Although online learning is expanding in availability and popularity, the high dropout rates remain a challenging problem. In this paper, we reviewed the existing empirical studies on online course dropouts in post-secondary education that were published during the last 10 years. We identified 69 factors that influence students’ decisions to dropout and classified them into three main categories: (a) Student factors, (b) Course/Program factors, and (c) Environmental factors. We then examined the strategies proposed to overcome these dropout factors: (a) understanding each student’s challenges and potential, (b) providing quality course activities and well-structured supports, and (c) handling environmental issues and emotional challenges. Finally, we discussed issues regarding dropout factors and strategies for addressing these factors and offered recommendations for future research.
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*These references make up the 35 past empirical studies that we reviewed
Allen, I. E., & Seaman, J. (2008). Staying the course: Online education in the United States. Needham, MA: Sloan Consortium.
*Bocchi, J., Eastman, J. K., & Swift, C. O. (2004). Retaining the online learner: Profile of students in an online MBA program and implications for teaching them. Journal of Education for Business, 79(4), 245–253.
*Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. Chronicle of Higher Education, 46, 39–42.
*Castles, J. (2004). Persistence and the adult learner: Factors affecting persistence in Open University students. Active Learning in Higher Education, 5(2), 166–179.
*Cheung, L. L. W., & Kan, A. C. N. (2002). Evaluation of factors related to student performance in a distance-learning business communication course. Journal of Education for Business, 77(5), 257.
*Chyung, S. Y. (2001). Systematic and systemic approaches to reducing attrition rates in online higher education. American Journal of Distance Education, 15(3), 36–49.
*Clay, M. N., Rowland, S., & Packard, A. (2009). Improving undergraduate online retention through gated advisement and redundant communication. Journal of College Student Retention: Research, Theory and Practice, 10(1), 93–102.
Creswell, J. W. (2008). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Upper Saddle River, New Jersey: Pearson Prentice Hall.
Diaz, D. P. (2002). Online drop rate revisited. The technology source, May/June. Retrieved from http://technologysource.org/issue/2002-05/.
*Drouin, M. A. (2008). The relationship between students’ perceived sense of community and satisfaction, achievement, and retention in an online course. Quarterly Review of Distance Education, 9(3), 267–284.
*Dupin-Bryant, P. (2004). Pre-entry variables related to retention in online distance education. American Journal of Distance Education, 18(4), 199–206.
Finnegan, C., Morris, L. V., & Lee, K. (2009). Differences by course discipline on student behavior, persistence, and achievement in online courses of undergraduate general education. Journal of College Student Retention: Research, Theory and Practice, 10(1), 39–54.
*Frydenberg, J. (2007). Persistence in university continuing education online classes. International Review of Research in Open and Distance Learning, 8(3), 1–15.
Harasim, L. (2000). Shift happens: Online education as a new paradigm in learning. The Internet and Higher Education, 3(1–2), 41–61.
*Holder, B. (2007). An investigation of hope, academics, environment, and motivation as predictors of persistence in higher education online programs. Internet and Higher Education, 10(4), 245–260.
Greene, J. C., & Caracelli, V. J. (1997). Defining and describing the paradigm issue in mixed-method evaluation. In J. C. Greene & V. J. Caracelli (Eds.), Advances in mixed-method evaluation: The challenges and benefits of integrating diverse paradigms (pp. 5–17). San Francisco, CA: Jossey-Bass.
*Ivankova, N. V., & Stick, S. L. (2007). Students’ persistence in a distributed doctoral program in educational leadership in higher education: A mixed methods study. Research in Higher Education, 48(1), 93–135.
Kember, D. (1995). Open learning courses for adults: A model of student progress. Englewood Cliffs, NJ: Educational Technology Publications.
*Kemp, W. C. (2002). Persistence of adult learners in distance education. American Journal of Distance Education, 16(2), 65.
*Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers and Education, 48(2), 185–204.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, GA: Sage Publications.
*Liu, S. Y., Gomez, J., & Cherng-Jyh, Y. (2009). Community college online course retention and final grade: Predictability of social presence. Journal of Interactive Online Learning, 8(2), 165–182.
*Moore, K., Bartkovich, J., Fetzner, M., & Ison, S. (2003). Success in cyberspace: Student retention in online courses. Journal of Applied Research in the Community College, 10(2), 12.
Moore, M., & Kearsley, G. (1996). Distance education: A system view. Belmont, CA: Wadsworth.
*Morgan, C. K., & Tam, M. (1999). Unravelling the complexities of distance education student attrition. Distance Education, 20(1), 96–108.
*Morris, L. V., Finnegan, C., & Wu, S. (2005a). Tracking student behavior, persistence, and achievement in online courses. The Internet and Higher Education, 8(3), 221–231.
*Morris, L. V., Wu, S., & Finnegan, C. L. (2005b). Predicting retention in online general education courses. American Journal of Distance Education, 19(1), 23–36.
*Muilenburg, L. Y., & Berge, Z. L. (2001). Barriers to distance education: A factor analytic study. The American Journal of Distance Education, 11(2), 39–54.
*Müller, T. (2008). Persistence of women in online degree-completion programs. International Review of Research in Open and Distance Learning, 9(2), 1–18.
*Osborn, V. (2001). Identifying at-risk students in videoconferencing and web-based distance education. American Journal of Distance Education, 15(1), 41–54.
*Packham, G., Jones, P., Miller, C., & Thomas, B. (2004). E-learning and retention: Key factors influencing student withdrawal. Education Training, 46(6/7), 335–342.
*Parker, A. (1999). A study of variables that predict dropout from distance education. International Journal of Educational Technology, 1(2), 1–10.
*Parker, A. (2003). Identifying predictors of academic persistence in distance education. United States Distance Learning Association Journal, 17(1), 55–61.
*Perry, B., Boman, J., Care, W. D., Edwards, M., & Park, C. (2008). Why do students withdraw from online graduate nursing and health studies education? Journal of Educators Online, 5(1), 1–17.
*Pierrakeas, C., Xenos, M., Panagiotakopoulos, C., & Vergidis, D. (2004). A comparative study of dropout rates and causes for two different distance education courses. International Review of Research in Open and Distance Learning, 5(2), 1–13.
*Pigliapoco, E., & Bogliolo, A. (2008). The effects of psychological sense of community in online and face-to-face academic courses. International Journal of Emerging Technologies in Learning, 3 (4), 60–69.
*Poellhuber, B., Chomienne, M., & Karsenti, T. (2008). The effect of peer collaboration and collaborative learning on self-efficacy and persistence in a learner-paced continuous intake model. Journal of Distance Education, 22(3), 41–62.
*Rolfe, C. J. (2007). Getting the bugs out of the distance learning experience. College Quarterly, 10(3), 1–35.
Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Washington, DC: American Psychological Association.
*Rovai, A. P., & Wighting, M. J. (2005). Feelings of alienation and community among higher education students in a virtual classroom. The Internet and Higher Education, 8(2), 97–110.
*Shin, N., & Kim, J. (1999). An exploration of learner progress and drop-out in Korea National Open University. Distance Education, 20(1), 81–95.
*Tello, S. F. (2007). An analysis of student persistence in online education. International Journal of Information and Communication Technology Education, 3(3), 47–62.
Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.
*Willging, P. A., & Johnson, S. D. (2004). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 8(4), 105–118.
*Woodley, A., De Lange, P., & Tanewski, G. (2001). Student progress in distance education: Kember’s model re-visited. Open Learning, 16(2), 113–131.
*Xenos, M., Pierrakeas, C., & Pintelas, P. (2002). A survey on student dropout rates and dropout causes concerning the students in the Course of Informatics of the Hellenic Open University. Computers and Education, 39(4), 361.
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Lee, Y., Choi, J. A review of online course dropout research: implications for practice and future research. Education Tech Research Dev 59, 593–618 (2011). https://doi.org/10.1007/s11423-010-9177-y
- Dropout factors
- Online course
- Higher education
- Future research