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Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Online Course Delivery: An Empirical Investigation
of Factors Affecting Student Satisfaction
Mirjeta S. Beqiri , Nancy M. Chase & Atena Bishka
To cite this article: Mirjeta S. Beqiri , Nancy M. Chase & Atena Bishka (2009) Online Course
Delivery: An Empirical Investigation of Factors Affecting Student Satisfaction, Journal of
Education for Business, 85:2, 95-100, DOI: 10.1080/08832320903258527
To link to this article: http://dx.doi.org/10.1080/08832320903258527
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Date: 11 January 2016, At: 22:28
JOURNAL OF EDUCATION FOR BUSINESS, 85: 95–100, 2010
C Heldref Publications
Copyright
ISSN: 0883-2323
DOI: 10.1080/08832320903258527
Online Course Delivery: An Empirical Investigation
of Factors Affecting Student Satisfaction
Mirjeta S. Beqiri and Nancy M. Chase
Gonzaga University, Spokane, Washington, USA
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Atena Bishka
TD Bank Financial Group, Toronto, Ontario, Canada
The authors investigated potential factors impacting students’ satisfaction with online course
delivery using business students as participants. The findings suggest that the student who
would be more satisfied with the delivery of online courses fits the following profile: graduate,
married, resides more than 1 mile away from campus, and male. Other factors found to
influence student satisfaction include the appropriateness of the course being offered online
and the degree of familiarity with it. Lastly, the study provides insights into students’ attitudes
toward the blended course delivery mode.
Keywords: Academic status, Distance learning, Online, Sociodemographic factors, Student
satisfaction
Whether at the undergraduate or graduate levels, studying
for a business administration degree has traditionally been
a means of attaining an initial professional position in the
workplace, improving employment opportunities, or furthering an existing career. Recent statistics indicate that during
the 2005–2006 academic year in the United States, more than
318,000 individuals received undergraduate business degrees
and more than 146,000 individuals earned a master’s degree
in business. Compared with the undergraduate and graduate
business degrees granted during the 2000–2001 academic
year, these numbers represent an increase by 20.7% and
26.6%, respectively (National Center for Education Statistics, 2007).
At the graduate level, attaining a master of business administration (MBA) degree has been a means of career development for individuals interested in acquiring management skills and improving job opportunities (e.g., Eberhardt,
Moser, & McGee, 1997; Sturges, Simpson, & Altman, 2003;
Zhao, Truell, Alexander, & Hill, 2006). The MBA degree
is thus “generally regarded as a competitive advantage for
enhancing one’s business career” (Huang & Chuan, 2005, p.
203). On the other hand, undergraduate business students
have a variety of choices upon graduation, including (a)
Correspondence should be addressed to Mirjeta Beqiri, Gonzaga University, School of Business Administration, 502 E Boone Ave, AD Box 9,
Spokane, WA 99258, USA. E-mail: beqiri@jepson.gonzaga.edu
pursuing full-time employment, (b) attending a graduatelevel degree, or (c) utilizing a combination of employment
and graduate studies (Piotrowski & Cox, 2004). Undergraduate business students entering the job market upon
graduation indicate they have “high expectations of finding employment in their chosen field or specialty area. Most
plan to be earning a respectable income in their initial job”
(Piotrowski & Cox, 2004, p. 716).
McFarland and Hamilton (winter 2005/2006) offered a
variety of definitions for the notion of online courses. These
ranged from “a course having materials delivered online that
meets synchronously and regularly. . .” to “a course having
materials delivered online that never meets synchronously,
and the student learns completely independent of a live instructor” (p. 25). For purposes of the present study, online
courses refer to courses in which materials are delivered
entirely online, and students have access to the instructor only electronically. Therefore, no face-to-face interaction occurs in such courses. Another contemporary course
delivery method, referred to as blended, requires that students meet face to face with the professor for several sessions of the course; however, the majority of sessions are
asynchronous. Additionally, because distance learning also
refers to courses delivered electronically through Web-based
sources (McLaren, 2004), we use the terms online instruction and distance learning interchangeably throughout this
article.
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M. S. BEQIRI ET AL.
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Distance learning has been practiced in a multitude of
forms since the early 1990s (Campbell, Floyd, & Sheridan,
2002). Both student and faculty interest in distance learning has continued to increase as technology improves and
fully supports this mode of course delivery (e.g., Alstete &
Beutell, 2004; McFarland & Hamilton, winter 2005/2006;
Tabatabaei, Schrottner, & Reichgelt, 2006). Although the
number of online business courses offered at many universities is increasing, the perception of the value of online degrees
has remained somewhat negative (Alsop, 2004), and “the traditional full-time degree still rules with corporate recruiters”
(p. 2).
BUSINESS STUDENT POPULATIONS
The majority of undergraduate business students enter the
higher education environment directly upon graduation from
high school. However, increasing numbers of nontraditional
students are also enrolled in undergraduate programs. The
nontraditional student has been defined as one who holds
“a full-time job, who has little flexibility in his or her daily
schedule” (Medlin, Vannoy, & Dave, 2004, p. 429).
According to Alstete and Beutell (2004), certain “demographics were found to be more influential than other factors
in predicting the interest of potential students in online business education, particularly the student age, annual income
and employment status” (p. 6). Other student populations
that might benefit from online courses included those with
scheduling conflicts from work, athletics, or other classes, as
well as students suffering from injuries or illness that would
prevent them from attending a traditional class (Boose, 2001).
Graduate business students differed from their undergraduate counterparts in several significant ways. The typical
graduate student was likely to be older, female, and diverse
in terms of race and nationality (Friga, Bettis, & Sullivan,
2003). Many graduate students were working professionals
who brought relevant work experience and insight into the
classroom (e.g., Ebersole, 2004; Giacalone, 1998; RichardsWilson, 2002). Gosling and Mintzberg (2004) suggested that
“providing education in the context of deep-rooted practical
experience turns the classroom into a rich arena for learning”
(p. 19). Working professionals tend to be more confident
as a result of their functional business experience and they
are frequently willing to express their opinions. Sometimes,
these students have competencies “that eclipse those of the
instructor. In such instances, they can become valuable resources with the potential to contribute in a most meaningful
manner to the effectiveness of the course” (Lazer & Frayer,
2000, p. 7). Graduate business students can also be very
vocal and demanding; they often have higher expectations
than do regular students (e.g., Lazer & Frayer, 2000; Rapert,
Smith, Velliquette, & Garretson, 2004). On the other hand,
segments of the graduate student population comprise young
adults with little managerial experience (Armstrong, 2005).
Frequently, these students enter the master’s program upon
completion of the undergraduate degree and therefore have
minimal first-hand business experience.
Distance Learning and Online Instruction
Online course offerings in higher education have continued
to steadily increase over the past decade (Bocchi, Eastman,
& Swift, 2004; Campbell et al., 2002). Graduate students and
working professionals are likely to be attracted to those business schools offering the flexibility of ubiquitous and just-intime distance learning courses, which enable students to remain in the workplace and to be productive for the employer.
At the same time, the employee obtains the “desired skill set
while keeping a needed income producing job” (Hollenbeck,
Zinkhan, & French, 2006, p. 41). One of the by-products of
online courses is increased flexibility in the content delivery
as well as in the learning process (Arbaugh, 2005).
Bocchi et al. (2004) maintained "that there is significant
growth in the online market because students working fulltime are the fastest growing segment of the student population and they bring corporate tuition dollars with them”
(p. 245). Time management seems to be a major concern
for this group because students are juggling commitments in
terms of classes, work, and family (McEwen, 2001).
Distance learning has emerged as an alternative to the traditional classroom mode of delivery (Lawrence, 2003) even
for the quantitative courses (e.g., Brown & Kulikowich 2004;
Grandzol, 2004). Teaching these courses online provides students with the flexibility to work and study at the same time,
but it may also posit new challenges. Although the traditional approach of teaching is instructor centered, distance
learning is more student centered (Larson, 2002). Also, distance learning could be a lonely experience (Desanctis &
Sheppard, 1999). In the traditional classroom setting, although students may frequently struggle to solve a difficult problem, they also enjoy access to immediate help from
the instructor or peers. Should this situation occur during
a distance learning course, the student may feel isolated or
abandoned without immediate access to help or expertise
(Desanctis & Sheppard, 1999), and may even withdraw from
the course. Consequently, monitoring the design and the quality of online courses becomes even more critical, and the assessment of students’ satisfaction with these courses equally
essential.
METHOD
The purpose of this study was to investigate the potential
factors affecting students’ satisfaction with online courses.
The following research questions were addressed:
Research Question 1: Does students’ satisfaction with online
courses differ based on their sociodemographic status?
ONLINE COURSE DELIVERY
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Research Question 2: What education-related factors impact
students’ satisfaction with online courses?
Research Question 3: Is the students’ satisfaction different
for online compared to blended courses?
To answer these questions, we designed a questionnaire
relying on the literature pertaining to online instruction as
well as employing findings from a pilot study we previously
conducted with business students. The earlier study identified
potential factors impacting students’ interest and motivation
in taking online courses. However, due to the small number
of students involved in this pilot study, no statistical analyses
were performed.
For the purposes of the present study, the survey was delivered via the Internet to undergraduate and graduate business students pursuing business degrees at Gonzaga University (GU), a private Jesuit university located in Spokane,
Washington. The total number of students in the target population was 962, of which 767 were undergraduates and 195
were graduates. To ensure a high participation rate among undergraduate students, the researchers collaborated with colleagues (teaching at different academic levels) who agreed
to grant extra course points for participation. Consequently,
509 undergraduate and all graduate business students enrolled in the spring semester were invited to complete the
survey. There were 168 responses collected from undergraduate students (a 33.0% response rate) and 72 responses collected from graduate students (a 36.9% response rate). All of
the questionnaires received were usable resulting in a sample
size of 240 respondents.
The web questionnaire consisted of three parts: the first
section captured students’ sociodemographic profile, the second section solicited students’ perceptions about online and
blended courses, and the last section, consisting of openended questions, asked students to share their own online
experience. The data were collected by using Sawtooth Software SSI Web (Version 5.2.2) and subsequently uploaded into
SPSS (Version 14.0). The qualitative variables were coded
as follows: gender (0 = female, 1 = male), academic status
(0 = graduate, 1 = undergraduate), major (1 = business administration [BA], 2 = accounting, 3 = undeclared general
business [UGB], 4 = other), marital status (0 = married, 1 =
single), and distance from campus (0 = less than 1 mile, 1 =
more than 1 mile).
DATA ANALYSIS AND RESULTS
This section outlines descriptive statistics regarding students’
profile and the distribution of variables of interest. To address
the stated research questions, we performed various types of
analyses, such as one-tailed t tests, a paired samples t test, an
analysis of variance F statistic, simple linear regression, and
multiple regression.
97
TABLE 1
Demographics of Participants (N = 240)
Variable
Gender
Female
Male
Marital status
Married
Single
Academic status
Graduate
Undergraduate
Major
BA
Accounting
UGB
Other
Distance from campus
Less than 1 mile
More than 1 mile
Frequency
%
106
134
44.2
55.8
33
207
13.8
86.2
72
168
30.0
70.0
175
52
6
7
72.9
21.7
2.5
2.9
161
79
67.1
32.9
Table 1 displays the respondents’ sociodemographic profile. Out of the 240 respondents, 134 were males and 106 females. Most of these students were undergraduates (70.0%),
majoring in business administration (72.9%), single (86.2%),
and resided less than 1 mile away from campus (67.1%).
Table 2 summarizes the descriptive statistics (means and
standard deviations) for continuous variables. The average
student was 23.33 years old(ranging from 18–62 years and a
standard deviation of 6.75). To capture students’ perceptions
about online courses, we included in the questionnaire such
statements as “I like online courses,” “I think online courses
are an appropriate way of learning in universities,” and “I
would take a course online if I was, to some extent, familiar
TABLE 2
Descriptive Statistics for Continuous Variables
(N = 240)
Variable
1. Age
2. I like online courses.
3. I think online courses are an appropriate way of
learning in universities.
4. I would take a course online if I was, to some
extent, familiar with the course material.
5. How many business courses have you taken online
at GU?
6. How many blended business courses have you
taken at GU?
7. How satisfied were you with the courses offered
online?
8. How satisfied were you with the blended courses?
M
SD
23.33
2.68
2.76
6.75
0.97
0.99
2.03
0.99
2.08
0.93
1.29
0.75
1.74
0.81
2.89
0.53
Note. Statements 2, 3, and 4 were rated on a 5-point Likert-type scale
ranging from 1 (strongly disagree) to 5 (strongly agree). Statements 7 and 8
were rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied)
to 5 (very satisfied).
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98
M. S. BEQIRI ET AL.
with the course material.” These statements were measured
using a five point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Furthermore, to separately assess students’ degree of satisfaction with online and blended courses, two questions were
used: “How satisfied were you with the courses offered online (100% Internet)” and “How satisfied were you with the
blended courses (both classroom and Internet based).” Both
of these questions were measured using a 5-point Likert-type
scale ranging from 1 (strongly dissatisfied) to 5 (strongly
satisfied). Lastly, the number of online and blended courses
taken at GU by participants was recorded; the means were
2.08 and 1.29, respectively, and the standard deviations 0.93
and 0.75. It is important to stress that online and blended business courses at GU are offered only during summer in order
to alleviate student scheduling conflicts, remove the need to
commute to campus, provide students with the opportunity
of a balanced workload spread throughout the academic year,
and, in some cases, finish the degree as planned.
Sociodemographic Factors
To explore the differences on students’ satisfaction with online courses by sociodemographic status, several one-tailed
t tests were performed. With regard to gender, male students (M = 1.81, SD = 0.83) reported a higher score of
the Mean Satisfaction with Online Courses (MSOC) than
did female students (M = 1.65, SD = 0.77). However, the
difference was marginally significant, t(238) = 1.55, p =
.06 (one tailed). Moreover, the results suggested that married respondents were significantly more satisfied with the
online courses (M = 2.48, SD = 0.76) compared with single
ones (M = 1.62, SD = 0.75), t(238) = 6.11, p = .000 (one
tailed). Furthermore, when considering the variable that captured the distance the student must travel to campus, the data
indicated that students living more than 1 mile away from
campus (residing off campus) were more satisfied with the
online courses (M = 2.24, SD = 0.90) than were those who
lived close to or on campus (M = 1.50, SD = 0.63). The results were found to be highly significant, t(238) = 7.42, p =
.000 (one tailed). Lastly, graduate students reported that they
were more satisfied with the delivery of online courses (M =
2.54, SD = 0.84) than were undergraduate students (M =
1.40, SD = 0.49), t(238) = 13.18, p = .000 (one tailed). Table 3 summarizes the findings with regard to the comparison
of means.
To determine whether or not there were any significant
differences in MSOC by major we performed an analysis
of variance (ANOVA), which indicated that there were no
significant differences across majors, F(3, 236) = 0.84, p =
.472. Lastly, to investigate the effect of age on MSOC, a
regression analysis was run. The results showed that the regression model was significant, F(1, 238) = 50.31, p = .000,
and explained 17.1% of the variance in the students’ satisfaction with the online courses. Moreover, as age increases
TABLE 3
Comparison of Means (N = 240)
Variable
Gender
Female
Male
Marital status
Married
Single
Academic status
Graduate
Ungraduate
Distance from campus
Less than 1 mile
More than 1 mile
M
SD
1.65
1.81
0.77
0.83
2.48
1.62
0.76
0.75
2.54
1.40
0.84
0.49
1.50
2.24
0.63
0.90
t
1.55∗
6.11∗∗∗
13.18∗∗∗
7.42∗∗∗
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied).
∗ p < .10. ∗∗∗ p < .01.
(as with it [age] come other responsibilities, such as work,
family matters), MSOC increases as well (β = .42), t(238) =
7.09, p = .000.
Education-Related Factors
Next, we examined the impact of the other block of variables,
referred to as education related, on MSOC using several regression analyses. The first variable incorporated was “I like
online courses.” The findings revealed that the regression
model was significant, F(1, 238) = 14.76, p = .000. Furthermore, if a student generally liked online courses, then he or
she was more satisfied with their online delivery (β = .24),
t(238) = 3.84, p = .000; yet, the adjusted R2 was very small
(.054).
The potential impact to MSOC of whether or not students
perceived online courses as an appropriate way of learning
in universities was also explored. The regression model was
found to be significant, F(1, 238) = 9.20, p = .003. Additionally, if a student perceived online courses as a suitable
way of learning, then he or she tended to be more satisfied
with course online delivery compared with those students
who did not accept the general concept of distance learning
(β = .19), t(238) = 3.03, p = .003. However, adjusted R2
was very small, explaining only 3.3% of the variance in the
dependent variable, MSOC.
The degree to which students were familiar with the course
background was another potential predictor of students’ satisfaction with online courses. The results revealed that, in
this case as well, the regression model was significant, F(1,
238) = 5.17, p = .024. Furthermore, as expected, a student
somewhat familiar with the course background was likely to
be more satisfied with the delivery of online courses (β =
.15), t(238) = 2.28, p = .024. Nevertheless, adjusted R2 was
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ONLINE COURSE DELIVERY
TABLE 5
Multiple Regression Analysis
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TABLE 4
Simple Regression Analyses
Variable
β
ta
Fb
1. Age
2. I like online courses
3. I think online courses are an
appropriate way of learning in
universities
4. I would take a course online if I
was, to some extent, familiar with
the course material
5. How many business courses have
you taken online at Gonzaga
University?
.42
.24
.19
7.09∗∗∗
3.84∗∗∗
3.03∗∗∗
50.31
14.76
9.20
.15
2.28∗∗
5.17
–.16
–2.48∗∗
6.15
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied).
∗∗ p < .05. ∗∗∗ p < .01.
adf = 238.
bdf = 1, 238.
very small, only .017; hence, explaining less than 2% of the
variance in the MSOC.
The number of courses completed online by students was
another variable that was predicted to potentially affect their
satisfaction with online courses. The regression model was
significant, F(1, 238) = 6.15, p = .014. However, the more
courses a student acquired online, the less dissatisfied he or
she became (β = –.16), t(238) = –2.48, p = .014. Adjusted R2
was still very small, explaining only 2.1% of the variance in
the dependent variable, MSOC. Table 4 presents a summary
of the regression analyses findings.
Lastly, given that, in addition to online courses, the School
of Business Administration at GU offers blended courses
(though in much smaller numbers), we performed a pairedsample t test to investigate whether there was a significant
difference in the students’ satisfaction with online courses
versus blended courses. The results revealed that there was
a significant difference, t(239) = –18.59, p = .000. Furthermore, the score of the mean satisfaction with online
courses was lower than the score of the mean satisfaction
with blended courses (d = –1.15).
DISCUSSION AND CONCLUSIONS
This study explored the potential sociodemographic and
education-related factors that influence students’ satisfaction
with online courses. As demonstrated by the analysis, the
student who would be more satisfied with the online delivery
of courses would fit the following profile: graduate, married,
residing off campus, and male. In terms of the educationrelated predictors, the student for whom the idea of distance
learning is appealing, who perceives online instruction to be
an appropriate way of learning in universities, and who has
Variable
Gender
Academic status
I like online courses.
ta
p
2.22
–14.50
5.98
.027
.000
.000
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied). Gender was a dummy variable coded as 0
(female) and 1 (male). Academic status was a dummy variable coded as
0 (graduate) and 1 (undergraduate). Adjusted R2 = 50.72%. F(3, 236) =
80.96, p = .000.
adf = 236.
some background regarding the course he or she decides to
take online is the type of student who would likely be more
satisfied with the online delivery of courses.
Acknowledging that some of the predictors may be moderately correlated among themselves, we developed a correlation matrix and found some multicollinearity issues. As
expected, there were moderate correlations (|r| ranged from
0.52–0.70) among the following independent variables: academic status, marital status, and distance from campus.
We ran multiple regression analyses (dropping the insignificant variables step by step) and found that the statistically significant variables affecting a student’s satisfaction
with online delivery included academic status, gender, and
the student’s inclination to take online courses. The regression model was significant, F(3, 236) = 80.96, p = .000, and
explained 50.72% of the variance. The results of the final
multiple regression analysis are depicted in Table 5.
The Appendix presents the regression equation(s) that can
be used to predict a student’s satisfaction with online courses.
Furthermore, it is important to emphasize that the variable
that stood out as having the largest impact on our dependent
variable, MSOC, was academic status. The analysis revealed
that the simple linear regression model was significant, F(1,
238) = 173.78, p = .000, and explained 42.20% of the
variance.
This study provides some insights into factors that impact
students’ satisfaction with online courses. The research results demonstrate that online courses might be better received
when offered at the graduate level (involving adult populations) than undergraduate level. Furthermore, degrees and
certain courses that attract more male (than female) students
would be potential candidates for online delivery. As course
familiarity seems to play a significant role in a student’s satisfaction, it is advisable that core and prerequisite courses not
be offered online; on the other hand, elective courses may be
offered online. Lastly, we recommend that schools and universities lean toward a blended course-delivery mode (with
some face-to-face component) versus 100% online delivery.
Regardless of the intended contribution to the academic
field, we acknowledge that the study carried some limitations
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M. S. BEQIRI ET AL.
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as well. First, even though we attempted to incorporate a
reasonable number of predictors, there are undoubtedly other
factors that may impact students’ satisfaction with online
courses. Second, the study encompassed students within one
single school (School of Business Administration) of one university. Lastly, we recognize the limitations regarding the
small predictive power of certain variables and the issues
arising from running several tests, as well as using singleitem measures. Further research should be directed toward
incorporating other predictors, refining some of the measures,
and increasing the sample size by involving other schools and
universities.
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APPENDIX
Prediction of Student Satisfaction With Online
Courses
Yˆ = β0 + β1 x1 + β2 x2 + β3 x3
Yˆ = 1.86 + .16x1 − 1.17x2 + .23x3
Where
yˆ = the dependent variable, student satisfaction with online courses
x1 = gender, 1 if student is male and 0 otherwise
x2 = academic status, 1 if student is undergraduate and 0 otherwise
x3 = I like online courses.
The following regression equations can be developed:
1. If a student is male and a graduate
Yˆ = 2.02 + .23x3
2. If a student is male and an undergraduate
Yˆ = .85 + .23x3
3. If a student is female and a graduate
Yˆ = 1.86 + .23x3
4. If a student is female and an undergraduate
Yˆ = .69 + .23x3
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Online Course Delivery: An Empirical Investigation
of Factors Affecting Student Satisfaction
Mirjeta S. Beqiri , Nancy M. Chase & Atena Bishka
To cite this article: Mirjeta S. Beqiri , Nancy M. Chase & Atena Bishka (2009) Online Course
Delivery: An Empirical Investigation of Factors Affecting Student Satisfaction, Journal of
Education for Business, 85:2, 95-100, DOI: 10.1080/08832320903258527
To link to this article: http://dx.doi.org/10.1080/08832320903258527
Published online: 07 Aug 2010.
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Date: 11 January 2016, At: 22:28
JOURNAL OF EDUCATION FOR BUSINESS, 85: 95–100, 2010
C Heldref Publications
Copyright
ISSN: 0883-2323
DOI: 10.1080/08832320903258527
Online Course Delivery: An Empirical Investigation
of Factors Affecting Student Satisfaction
Mirjeta S. Beqiri and Nancy M. Chase
Gonzaga University, Spokane, Washington, USA
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:28 11 January 2016
Atena Bishka
TD Bank Financial Group, Toronto, Ontario, Canada
The authors investigated potential factors impacting students’ satisfaction with online course
delivery using business students as participants. The findings suggest that the student who
would be more satisfied with the delivery of online courses fits the following profile: graduate,
married, resides more than 1 mile away from campus, and male. Other factors found to
influence student satisfaction include the appropriateness of the course being offered online
and the degree of familiarity with it. Lastly, the study provides insights into students’ attitudes
toward the blended course delivery mode.
Keywords: Academic status, Distance learning, Online, Sociodemographic factors, Student
satisfaction
Whether at the undergraduate or graduate levels, studying
for a business administration degree has traditionally been
a means of attaining an initial professional position in the
workplace, improving employment opportunities, or furthering an existing career. Recent statistics indicate that during
the 2005–2006 academic year in the United States, more than
318,000 individuals received undergraduate business degrees
and more than 146,000 individuals earned a master’s degree
in business. Compared with the undergraduate and graduate
business degrees granted during the 2000–2001 academic
year, these numbers represent an increase by 20.7% and
26.6%, respectively (National Center for Education Statistics, 2007).
At the graduate level, attaining a master of business administration (MBA) degree has been a means of career development for individuals interested in acquiring management skills and improving job opportunities (e.g., Eberhardt,
Moser, & McGee, 1997; Sturges, Simpson, & Altman, 2003;
Zhao, Truell, Alexander, & Hill, 2006). The MBA degree
is thus “generally regarded as a competitive advantage for
enhancing one’s business career” (Huang & Chuan, 2005, p.
203). On the other hand, undergraduate business students
have a variety of choices upon graduation, including (a)
Correspondence should be addressed to Mirjeta Beqiri, Gonzaga University, School of Business Administration, 502 E Boone Ave, AD Box 9,
Spokane, WA 99258, USA. E-mail: beqiri@jepson.gonzaga.edu
pursuing full-time employment, (b) attending a graduatelevel degree, or (c) utilizing a combination of employment
and graduate studies (Piotrowski & Cox, 2004). Undergraduate business students entering the job market upon
graduation indicate they have “high expectations of finding employment in their chosen field or specialty area. Most
plan to be earning a respectable income in their initial job”
(Piotrowski & Cox, 2004, p. 716).
McFarland and Hamilton (winter 2005/2006) offered a
variety of definitions for the notion of online courses. These
ranged from “a course having materials delivered online that
meets synchronously and regularly. . .” to “a course having
materials delivered online that never meets synchronously,
and the student learns completely independent of a live instructor” (p. 25). For purposes of the present study, online
courses refer to courses in which materials are delivered
entirely online, and students have access to the instructor only electronically. Therefore, no face-to-face interaction occurs in such courses. Another contemporary course
delivery method, referred to as blended, requires that students meet face to face with the professor for several sessions of the course; however, the majority of sessions are
asynchronous. Additionally, because distance learning also
refers to courses delivered electronically through Web-based
sources (McLaren, 2004), we use the terms online instruction and distance learning interchangeably throughout this
article.
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M. S. BEQIRI ET AL.
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Distance learning has been practiced in a multitude of
forms since the early 1990s (Campbell, Floyd, & Sheridan,
2002). Both student and faculty interest in distance learning has continued to increase as technology improves and
fully supports this mode of course delivery (e.g., Alstete &
Beutell, 2004; McFarland & Hamilton, winter 2005/2006;
Tabatabaei, Schrottner, & Reichgelt, 2006). Although the
number of online business courses offered at many universities is increasing, the perception of the value of online degrees
has remained somewhat negative (Alsop, 2004), and “the traditional full-time degree still rules with corporate recruiters”
(p. 2).
BUSINESS STUDENT POPULATIONS
The majority of undergraduate business students enter the
higher education environment directly upon graduation from
high school. However, increasing numbers of nontraditional
students are also enrolled in undergraduate programs. The
nontraditional student has been defined as one who holds
“a full-time job, who has little flexibility in his or her daily
schedule” (Medlin, Vannoy, & Dave, 2004, p. 429).
According to Alstete and Beutell (2004), certain “demographics were found to be more influential than other factors
in predicting the interest of potential students in online business education, particularly the student age, annual income
and employment status” (p. 6). Other student populations
that might benefit from online courses included those with
scheduling conflicts from work, athletics, or other classes, as
well as students suffering from injuries or illness that would
prevent them from attending a traditional class (Boose, 2001).
Graduate business students differed from their undergraduate counterparts in several significant ways. The typical
graduate student was likely to be older, female, and diverse
in terms of race and nationality (Friga, Bettis, & Sullivan,
2003). Many graduate students were working professionals
who brought relevant work experience and insight into the
classroom (e.g., Ebersole, 2004; Giacalone, 1998; RichardsWilson, 2002). Gosling and Mintzberg (2004) suggested that
“providing education in the context of deep-rooted practical
experience turns the classroom into a rich arena for learning”
(p. 19). Working professionals tend to be more confident
as a result of their functional business experience and they
are frequently willing to express their opinions. Sometimes,
these students have competencies “that eclipse those of the
instructor. In such instances, they can become valuable resources with the potential to contribute in a most meaningful
manner to the effectiveness of the course” (Lazer & Frayer,
2000, p. 7). Graduate business students can also be very
vocal and demanding; they often have higher expectations
than do regular students (e.g., Lazer & Frayer, 2000; Rapert,
Smith, Velliquette, & Garretson, 2004). On the other hand,
segments of the graduate student population comprise young
adults with little managerial experience (Armstrong, 2005).
Frequently, these students enter the master’s program upon
completion of the undergraduate degree and therefore have
minimal first-hand business experience.
Distance Learning and Online Instruction
Online course offerings in higher education have continued
to steadily increase over the past decade (Bocchi, Eastman,
& Swift, 2004; Campbell et al., 2002). Graduate students and
working professionals are likely to be attracted to those business schools offering the flexibility of ubiquitous and just-intime distance learning courses, which enable students to remain in the workplace and to be productive for the employer.
At the same time, the employee obtains the “desired skill set
while keeping a needed income producing job” (Hollenbeck,
Zinkhan, & French, 2006, p. 41). One of the by-products of
online courses is increased flexibility in the content delivery
as well as in the learning process (Arbaugh, 2005).
Bocchi et al. (2004) maintained "that there is significant
growth in the online market because students working fulltime are the fastest growing segment of the student population and they bring corporate tuition dollars with them”
(p. 245). Time management seems to be a major concern
for this group because students are juggling commitments in
terms of classes, work, and family (McEwen, 2001).
Distance learning has emerged as an alternative to the traditional classroom mode of delivery (Lawrence, 2003) even
for the quantitative courses (e.g., Brown & Kulikowich 2004;
Grandzol, 2004). Teaching these courses online provides students with the flexibility to work and study at the same time,
but it may also posit new challenges. Although the traditional approach of teaching is instructor centered, distance
learning is more student centered (Larson, 2002). Also, distance learning could be a lonely experience (Desanctis &
Sheppard, 1999). In the traditional classroom setting, although students may frequently struggle to solve a difficult problem, they also enjoy access to immediate help from
the instructor or peers. Should this situation occur during
a distance learning course, the student may feel isolated or
abandoned without immediate access to help or expertise
(Desanctis & Sheppard, 1999), and may even withdraw from
the course. Consequently, monitoring the design and the quality of online courses becomes even more critical, and the assessment of students’ satisfaction with these courses equally
essential.
METHOD
The purpose of this study was to investigate the potential
factors affecting students’ satisfaction with online courses.
The following research questions were addressed:
Research Question 1: Does students’ satisfaction with online
courses differ based on their sociodemographic status?
ONLINE COURSE DELIVERY
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Research Question 2: What education-related factors impact
students’ satisfaction with online courses?
Research Question 3: Is the students’ satisfaction different
for online compared to blended courses?
To answer these questions, we designed a questionnaire
relying on the literature pertaining to online instruction as
well as employing findings from a pilot study we previously
conducted with business students. The earlier study identified
potential factors impacting students’ interest and motivation
in taking online courses. However, due to the small number
of students involved in this pilot study, no statistical analyses
were performed.
For the purposes of the present study, the survey was delivered via the Internet to undergraduate and graduate business students pursuing business degrees at Gonzaga University (GU), a private Jesuit university located in Spokane,
Washington. The total number of students in the target population was 962, of which 767 were undergraduates and 195
were graduates. To ensure a high participation rate among undergraduate students, the researchers collaborated with colleagues (teaching at different academic levels) who agreed
to grant extra course points for participation. Consequently,
509 undergraduate and all graduate business students enrolled in the spring semester were invited to complete the
survey. There were 168 responses collected from undergraduate students (a 33.0% response rate) and 72 responses collected from graduate students (a 36.9% response rate). All of
the questionnaires received were usable resulting in a sample
size of 240 respondents.
The web questionnaire consisted of three parts: the first
section captured students’ sociodemographic profile, the second section solicited students’ perceptions about online and
blended courses, and the last section, consisting of openended questions, asked students to share their own online
experience. The data were collected by using Sawtooth Software SSI Web (Version 5.2.2) and subsequently uploaded into
SPSS (Version 14.0). The qualitative variables were coded
as follows: gender (0 = female, 1 = male), academic status
(0 = graduate, 1 = undergraduate), major (1 = business administration [BA], 2 = accounting, 3 = undeclared general
business [UGB], 4 = other), marital status (0 = married, 1 =
single), and distance from campus (0 = less than 1 mile, 1 =
more than 1 mile).
DATA ANALYSIS AND RESULTS
This section outlines descriptive statistics regarding students’
profile and the distribution of variables of interest. To address
the stated research questions, we performed various types of
analyses, such as one-tailed t tests, a paired samples t test, an
analysis of variance F statistic, simple linear regression, and
multiple regression.
97
TABLE 1
Demographics of Participants (N = 240)
Variable
Gender
Female
Male
Marital status
Married
Single
Academic status
Graduate
Undergraduate
Major
BA
Accounting
UGB
Other
Distance from campus
Less than 1 mile
More than 1 mile
Frequency
%
106
134
44.2
55.8
33
207
13.8
86.2
72
168
30.0
70.0
175
52
6
7
72.9
21.7
2.5
2.9
161
79
67.1
32.9
Table 1 displays the respondents’ sociodemographic profile. Out of the 240 respondents, 134 were males and 106 females. Most of these students were undergraduates (70.0%),
majoring in business administration (72.9%), single (86.2%),
and resided less than 1 mile away from campus (67.1%).
Table 2 summarizes the descriptive statistics (means and
standard deviations) for continuous variables. The average
student was 23.33 years old(ranging from 18–62 years and a
standard deviation of 6.75). To capture students’ perceptions
about online courses, we included in the questionnaire such
statements as “I like online courses,” “I think online courses
are an appropriate way of learning in universities,” and “I
would take a course online if I was, to some extent, familiar
TABLE 2
Descriptive Statistics for Continuous Variables
(N = 240)
Variable
1. Age
2. I like online courses.
3. I think online courses are an appropriate way of
learning in universities.
4. I would take a course online if I was, to some
extent, familiar with the course material.
5. How many business courses have you taken online
at GU?
6. How many blended business courses have you
taken at GU?
7. How satisfied were you with the courses offered
online?
8. How satisfied were you with the blended courses?
M
SD
23.33
2.68
2.76
6.75
0.97
0.99
2.03
0.99
2.08
0.93
1.29
0.75
1.74
0.81
2.89
0.53
Note. Statements 2, 3, and 4 were rated on a 5-point Likert-type scale
ranging from 1 (strongly disagree) to 5 (strongly agree). Statements 7 and 8
were rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied)
to 5 (very satisfied).
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98
M. S. BEQIRI ET AL.
with the course material.” These statements were measured
using a five point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Furthermore, to separately assess students’ degree of satisfaction with online and blended courses, two questions were
used: “How satisfied were you with the courses offered online (100% Internet)” and “How satisfied were you with the
blended courses (both classroom and Internet based).” Both
of these questions were measured using a 5-point Likert-type
scale ranging from 1 (strongly dissatisfied) to 5 (strongly
satisfied). Lastly, the number of online and blended courses
taken at GU by participants was recorded; the means were
2.08 and 1.29, respectively, and the standard deviations 0.93
and 0.75. It is important to stress that online and blended business courses at GU are offered only during summer in order
to alleviate student scheduling conflicts, remove the need to
commute to campus, provide students with the opportunity
of a balanced workload spread throughout the academic year,
and, in some cases, finish the degree as planned.
Sociodemographic Factors
To explore the differences on students’ satisfaction with online courses by sociodemographic status, several one-tailed
t tests were performed. With regard to gender, male students (M = 1.81, SD = 0.83) reported a higher score of
the Mean Satisfaction with Online Courses (MSOC) than
did female students (M = 1.65, SD = 0.77). However, the
difference was marginally significant, t(238) = 1.55, p =
.06 (one tailed). Moreover, the results suggested that married respondents were significantly more satisfied with the
online courses (M = 2.48, SD = 0.76) compared with single
ones (M = 1.62, SD = 0.75), t(238) = 6.11, p = .000 (one
tailed). Furthermore, when considering the variable that captured the distance the student must travel to campus, the data
indicated that students living more than 1 mile away from
campus (residing off campus) were more satisfied with the
online courses (M = 2.24, SD = 0.90) than were those who
lived close to or on campus (M = 1.50, SD = 0.63). The results were found to be highly significant, t(238) = 7.42, p =
.000 (one tailed). Lastly, graduate students reported that they
were more satisfied with the delivery of online courses (M =
2.54, SD = 0.84) than were undergraduate students (M =
1.40, SD = 0.49), t(238) = 13.18, p = .000 (one tailed). Table 3 summarizes the findings with regard to the comparison
of means.
To determine whether or not there were any significant
differences in MSOC by major we performed an analysis
of variance (ANOVA), which indicated that there were no
significant differences across majors, F(3, 236) = 0.84, p =
.472. Lastly, to investigate the effect of age on MSOC, a
regression analysis was run. The results showed that the regression model was significant, F(1, 238) = 50.31, p = .000,
and explained 17.1% of the variance in the students’ satisfaction with the online courses. Moreover, as age increases
TABLE 3
Comparison of Means (N = 240)
Variable
Gender
Female
Male
Marital status
Married
Single
Academic status
Graduate
Ungraduate
Distance from campus
Less than 1 mile
More than 1 mile
M
SD
1.65
1.81
0.77
0.83
2.48
1.62
0.76
0.75
2.54
1.40
0.84
0.49
1.50
2.24
0.63
0.90
t
1.55∗
6.11∗∗∗
13.18∗∗∗
7.42∗∗∗
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied).
∗ p < .10. ∗∗∗ p < .01.
(as with it [age] come other responsibilities, such as work,
family matters), MSOC increases as well (β = .42), t(238) =
7.09, p = .000.
Education-Related Factors
Next, we examined the impact of the other block of variables,
referred to as education related, on MSOC using several regression analyses. The first variable incorporated was “I like
online courses.” The findings revealed that the regression
model was significant, F(1, 238) = 14.76, p = .000. Furthermore, if a student generally liked online courses, then he or
she was more satisfied with their online delivery (β = .24),
t(238) = 3.84, p = .000; yet, the adjusted R2 was very small
(.054).
The potential impact to MSOC of whether or not students
perceived online courses as an appropriate way of learning
in universities was also explored. The regression model was
found to be significant, F(1, 238) = 9.20, p = .003. Additionally, if a student perceived online courses as a suitable
way of learning, then he or she tended to be more satisfied
with course online delivery compared with those students
who did not accept the general concept of distance learning
(β = .19), t(238) = 3.03, p = .003. However, adjusted R2
was very small, explaining only 3.3% of the variance in the
dependent variable, MSOC.
The degree to which students were familiar with the course
background was another potential predictor of students’ satisfaction with online courses. The results revealed that, in
this case as well, the regression model was significant, F(1,
238) = 5.17, p = .024. Furthermore, as expected, a student
somewhat familiar with the course background was likely to
be more satisfied with the delivery of online courses (β =
.15), t(238) = 2.28, p = .024. Nevertheless, adjusted R2 was
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ONLINE COURSE DELIVERY
TABLE 5
Multiple Regression Analysis
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TABLE 4
Simple Regression Analyses
Variable
β
ta
Fb
1. Age
2. I like online courses
3. I think online courses are an
appropriate way of learning in
universities
4. I would take a course online if I
was, to some extent, familiar with
the course material
5. How many business courses have
you taken online at Gonzaga
University?
.42
.24
.19
7.09∗∗∗
3.84∗∗∗
3.03∗∗∗
50.31
14.76
9.20
.15
2.28∗∗
5.17
–.16
–2.48∗∗
6.15
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied).
∗∗ p < .05. ∗∗∗ p < .01.
adf = 238.
bdf = 1, 238.
very small, only .017; hence, explaining less than 2% of the
variance in the MSOC.
The number of courses completed online by students was
another variable that was predicted to potentially affect their
satisfaction with online courses. The regression model was
significant, F(1, 238) = 6.15, p = .014. However, the more
courses a student acquired online, the less dissatisfied he or
she became (β = –.16), t(238) = –2.48, p = .014. Adjusted R2
was still very small, explaining only 2.1% of the variance in
the dependent variable, MSOC. Table 4 presents a summary
of the regression analyses findings.
Lastly, given that, in addition to online courses, the School
of Business Administration at GU offers blended courses
(though in much smaller numbers), we performed a pairedsample t test to investigate whether there was a significant
difference in the students’ satisfaction with online courses
versus blended courses. The results revealed that there was
a significant difference, t(239) = –18.59, p = .000. Furthermore, the score of the mean satisfaction with online
courses was lower than the score of the mean satisfaction
with blended courses (d = –1.15).
DISCUSSION AND CONCLUSIONS
This study explored the potential sociodemographic and
education-related factors that influence students’ satisfaction
with online courses. As demonstrated by the analysis, the
student who would be more satisfied with the online delivery
of courses would fit the following profile: graduate, married,
residing off campus, and male. In terms of the educationrelated predictors, the student for whom the idea of distance
learning is appealing, who perceives online instruction to be
an appropriate way of learning in universities, and who has
Variable
Gender
Academic status
I like online courses.
ta
p
2.22
–14.50
5.98
.027
.000
.000
Note. The dependent variable was student satisfaction with online
courses rated on a 5-point Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied). Gender was a dummy variable coded as 0
(female) and 1 (male). Academic status was a dummy variable coded as
0 (graduate) and 1 (undergraduate). Adjusted R2 = 50.72%. F(3, 236) =
80.96, p = .000.
adf = 236.
some background regarding the course he or she decides to
take online is the type of student who would likely be more
satisfied with the online delivery of courses.
Acknowledging that some of the predictors may be moderately correlated among themselves, we developed a correlation matrix and found some multicollinearity issues. As
expected, there were moderate correlations (|r| ranged from
0.52–0.70) among the following independent variables: academic status, marital status, and distance from campus.
We ran multiple regression analyses (dropping the insignificant variables step by step) and found that the statistically significant variables affecting a student’s satisfaction
with online delivery included academic status, gender, and
the student’s inclination to take online courses. The regression model was significant, F(3, 236) = 80.96, p = .000, and
explained 50.72% of the variance. The results of the final
multiple regression analysis are depicted in Table 5.
The Appendix presents the regression equation(s) that can
be used to predict a student’s satisfaction with online courses.
Furthermore, it is important to emphasize that the variable
that stood out as having the largest impact on our dependent
variable, MSOC, was academic status. The analysis revealed
that the simple linear regression model was significant, F(1,
238) = 173.78, p = .000, and explained 42.20% of the
variance.
This study provides some insights into factors that impact
students’ satisfaction with online courses. The research results demonstrate that online courses might be better received
when offered at the graduate level (involving adult populations) than undergraduate level. Furthermore, degrees and
certain courses that attract more male (than female) students
would be potential candidates for online delivery. As course
familiarity seems to play a significant role in a student’s satisfaction, it is advisable that core and prerequisite courses not
be offered online; on the other hand, elective courses may be
offered online. Lastly, we recommend that schools and universities lean toward a blended course-delivery mode (with
some face-to-face component) versus 100% online delivery.
Regardless of the intended contribution to the academic
field, we acknowledge that the study carried some limitations
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M. S. BEQIRI ET AL.
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as well. First, even though we attempted to incorporate a
reasonable number of predictors, there are undoubtedly other
factors that may impact students’ satisfaction with online
courses. Second, the study encompassed students within one
single school (School of Business Administration) of one university. Lastly, we recognize the limitations regarding the
small predictive power of certain variables and the issues
arising from running several tests, as well as using singleitem measures. Further research should be directed toward
incorporating other predictors, refining some of the measures,
and increasing the sample size by involving other schools and
universities.
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APPENDIX
Prediction of Student Satisfaction With Online
Courses
Yˆ = β0 + β1 x1 + β2 x2 + β3 x3
Yˆ = 1.86 + .16x1 − 1.17x2 + .23x3
Where
yˆ = the dependent variable, student satisfaction with online courses
x1 = gender, 1 if student is male and 0 otherwise
x2 = academic status, 1 if student is undergraduate and 0 otherwise
x3 = I like online courses.
The following regression equations can be developed:
1. If a student is male and a graduate
Yˆ = 2.02 + .23x3
2. If a student is male and an undergraduate
Yˆ = .85 + .23x3
3. If a student is female and a graduate
Yˆ = 1.86 + .23x3
4. If a student is female and an undergraduate
Yˆ = .69 + .23x3