
engage this generation that grew up immersed in interactive technology. Also, the findings from
this study align with Shea and Bidjerano (2008), since the students in the community colleges
and public 4-year institution were younger than the other two institutions. Although the online
course from Institution D was also an asynchronous online course, the mean age of the
participants were at least 10 years older than the participants from Institution A, B, and C.
In examining the impact of gender on student satisfaction, this study found no differences
in satisfaction by gender. Although Bequiri and colleagues (2010) found that male students
reported higher satisfaction with online courses than female students, that was not supported by
this study. However, there were inconsistent findings on the significance of gender on
satisfaction and the results from the study further support other studies that found no difference
between gender and satisfaction (Arbaugh, 2000; Cole et al., 2014; McFarland & Hamilton,
2005).
Self-efficacy, Voluntary Collaboration, and Help-Seeking Related to Satisfaction
The findings from this study supported the results of the study conducted by many
researchers (Palmer & Holt, 2008; Shea & Bidjerano, 2010; Shen et al., 2013) where a
significant correlation between self-efficacy and satisfaction was also found. The results also
showed that self-efficacy was a strong predictive variable of student satisfaction. Although self-
efficacy related to specific tasks had previously been found to predict student satisfaction, this
study measured self-efficacy in learning and performance (Pintrich et al., 1991) and discovered
that more than one-fourth of the variance in satisfaction was attributed to self-efficacy.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 61
In this study, there was no significant relationship between satisfaction, formal and
informal help-seeking and voluntary collaboration found. However, participants that sought help
from their instructor reported higher levels of satisfaction with the course. This finding was
expected since they were similar to the results of the Abdous and Yen (2010) study, in which
they found learner-to-teacher interactions were significantly related to positive student
satisfaction. The findings of the regression analysis in this study, which indicated that the
overall model of three predictor variables: general and formal help-seeking and help-seeking
behavior significantly predicted student satisfaction. General help-seeking beliefs were lower in
older participants.
Implications
The increasing demand for online courses, evidence of low retention rates, and
inconsistent findings in the research make studies in this area highly relevant to the field. This
study yielded important implications for the design of future online courses to increase
satisfaction as an important factor for student retention. Since significant differences in
satisfaction were found in the study between online and on-campus courses and there were two
demographic characteristics (age and previous online experience) identified as contributing
factors, designing online courses with these demographic characteristics as targeted students
would be recommended. Also, self-efficacy and help-seeking were two constructs that were
predictors of student satisfaction. Therefore, the researcher recommends the following to
instructors, administrators, and instructional designers of online courses:
• Conduct trainings for instructors on designing online courses, which would include
structuring the course for optimal learning and planning activities that increase self-
efficacy, as explained by Bandura (1993), throughout the course since this study found it
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 62
to be a strong predictor of student satisfaction. For example, the instructor could design
learning activities that are goal directed and challenging, but allows for successful
completion with little assistance or have learners perform difficult tasks in groups. The
course design could also allow for instructor to provide opportunities for observing
positive models and provide instructional support early in the course, balancing the areas
of improvement with positive feedback that are timely. Also, ensure that technology is
utilized to support the learning and not for the sake of using technology. For example,
purposefully utilize the tools to support good teaching principles and incorporate into
course design effectively.
• Providing opportunities for students to take the online courses at their convenience with a
schedule that is flexible since this was the reason why majority of participants chose the
course format.
• Encouraging and providing opportunities for students to interact with instructors and
peers since help-seeking beliefs and behaviors were found to be a predictor of student
satisfaction. Some specific strategies include having posted office hours and being
available during those times; responding to students in timely manner; discussing help-
seeking as a positive behavior; and positively reinforcing the behavior
• Incorporating assignments that include interaction with classmates. For example, group
projects; small group discussions, and presentations.
• Promote help-seeking behaviors by having one-on-one interactions with students early on
in the course. For example, after submission of the first assignment, schedule
appointments with the students to reviewing the grading of the assignment with them and
provide a balance of positive feedback with areas that need improvement.
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 63
These recommendations are designed to increase instructional effectiveness as an influential
factor of student satisfaction. Implementing these recommendations in the design of online
courses may increase satisfaction and decrease attrition rates.
Limitations
The design of the study has a range of limitations. One major limitation was that it was a
correlational study; therefore no causal relationships were determined. The researcher was only
able to determine if the independent and dependent variables were related and could not
conclude that the changes in the dependent variables were a result of the independent variables.
The participants were asked to self-report their perceptions, belief and behaviors. Therefore, the
study has limitations related to honesty and social desirability. The researcher could not
determine if the participants honestly completed the survey. Social desirability bias could have
occurred when participants reported answers they believed were acceptable. Participants may
have also misinterpreted questions, answered them inaccurately or had someone else complete
the survey since it was administered online. Since the participants were not randomly assigned
and given the choice to take the course online or in-person, the study also has limitations due to
self-selection biases. Self-selection bias occurs when individuals voluntarily assign themselves
into a group, which could have caused a biased sample. Participants who chose to complete the
survey may not have accurately represented the student population. Limitations of this study
could have compromised the results and led to incorrect or limited conclusions. Another
limitation of the study was the one time collection of data with different surveys. Since the data
for this study was collected in collaboration with other doctorate candidate researchers in a
thematic dissertation cohort studying different constructs, the sample size for each construct
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 64
were different and the type of online course differed from completely asynchronous to partially
synchronous or hybrid.
Although the study has several limitations, the researcher controlled several factors such as
how many participants received the survey to ensure adequate sample size, how the survey was
administered, what topics the survey addressed and how the questions are asked. To control how
the questions are asked, the researcher carefully developed the questions based on existing valid
and reliable surveys and distributed the same survey to the same subset of participants.
Moreover, an information sheet was attached explaining the confidentiality of the study between
the researcher and the participants. The factors controlled by the researcher provided internal
and external validity as well as reliability by reducing the possible limitations of the study.
Recommendations for Future Research
The significant increase in online learning courses and lower retention rates underscores
the need for comparative studies examining the factors influencing student satisfaction across
course delivery methods. Future research that expands upon the constructs examined in this
study is essential to better understand motivational factors for students enrolled in courses
offered through different delivery methods and increase instructional effectiveness. It is
suggested that future studies utilize consistent survey items and measure the same constructs
across the entire population sample to avoid the different sample subsets in this study. Also,
expanding the data collected on these constructs by including qualitative survey items and
conducting it as a longitudinal study would provide insights that are difficult to conclude with a
quantitative one-time study.
Another suggestion for further study is to continue to replicate this work across different
populations and increase the sample size. Although this study incorporated three different levels
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 65
of higher education and a variety of types of higher education institutions, the sample size for the
synchronous online learning course was small. A larger sample size with similar number of
participants from the different delivery methods in future studies could validate and make these
findings generalizable. It would also assist in providing more evidence to settle the inconsistent
findings in the research. An additional recommendation for future studies is study all three types
of online learning (asynchronous, synchronous, and hybrid) in comparison to on-campus.
Finally, an experimental study is recommended to determine causal relationships.
Although this might be difficult, future studies could randomly assign students to either the
online or on-campus course, ensure the two offerings have the same instructional design and
have the courses taught by the same instructor.
Conclusion
The purpose of this study was to examine differences in satisfaction between students
enrolled in online versus on-campus courses and determine if differences exist based to
demographic characteristics. The study also assessed if self-efficacy, volunteer collaboration,
and help-seeking beliefs and behaviors were predictors of satisfactions. The data was collected
collaboratively with five other researchers of a thematic dissertation group and included
participants from five different higher education institutions. The study was partly in response to
inconsistent findings in research examining the current state of online learning and evidence of
low retention rates, which student satisfaction was a strong determinant. Overall, the study
found statistical differences in student satisfaction between online and on-campus courses when
asynchronous and synchronous online offerings were combined. However, further analysis of
the data collected by institution also found that the significant differences were found with those
STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 66
online courses that were asynchronous and not those that were synchronous. The results of this
study also found help-seeking and self-efficacy were predictors of student satisfaction.
With the increased number of institutions offering and students taking online learning
courses, considering the findings of this study in designing online learning courses are
recommended. As discussed, the implications of the findings are significant and relevant to the
growing field of online learning and ensuring critical factors are considered in developing an
effective learning environment.

STUDENT SATISFACTION WITH ONLINE AND ON-CAMPUS 67
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Abstract (if available)

Abstract The higher demand for online learning has impacted the higher education institutions to offer more online learning courses. The enrollment rates for online learning continue to increase and the proportion of students taking at least one online course is at an all-time high. However, the low retention rates of online courses are concerning higher education institutions. One of the strongest determinants of student retention has been found to be student satisfaction. Therefore, this study examines the literature surrounding online learning in higher education, student satisfaction, and factors of student satisfaction. In particular, demographic characteristics, self-efficacy, help-seeking beliefs and behaviors, and voluntary collaboration were studied in the current research. This study compared these constructs between online and on-campus offerings of a course across five different institutions and levels of higher education. ❧ The study results indicated that there was a significant difference in student satisfaction between the on-campus and online when participants in both asynchronous and synchronous are considered together. However, since the sample sizes and design of the online learning were different between the institutions, further analysis was conducted to investigate the difference in student satisfaction by institutions. The results showed a statistically significant difference for institutions that offered a completely asynchronous online course and no differences were found in satisfaction for online courses that were synchronous. Overall, the study also yielded no significant differences in student satisfaction based on some demographic characteristics and found that self-efficacy and help-seeking were predictors of satisfaction. The implications of this study can be valuable in the field of education as more higher education institutions create online learning opportunities to reach a diverse student population.

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Creator Kim, Jee Eun (author)

Core Title A comparative study of motivational predictors and differences of student satisfaction between online learning and on-campus courses

School Rossier School of Education

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Publication Date 07/15/2015

Defense Date 05/11/2015

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