Online attrition is both a concern and a mystery; very little data exists on why students actually dropout of online courses. Survey responses were gathered from 26,595 students, a response rate of roughly 20%. Results suggest that online dropout may be a matter of self-preservation meeting life or academic needs.
Online learning is now ubiquitous in higher education. The data show that more than one out of four (28%) post-secondary students in the U.S. takes online courses. Moreover, enrollments in online courses rose 7% from 2012 to 2014, while overall higher education enrollments declining during this same period (Allen & Seaman, 2016).
The wide implementation of online offerings is a reflection of courses being seen as a way to increase college access, particularly for non-traditional and/or under-served students (Picciano, Seaman & Allen, 2010). Despite the almost universal adoption of online learning in higher education, currently there is little research available about the extent to which online courses actually increase college enrollments, or the impact that they have on subsequent college persistence (Jaggars, 2011a/b). Online courses may provide increased access to college (Johnson & Mejia, 2014), but they have also been shown to have higher attrition rates than face-to-face courses (e.g. Morris & Finnegan, 2009; Patterson & McFadden, 2009; Hachey, Wladis & Conway, 2013). This continues to raise the concern that online course enrollment might in actuality hinder degree completion because dropout is often associated with academic non-success. In 2002, however, Diaz theorized that dropout may not be detrimental to education success, instead, choosing to drop could be considered a smart move for students’ immediate personal or long term academic goals. Fifteen year later, we still do not have a better understanding of what motivates online students to drop.
Research question
- What reasons do postsecondary students cite for online course withdrawal?
- Is course withdrawal a strategic decision or due to issues beyond a student’s control?
- Is withdrawal more common among certain students (age, gender, race/ethnicity), in certain majors or in courses taught by particular faculty?
- Is there a relationship between prior G.P.A. and course withdrawal?
Literature review
Despite well documented higher attrition in online courses, recent large-scale studies on online students provide mixed results as to whether they are at higher risk of course or college dropout. On one hand, Jaggars & Xu (2010) and Xu & Jaggars (2011a/b) found that online course-taking hinders college progression. Moreover, Xu & Jaggars (2013) report that for community college students in Washington state, all students had lower performance (higher dropout/lower grade) in online courses in comparison to face-to-face courses. Similarly, Smith (2016), using multi-institution data from North Carolina found results for 4-year institutions that suggest an overall negative impact of online learning on course retention and grade outcomes. However, Johnson & Mejia (2014) analyzed multi-institutional data from the California Community College system and they report that students who took some online courses were more likely than those who took only face-to-face courses to earn an associate’s degree or to transfer to a four-year institution. And, Shea & Bidjerano (2014), using national data, found that students who had taken some of their early courses online actually completed degrees at significantly higher rates than those that did not enroll online.
Wladis, Conway & Hachey (2016) analyzed a sample from a large U.S. university system in New York and found that online course outcomes themselves had no direct effect on college persistence; rather, it was other student characteristics that seemed to make students simultaneously both more likely to enroll online and to drop out of college. This echoes earlier positing by Diaz (2002), who notes that “the mere fact of high drop rates is not necessarily indicative of academic non-success” but may instead reflect a mature decision on the part of students who are characteristically different from face-to-face students. There is strong evidence that students in online courses are more likely to be female, older (e.g. over 24 years old), employed and financially independent, married with children, and with other life responsibilities (e.g. Ashby, Sadera & McNary, 2011; Hyllegard, Deng & Hunter, 2008; Jaggars & Xu, 2010; Johnson & Mejia, 2014; Shea & Bidjerano, 2014; Smith, 2016; Wladis, Hachey, & Conway, 2015b; Xu & Jaggars, 2011a/b). These factors have been connected to higher rates of time poverty, which has been shown to mediate course outcomes (Wladis, Conway & Hachey, 2016).
Methodology
Data source and sample
This study uses a dataset collected from the City University New York (CUNY) system, the third largest university system in the U.S. (CUNY), combining institutional records with student surveys. The sample frame used was a cross section of commonly-taken courses across a wide range of disciplines from all CUNY two- and four-year campuses. Analyses are based on 26,595 survey responses that were collected from students taking fully online, hybrid, or face-to-face courses that were matched by specific course taken so that students taking the same course across different media could be compared. Institutional data was merged with survey data to provide detailed information about student demographic, academic, affective and other characteristics. Students were asked a variety of questions about their attitudes, and about various “life” factors; the particular questions of interest here included those in which students who dropped were asked to explain their reasons for dropping the course.
Results & Discussion
Initial coding of the survey responses has been completed. Preliminary results indicate that students cited many reasons for dropping their online courses. By far, the most frequent reason for leaving a course appears to be perceived quality of instructor, followed by lack of time due to work, family, or other academic demands. Other frequently cited reasons for dropping a course reflect unexpected life events, such as personal or family health issues. Although not as frequent, course difficulty was also cited as a reason for dropping. However, this was far outweighed by the previously mentioned reasons. This calls into question the idea that online students who drop are academically unsuccessful or possess inferior academic abilities; in fact, previous research suggests that that students who enroll in online courses have higher levels of academic preparation (Hyllegard, Deng & Hunter, 2008; Jaggars & Xu, 2010; Johnson & Mejia, 2014; Osborne, 2001; Xu & Jaggars, 2011a/b). The vast majority of students did not indicate that preparation or difficulty was a major issue, instead it was affective and life factors that seemed to be the greatest motivator to drop.
Diaz (2002) contends that:
“many online students who drop a class may do so because it is the right thing to do. In other words, because of the requirements of school, work, and/or family life in general, students can benefit more from a class if they take it when they have enough time to apply themselves to the class work. Thus, by dropping the class, they may be making a mature, well-informed decision that is consistent with a learner with significant academic and life experience.”
In support of Diaz’s contention, we found overwhelming evidence that many students dropped their online course because of a concern with receiving a low grade that would adversely affect their G.P.A’s. Typical of the comments were:
“I was not doing well in the class and I was afraid of falling and see the effects in my GPA.”
Further analysis of the survey responses will be completed in the next month. We will be probing for correlations between: withdrawal and course load (credits enrolled); withdrawal for purposes of grade management and major (low grades in preliminary courses can result in disqualification for in-demand majors); withdrawal related to specific instructor (looking at student perception of instructor quality along with online and face-to-face dropout rates by instructor); and withdrawal related to family issues and gender.
Implications
The results will enable colleges and universities to determine how to best allocate resources to students at risk of online course withdrawal and to better advise students prior to enrollment about issues they are likely to face.
References
Allen, E. and Seaman. J. (2016). Online report card: Tracking online education in the United States. Retrieved from: http://onlinelearningsurvey.com/reports/onlinereportcard.pdf
Ashby, J., Sadera, W.A. & McNary, S.W. (2011). Comparing Student Success between Developmental Math Courses Offered Online, Blended, and Face-to-Face. Journal of Interactive Online Learning, 10(3), 128-140.
Diaz (2002). Online drop rates revisited. Retrieved from: http://www.technologysource.org/article/online_drop_rates_revisited/?utm...
Hachey, A.C., Wladis, C.W. & Conway, K.M. (2013). Balancing retention and access in online courses: Restricting enrollment… Is it worth the cost? Journal of College Student Retention: Research, Theory & Practice, 15(1), 9-36.
Hyllegard, D., Deng, H. & Hunter, C. (2008) Why do students leave online courses? Attrition in community college distance learning courses. International Journal of Instructional Media, 35(4), 429-434.
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Patterson, B., & McFadden, C. (2009). Attrition in online and campus degree programs. Online Journal of Distance Learning Administration, 12(2) Retrieved from http://www.westga.edu/~distance/ojdla/summer122/patterson112.html
Picciano, A. G., Seaman, J., & Allen, I. E. (2010). Educational transformation through online learning: To be or not to be. Journal of Asynchronous Learning Networks, 14(4), 17-35. Retrieved from http://sloanconsortium.org/jaln/v14n4/educational-transformation-through...
Shea, P., & Bidjerano, T. (2014). Does online learning impede degree completion? A national study of community college students. Computers & Education, 75, 103-111.
Smith, N.D. (2016). Examining the effects of college courses on student outcomes using a joint nearest neighbor matching procedure on a state-wide university system. North Carolina State University. Retrieved from https://aefpweb.org/sites/default/files/webform/41/NicholeDSmith_Examini...
Wladis, C., Hachey, A.C. & Conway, K.M. (2015b). The representation of minority, female, and non-traditional STEM majors in the online environment at community colleges: A nationally representative study. Community College Review, 43(1), 89-114.
Wladis, C. W., Conway, K. M., & Hachey, A. C. (2016). Assessing Readiness for Online Education – Research Models for Identifying Students at Risk. Online Learning Journal, 20(3).
Xu, D., & Jaggars, S. S. (2011a). The effectiveness of distance education across Virginia's community colleges: Evidence from introductory college-level math and English courses. Educational Evaluation and Policy Analysis, 33(3), 360-377. doi:10.3102/0162373711413814
Xu, D., & Jaggars, S. S. (2011b). Online and hybrid course enrollment and performance in Washington state community and technical colleges. (CCRC Working Paper No. 31) Community College Research Center, Columbia University. Retrieved from http://ccrc.tc.columbia.edu/media/k2/attachments/online-hybrid-performance-washington.pdf
Xu, D., & Jaggars, S. S. (2013). Adaptability to online learning: Differences across types of students and academic subject areas. (CCRC Working Paper No. 54) Community College Research Center, Columbia University. Retrieved from http://ccrc.tc.columbia.edu/media/k2/attachments/adaptability-to-online-learning.pdf