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FACTORS THAT INFLUENCE STUDENTS' DECISION TO DROPOUT OF ONLINE COURSES

Pedro A. Willging

Department of Human Resource Education

University of Illinois at Urbana-Champaign

Champaign, IL 61820

email: willging@uiuc.edu

Scott D. Johnson

Department of Human Resource Education

University of Illinois at Urbana-Champaign

Champaign, IL 61820

Email: sjohnson@uiuc.edu

ABSTRACT

Although there are many reasons why students dropout of college courses, those reasons may be unique for students who are enrolled in an online program. Issues of isolation, disconnectedness, and technological problems may be factors that influence a student to leave a course. To understand these factors, an online survey was developed to collect data from students who dropped out of an online program. Logistic regression analysis was used to compare various factors between those who persist in the program and those who dropout. The results, based on the dropouts from three cohorts in an online graduate program, show that demographic variables do not predict likelihood of dropping from a program. Instead, the students' reasons for dropping out of an online program are varied and unique to each individual. Recommendations for further study are incorporated in the conclusions.

I. INTRODUCTION

The landscape of education is changing with the increasing popularity of online instruction. Developments in educational use of computers, software, and distributed networks have led to questions about the effectiveness of this new method of educational delivery and the conditions that make it a successful experience for learners [1, 2]. Dropout rate is one measure of the effectiveness of an online program. Program quality can be determined, in part, by calculating student completion rates [3], and these rates tend to be lower for online classes [4]. This suggests that online programs may be less desirable for certain students than the more traditional face-to-face type of instruction.

"While there is now some statistical information available on distance education at higher education institutions in the United States, very few, if any, research surveys have focused on online education" [5]. National estimates on attrition in graduate programs in higher education are not available, in part due to the diversity of the programs and in the difficulty in establishing common metrics that allow valid cross-program comparisons of program completion and dropout rates [6]. Moreover, since high dropout rates reflect poorly on a program, which can impact program promotion and recruitment efforts, some institutions have registration procedures that mask attrition. For example, at the British Open University, beginning students register on a temporary basis, and, if they withdraw within three months of starting the

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Mostly from anecdotal information, it is estimated that dropout rates for distance education are higher than those for on-campus programs and courses. Some studies roughly estimate that students enrolled in distance education are twice as likely to drop out than on-campus students. For example, Dutton, Dutton, and Perry [8] studied two class sections of an introduction to computer programming course; one was taught on-campus and the other in an online version of the course. Their results revealed substantial differences in the likelihood of students to complete the course. The online students had a 72.2% completion rate, while 90.3% of the undergraduates completed their face-to-face course. A study of enrollment and attrition rates for the online MBA program at West Texas A&M University found that online courses enroll more students than traditional campus courses but they also suffer from higher attrition rates [9]. That study was conducted by analyzing 15 graduate business courses offered during the past three years where the same professor taught both the campus and the internet courses.

II. LITERATURE REVIEW

Two theories provide a comprehensive theoretical framework that might explain why students leave a course. One of these theories is Tinto's Student Integration Model, in which persistence is hypothesized to be related to how well the individual's motivation and academic ability match the institution's academic and social characteristics. This match shapes a person's commitment to completing college and commitment to the institution [10]. The second theory, Bean's Model of Student Departure, predicts persistence based on behavioral intention. These behavioral intentions are shaped by beliefs and attitudes. Student's experiences within the institution, but also factors external to the institution, can affect beliefs, attitudes, and decisions [11]. Noting some gaps in Tinto's theory, a convergence model has been suggested that combines the major propositions embedded in these two theories [12].

The American College Testing (ACT) program collects data about collegiate dropout rates in general. Table 1 shows dropout rate means and standard deviations for freshmen to sophomore year by type of institution. More than 2,500 institutions are included in the compiled data for these 2003 estimates [13].

Table 1: Freshman to Sophomore Year by Type of Institution

Degree Level

N

Dropout Rate Mean (%)

Standard Deviation

Two-year Public

729

47.2

14.6

Two-year Private

122

33.0

18.4

BA/BS Public

84

31.8

13.4

BA/BS Private

464

29.6

16.6

MA Public

227

30.2

10.7

MA Private

506

25.7

12.0

PhD Public

214

22.7

9.4

PhD Private

184

17.7

12.1

Source: The American College Testing Program (2003).

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