Academic Exchange Quarterly Spring 2004: Volume 8, Issue 1
Factors Affecting Student Adoption of Online Education
William Pan, Ph.D.
Singh is an Assistant Professor in the
North American colleges and universities are increasing their use of online education. While there is a large volume of literature on the reasons for administrators’ offering online education, there is less written on why students take such courses. In this paper, using a sample of 101 graduate business school students, we examine the factors associated with the adoption of online education by students. Implications for administrators are discussed.
Online education is creating
excitement among educators in colleges and universities in the
The use of online education has grown significantly as a
result of its real and perceived benefits (McGinn,
and Weggen (2000) state that revenues from Web-based
training for online education are forecasted to climb from $550 million in 1998
to $11.4 billion in 2003. John Chambers,
CEO of Cisco, states that “education over the Internet is so big, it is going
to make e-mail look like a rounding error” (Chambers, 1999). The number of colleges and universities
offering online education has also increased dramatically – from 93 in 1993 to
762 in 1997 (Hankin, 1999), including many established universities such as
Duke, University of Baltimore, Colorado State University, University of
Florida, New York University, University of Maryland, Massachusetts Institute
of Technology, Ohio University, Pennsylvania State University, Stanford
University, the University of Wisconsin, and the University of Tennessee
(Eastman and Swift, 2001). In 2000,
Despite such rapid growth of
online education on campuses, there is a paucity of related research in the
business and management literature. As Arbaugh (2000: 213) notes, “because Internet-based
instruction is a relatively new means of communicating knowledge, research on
this type of instruction is still in its infancy.” Furthermore, there is a general lack of research
on the reasons associated with the adoption of online courses by students not only in business studies
but in other disciplines as well.
Rather, the focus has been on the reasons for implementation by
administrators. Thus, our main objective
in this empirical study is to examine the factors associated with the use of
online education by students within a
A review of the extant research reveals that while there is a relatively large body of literature on the growth and use of online education by educators, there is less research on the factors associated with the adoption of online education by students. Demographic variables, such as student and work status (full or part-time), seem to be among the most pertinent in explaining the use of online education by students. For instance, one of the primary reasons for students’ taking online courses gleaned from the literature is that inflexible work schedules may not allow for participation in traditional 9-5 classes (Canzer, 1997; Donoho, 1998; Phillips, 1998). That is, students working full-time generally do not have the flexibility to attend “in-class” sessions. Student quality may also be a deciding factor. As Volery and Lord (2001) argue, the brightest students may prefer to learn in an individual online environment rather than sharing their knowledge with less bright students in a traditional classroom setting. Personal commitments, such as responsibilities to the family, measured by marital status and number of children, are also cited as important factors driving the use of online education by students (Berger, 1999; Roberts, 1998). Apart from demographic variables, technological factors are also important. For instance, having a computer at home and prior experience with computers and the Internet are important variables influencing student adoption of online courses (Volery and Lord, 2001).
One’s attitude towards a new technology is pivotal in the decision on whether or not to adopt it (DeLoughry, 1996). Yet, student attitudes towards online education has attracted little, if any, attention in the empirical literature in business education, and is a distinctive contribution of this study to this emerging body of knowledge. Thus, in this study, we will examine the relationships between the adoption of online education by students and the availability and use of appropriate technology; student demographics; and student attitudes towards online education.
Sample and Procedures
A questionnaire survey was
distributed to 220 students enrolled in the MBA program of a university in the
The survey questions focused on four broad areas: a) if students were taking online courses, and if so, how many; b) technology; c) student demographics and other characteristics; and d) student attitudes towards online education. The technology-oriented questions were classified into two parts: availability of appropriate technology, and the actual use of computer and Internet technology.
Use of the Computer and the Internet: Four questions captured a respondent’s technological expertise: amount of time spent on the Internet at home, and at work (2 questions), and the amount of time spent on the computer at home and at work (2 questions). These were continuous variables. The alpha reliability of the scale was 0.60.
Student Characteristics: Demographic variables included: student status, with full-time students coded as 1, and part-time students coded 2; work-status (full-time, part-time, retired, and unemployed – coded 1, 2, 3 and 4, respectively); age group (coded into 8 categories, with 1 = under 20, 2 = 21-24, 3 = 25-29, … and 8 = 50 and over); sex (1 = male; 2 = female); marital status (1 = married; 2 = single; 3 = divorced; 4 = separated; and 5 = widowed); and, number of children (measured as a continuous variable.
Student Quality was measured as current GPA (as reported by respondent/student).
Availability of technology: A scale/index was developed to capture these questions as a single variable. There were six questions that asked whether the respondent had any of the following: a computer at home; a computer at work; Internet at home; Internet at work; e-mail at home; and e-mail at work (all coded 0 = no; 1 = yes). The alpha reliability of the scale was 0.65.
Attitude Towards Online Education: Four statements, using a Likert-type scale ranging from 1 = strongly disagree, to 7 = strongly agree, were used to capture the respondents’ attitudes towards online education: universities that use online education are more competitive; online education is of the same quality as education in class; there is more student effort in online classes; and, there are higher standards for online education. The alpha reliability for the scale was 0.67.
Basic descriptive statistics were used to assess the characteristics of the sample and ANOVAs were used to examine the key differences between students who were taking online classes versus those who were not; correlation analysis was utilized to assess the relationships among the variables in the study.
As Table 1 below reveals, students who enrolled in online courses differ significantly from “non-adopters” in three key categories: student status, age, and attitudes toward online education. More specifically, more part-time and younger students in the sample take online courses, as well as those with more “positive” attitudes towards this new delivery medium.
Table 1: Descriptive Statistics and Differences (ANOVAs) on Key Factors
Number of Children
Attitudes to Online Education
Mean Std Dev
Mean Std Dev
Mean Std Dev
These results are also exhibited in the correlations (Table 2 below). Taking an online course is correlated at statistically significant levels with student status (increases with part-time status); age (decreases as one gets older); and attitudes to online education (increases with positive attitudes). Interestingly, taking online courses is not significantly associated with work status (part versus full-time), sex, marital status, number of children, and current GPA.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
2 96*** -
3 11 09 -
4 -00 -01 85*** -
5 -26*** -28*** 09 07 -
6 -03 04 -07 -06 -46*** -
7 -19** -22** -07 -06 48*** -17* -
8 -04 -08 21** 17 14 -06 10 -
9 -00 -00 -06 -09 -08 -03 04 11 -
10 -13 -14 -05 07 13 -00 16 -13 -33*** -
1= taking university Online course; 2 = No. of university online courses; 3 = taken other online course; 4 = no. of other online courses; 5= Student status; 6 = Work Status; 7 = Age Group; 8 = Sex; 9 = Marital Status; 10 = Number of Children; 11 = Current GPA; 12 = Tech. Availability; 13 = Tech. Use; 14 = Attitudes to Tech
There are several implications for administrators. First, as the literature suggests, we found that students attending the university on a part-time basis were more likely to adopt online courses in their educational programs. Thus, it seems as if the flexibility offered by Web-based education is important in the adoption decision, and administrators should take advantage of this element in their marketing campaigns. It should be noted, as well, that work status was not a statistically significant factor in explaining the adoption of online education. We are not sure of the exact reasons for this in our study but it is possible that a large number of MBA students surveyed received tuition reimbursement for enrolled courses and that their employers do not offer funds for online courses. Second, since students’ attitudes are associated with the adoption of Web-based education, administrators may want to survey potential students to capture perceptions of this pedagogical tool and develop profiles of potential students. Again, this will help with marketing campaigns through the identification of target markets. Finally, unlike much of previous research, we did not find work status, sex, family connections, and student quality to be significant variables. Thus, it may be prudent for administrators to carefully assess the costs and benefits of promotional efforts that target these market segments. The foregoing should, however, be tempered by the fact that a limitation of this study is its relatively small sample size.
Online education is here to stay. Hopefully, this research will contribute to the knowledge base on this issue and help administrators improve their marketing and other operations.
Arbaugh, J. (2000). Virtual classroom versus the physical classroom: An exploratory study of class discussion patterns and student learning in an asynchronous Internet-based MBA course. Journal of Management Education, 24(2), 213-233.
Aron, L. (1999). Online U. Across the Board, 36 (8), 63-66.
Berger, N. (1999). Pioneering experiences in distance learning: Lessons learned. Journal of Management Education, 23(6), 684-690.
Canzer, B. (1997). Marketing education on the Internet. Journal of Marketing Education, 19, 56-65.
Chambers, J. (1999). Speech at COMDEX. http://www.mercurycenter.com/archives/reprints/0300/killer_aps11191999.htm
DeLoughry, T. (1996). Eaching a critical mass. Chronicle of Higher Education. January 26, A17.
Donoho, R. (1998). The new MBA. Training, 35 (October), D4-D9.
Driver, M. (2002). Investigating the benefits of Web-centric instruction for student learning – an exploratory study of an MBA course. Journal of Education for Business, 77(4), 236-245.
Eastman, J., & Swift, C. (2001). New horizons in distance education: The online learner- centered marketing class. Journal of Marketing Education, 23(1), 25-34.
--- (2002). Business: Teaching the world a lesson. The Economist, June 8, 81-85.
Fornaciari, C., Forte, M., & Matthews, C. (1999). Distance education as strategy : How can your school compete ? Journal of Management Education, 23(6), 703-718.
Hankin, J. (1999). Alice, the college teacher, and the rottweiler in Wonderland: The prospects and problems of distance education. Executive Speeches 14 (2), 18-21.
McGinn, D. (2000). College online. Newsweek, 135(17), 54-58.
Oliver, R. (1999). Exploring strategies for online teaching and learning. Distance Education, 20(2), 240-248.
Olsen, F. (2002).
Phillips, V. (1998). Online universities teach knowledge beyond the books. HRMagazine, 43 (July), 120-128.
Roberts, B. (1998). Training via the desktop. HRMagazine, 43(9), 98-104.
Sausner, R. (2003). Carving your slice of the virtual education pie. University Business, July, http://www.universitybusiness.com/page.cfm?id=311 (accessed November 11, 2003).
Urdan, T., & Weggen, C. (2000). Corporate elearning: Exploring a new frontier. http://wrhambrecht.com/research/coverage/elearning/ir/ir_explore.pdf
Volery, T., & Lord, D. (2000). Critical success factors in online education. The International Journal of Educational Management, 1495), 216-223.
Webster, J., & Hackley, P.
(1997). Teaching effectiveness in technology-mediated distance learning.