Student persistence has long been a major challenge for open universities. Despite the evolution of open education, an overall high student attrition rate remains. This paper examines the changes and trends in factors related to student persistence in open universities. It reviews the empirical studies from the 1970s to the 2010s which reported factors influencing student persistence. The relevant studies were searched from databases, including Scopus, Web of Science, and Google Scholar. Among the 108 studies collected, a total of 284 factors influencing student persistence were identified. The factors were categorised into student factors, institutional factors, and environmental factors. Their changes and trends over the years were examined. The results show that student factors were the most frequently studied over the years examined, with the major categories being students’ psychological attributes and outcomes. Institutional factors have been increasingly studied in recent decades, with the design and delivery of programmes and courses being the strongest category. Finally, environmental factors have been decreasingly examined, with factors related to students’ family and work being the two main categories. Based on the results, the implications for developing intervention and retention strategies for student persistence in open universities are discussed.
- student persistence,
- open universities,
- open and distance education
Download the article in PDF to read it.
- Au, O. T. S., Li, K. C., & Wong, B. T. M. (2017). Student persistence in open and distance learning: A case in Hong Kong. Proceedings of the 31st Annual Conference of the Asian Association of Open Universities: Quality Assurance in Open University (pp. 304-313). Yogyakarta, Indonesia. 10.1108/AAOUJ-12-2018-0030
- Bernard, R. M., Borokhovski, E., & Tamim, R. M. (2014). Detecting bias in meta-analyses of distance education research: Big pictures we can rely on. Distance Education, 35(3), 271-293. 10.1080/01587919.2015.957433
- Brown, W. J., & Kinshuk, (2016). Influencing metacognition in a traditional classroom environment through learning analytics. In Li et al. (Eds.), State-of-the-art and future directions of smart learning (pp. 1-12). Singapore: Springer. 10.1007/978-981-287-868-7_1
- Choi, S. P. M., Lam, S. S., Li, K. C., & Wong, B. T. M. (2018). Learning analytics at low-cost: At-risk student prediction with clicker data and systematic proactive interventions. Educational Technology & Society, 21(2), 273-290. Retrieved from https://www.semanticscholar.org/paper/Learning-Analytics-at-Low-Cost%3A-At-risk-Student-and-Choi-Lam/8960392f0ee6f3751159e682798f7da99e67c50d
- Garrett, R. (2016). The state of open universities in the Commonwealth: A perspective on performance, competition and innovation. Burnaby, BC: Commonwealth of Learning. Retrieved from http://oasis.col.org/handle/11599/2048
- Gibbs, G., Regan, P., & Simpson, O. (2006). Improving student retention through evidence based proactive systems at the Open University (UK). Journal of College Student Retention: Research, Theory & Practice, 8(3), 359-376. 10.2190/2296-8237-8743-NW7P
- Government of Western Australia. (2006). Teacher ICT skills: Evaluation of the information and communication technology (ICT) knowledge and skill levels of Western Australian Government school teachers. Western Australia: Department of Education and Training. Retrieved from http://det.wa.edu.au/accountability/detcms/cms-service/download/asset/?asset_id=13038974
- Greene, J. A., Oswald, C. A., & Pomerantz, J. (2015). Predictors of retention and achievement in a massive open online course. American Educational Research Journal, 52(5), 925-955. 10.3102/0002831215584621
- Hart, C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning, 11(1), 19-42. Retrieved from https://www.ncolr.org/jiol/issues/pdf/11.1.2.pdf
- Hew, K. F. (2018). Unpacking the strategies of 10 highly rated MOOCs: Implications for engaging students in large online courses. Teachers College Record, 120(1). Retrieved from http://www.tcrecord.org/Content.asp?ContentId=22013
- Hwang, G.-J., & Tsai, C.-C. (2011). Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 42(4), E65-E70. 10.1111/j.1467-8535.2011.01183.x
- Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of Instructional Development, 10(3), 2-10. Retrieved from https://link.springer.com/article/10.1007/BF02905780
- Keller, J. M. (1999). Using the ARCS motivational process in computer-based instructional and distance education. New Directions for Teaching and Learning, 78, 39-47. 10.1002/tl.7804
- Krull, G., & Duart, J. M. (2017). Research trends in mobile learning in higher education: A systematic review of articles (2011-2015). International Review of Research in Open and Distributed Learning, 18(7). 10.19173/irrodl.v18i7.2893
- Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59(5), 593-618. 10.1007/s11423-010-9177-y
- Li, K. C., Wong, B. T. M., & Wong, B. Y. Y. (2015). Catering for diverse needs for student support: Differences between face-to-face and distance-learning students. Paper presented in the 29th Annual Conference of the Asian Association of Open Universities. Kuala Lumpur, Malaysia.
- Mishra, S. (2017). Open universities in the Commonwealth: At a glance. Burnaby, BC: Commonwealth of Learning. Retrieved from http://hdl.handle.net/11599/2786
- Peltier, G. L., Laden, R., & Matranga, M. (2000). Student persistence in college: A review of research. Journal of College Student Retention: Research, Theory & Practice, 1(4), 357-375. Retrieved from https://journals.sagepub.com/doi/pdf/10.2190/L4F7-4EF5-G2F1-Y8R3
- Pittenger, A., & Doering, A. (2010). Influence of motivational design on completion rates in online self‐study pharmacy‐content courses. Distance Education, 31(3), 275-293. Retrieved from https://eric.ed.gov/?id=EJ901061
- Rienties, B., Boroowa, A., Cross, S., Kubiak, C., Mayles, K., & Murphy, S. (2016). Analytics4action evaluation framework: A review of evidence-based learning analytics interventions at the Open University UK. Journal of Interactive Media in Education, 1(2), 1-13. 10.5334/jime.394
- Simpson, O. (2013). Student retention in distance education: Are we failing our students? Open Learning: The Journal of Open, Distance and e-Learning, 28(2), 105-119. 10.1080/02680513.2013.847363
- Tait, A. (2015). Student success in open, distance and e-learning. Oslo: International Council for Open and Distance Education. Retrieved from https://www.icde.org/s/student-success-research-findings.pdf
- Tait, A. (2018a). Education for development: From distance to open education. Journal of Learning for Development, 5(2), 101-115. Retrieved from https://jl4d.org/index.php/ejl4d/article/view/294/313
- Tait, A. (2018b). Open universities: The next phase. Asian Association of Open Universities Journal, 13(1), 13-23. 10.1108/AAOUJ-12-2017-0040
- Wong, B. T. M. (2017). Learning analytics in higher education: An analysis of case studies. AAOU Journal, 12(1), 21-40. 10.1108/AAOUJ-01-2017-0009
- Wong, B. Y. Y., & Wong, B. T. M. (2016). Supporting the wellness of students in open and distance learning. Proceedings of the 3rd International Conference on Open and Flexible Education (pp. 211-223). Hong Kong, China.