
Mapping the dropout phenomenon in open, distance, and digital education (ODDE): A conceptual analysis
By: Berrin Cefa and Olaf Zawacki-Richter
References
- Allen, I. E., & Seaman, J. (2017).
Digital Learning Compass: Distance Education Enrollment Report 2017 . Babson Survey Research Group. - Aljohani, O. (2016). A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention in Higher Education. Higher Education Studies, 6(2),
1 . 10.5539/hes.v6n2p1 - Arnhold, N., & Bassett, R. M. (2021). Steering Tertiary Education: Toward Resilient Systems That Deliver for All (pp. 1–88). World Bank.
http://www.worldbank.org/ - 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.
- Bağrıacık Yılmaz, A., & Karataş, S. (2022). Why do open and distance education students drop out? Views from various stakeholders. International Journal of Educational Technology in Higher Education, 19(1). 10.1186/s41239-022-00333-x
- Balfanz, R., Herzog, L., & Mac Iver, D. J. (2007). Preventing Student Disengagement and Keeping Students on the Graduation Path in Urban Middle-Grades Schools: Early Identification and Effective Interventions. Educational Psychologist, 42(4), 223–235. 10.1080/00461520701621079
- Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, A. E., & Karadeniz, A. (2020). An early warning system to detect at-risk students in online higher education. Applied Sciences (Switzerland), 10(13). 10.3390/app10134427
- Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in higher education, 12, 155–187. 10.1007/BF00976194
- Bean, J. P., & Metzner, B. S. (1985). A Conceptual Model of Nontraditional Undergraduate Student Attrition. Review of Educational Research, 55(4),
485 . 10.2307/1170245 - Bissessar, C., Black, D., & Boolaky, M. (2020). International online graduate students’ perception of CoI. European Journal of Open, Distance & E-Learning, 23(1), 61–83. 10.2478/eurodl-2020-0005
- Bodin, R., & Orange, S. (2018). Access and retention in French higher education: Student drop-out as a form of regulation. British Journal of Sociology of Education, 39(1), 126–143. 10.1080/01425692.2017.1319760
- Boston, W., Díaz, S. R., Gibson, A. M., Ice, P., Richardson, J., & Swan, K. (2010). An exploration of the relationship between indicators of the Community of Inquiry framework and retention in online programs. Journal of Asynchronous Learning Networks, 14(1), 3–19. 10.24059/olj.v14i1.1636
- Bourdieu, P. (1986).
The forms of capital . In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). Wiley. - Boyle, F., Kwon, J., Ross, C., & Simpson, O. (2010). Student-student mentoring for retention and engagement in distance education. Open Learning, 25(2), 115–130. 10.1080/02680511003787370
- Branchu, C., & Flaureau, E. (2022). “I’m not listening to my teacher, I’m listening to my computer”: Online learning, disengagement, and the impact of COVID-19 on French university students. Higher Education. Scopus. 10.1007/s10734-022-00854-4
- Brindley, J. E., & Paul, R. (1996).
Lessons from distance education for the university of the future . In R. Mills & A. Tait (Eds.), Supporting the learner in open and distance learning (pp. 43–55). Pitman Publishing. - Brownson, S. (2014). Embedding Social Media Tools in Online Learning Courses. Journal of Research in Innovative Teaching, 7(1), 112–118.
- Brubacher, M. R., & Silinda, F. T. (2019). Enjoyment and not competence predicts academic persistence for distance education students. International Review of Research in Open and Distance Learning, 20(3), 165–179. 10.19173/irrodl.v20i4.4325
- Brubacher, M. R., & Silinda, F. T. (2021). First-Generation Students in Distance Education Program: Family Resources and Academic Outcomes. International Review of Research in Open and Distance Learning, 22(1), 135–147. 10.19173/irrodl.v22i1.4872
- Budash, D., & Shaw, M. (2017). Persistence in an Online Master’s Degree Program: Perceptions of Students and Faculty. Online Journal of Distance Learning Administration, 20(3), 1–19.
- Burke, A. (2019). Student Retention Models in Higher Education—A Literature Review. College and University, 94(2), 12–21.
- Chernosky, J., Ausburn, J., & Curtis, R. (2021). Students as Consumers: Retaining Engineering Students by Designing Learner-Centric Courses of Value. Journal of Continuing Higher Education, 69(2), 100–120. 10.1080/07377363.2020.1786342
- Clay, M. N., Rowland, S., & Packard, A. (2008). Improving Undergraduate Online Retention through Gated Advisement and Redundant Communication. Journal of College Student Retention: Research, Theory & Practice, 10(1), 93–102. 10.2190/CS.10.1.g
- Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and psychological measurement, 20(1), 37–46. 10.1177/001316446002000104
- Cretchley, J., Rooney, D., & Gallois, C. (2010). Mapping a 40-Year History With Leximancer: Themes and Concepts in the Journal of Cross-Cultural Psychology. Journal of Cross-Cultural Psychology, 41(3), 318–328. 10.1177/0022022110366105
- Daniel, J. S. (1999).
Mega-universities and knowledge media: Technology strategies for higher education . Kogan Page. - De Oliveira, C. F., Sobral, S. R., Ferreira, M. J., & Moreira, F. (2021). How Does Learning Analytics Contribute to Prevent Students’ Dropout in Higher Education: A Systematic Literature Review. Big Data and Cognitive Computing, 5(4),
64 . 10.3390/bdcc5040064 - Dillon, C. L., Gunawardena, C. N., & Parker, R. (1992). Learner support: The critical link in distance education. Distance Education, 13(1), 29–45. 10.1080/0158791920130104
- Elibol, S., & Bozkurt, A. (2023). Student Dropout as a Never-Ending Evergreen Phenomenon of Online Distance Education. European Journal of Investigation in Health, Psychology and Education, 13(5), 906–918. 10.3390/ejihpe13050069
- Ferguson, S. (2020). Attrition in online and face-to-face calculus and precalculus courses: A comparative analysis. Journal of Educators Online, 17(1).
https://files.eric.ed.gov/fulltext/EJ1241557.pdf - Fisk, K., Cherney, A., Hornsey, M., & Smith, A. (2012). Using computer-aided content analysis to map a research domain: A case study of institutional legitimacy in postconflict East Timor. SAGE Open, 2(4), Article
4 . 10.1177/2158244012467788 - Garrison, D. R. (2009).
Communities of inquiry in online learning . In P. L. Rogers, G. A. Berg, J. V. Boettcher, C. Howard, L. Justice, & K. D. Schenk (Eds.), Encyclopedia of Distance Learning (pp. 352–355. (2nd ed.). Hershey, PA: IGI Global. 10.4018/978-1-60566-198-8.ch052 - Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2–3), 87–105. 10.1016/S1096-7516(00)00016-6
- Garzón, A., Rubio, A., & Pérez-Pulido, A. J. (2022). E-learning strategies from a bioinformatics postgraduate programme to improve student engagement and completion rate. Bioinformatics Advances, 2(1). 10.1093/bioadv/vbac031
- Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education, 28, 68–84. 10.1016/j.iheduc.2015.10.002
- Gough, D., Oliver, S., & Thomas, J. (2017). An introduction to systematic reviews (2nd edition). SAGE. 10.53841/bpsptr.2017.23.2.95
- Harwood, I., Gapp, R. P., & Stewart, H. J. (2015). Cross-check for completeness: Exploring a novel use of Leximancer in a Grounded Theory study. The Qualitative Report, 20(7), Article
7 . 10.46743/2160-3715/2015.2191 - Herodotou, C., Naydenova, G., Boroowa, A., Gilmour, A., & Rienties, B. (2020). How can predictive learning analytics and motivational interventions increase student retention and enhance administrative support in distance education? Journal of Learning Analytics, 7(2), 72–83. 10.18608/jla.2020.72.4
- Ice, P., Gibson, A. M., Boston, W., & Becher, D. (2011). An exploration of differences between community of inquiry indicators in low and high disenrollment online courses. Journal of Asynchronous Learning Network, 15(2), 44–70. 10.24059/olj.v15i2.196
- Jackson, V. (2012). The use of a social networking site with pre-enrolled Business School students to enhance their first year experience at university, and in doing so, improve retention. Widening Participation & Lifelong Learning, 14, 25–41. 10.5456/WPLL.14.S.25
- Jayaprakash, S. M., Moody, E. W., Lauría, E. J. M., Regan, J. R., & Baron, J. D. (2014). Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative. Journal of Learning Analytics, 1(1), 6–47. 10.18608/jla.2014.11.3
- Joksimović, S., Kovanović, V., & Dawson, S. (2019). The journey of learning analytics. HERDSA Review of Higher Education, 6, 27–63.
- Kember, D. (1995). Open learning for adults: A model of learner progress. Educational Technology Publications.
- Kirkwood, A. (1998). New media mania: Can information and communication technologies enhance the quality of open and distance learning? Distance Education, 19(2), 228–241. 10.1080/0158791980190204
- Krippendorff, K. (2013). Content analysis: An introduction to its methodology (3rd ed). SAGE.
- Kustitskaya, T., Kytmanov, A., & Noskov, M. (2022). Early Student-at-Risk Detection by Current Learning Performance and Learning Behavior Indicators. Cybernetics and Information Technologies, 22(1), 117–133. 10.2478/cait-2022-0008
- 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
- Lee, Y., Driscoll, M. P., & Nelson, D. W. (2004). The past, present, and future of research in distance education: Results of a content analysis. American Journal of Distance Education, 18(4), 225–241. 10.1207/s15389286ajde1804_4
- Li, I. W., & Carroll, D. R. (2019). Factors influencing dropout and academic performance: An Australian higher education equity perspective. Journal of Higher Education Policy and Management, 42(1), 14–30. 10.1080/1360080X.2019.1649993
- Lint, A. H. (2013). E-Learning Student Perceptions on Scholarly Persistence in the 21st Century with Social Media in Higher Education. Creative Education, 4(11), 718–725. 10.4236/ce.2013.411102
- Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE review, 46(5), 30–32.
- Lu, J., Yang, J., & Yu, C.-S. (2013). Is social capital effective for online learning? Information & Management, 50(7), 507–522. 10.1016/j.im.2013.07.009
- Marshall, J. (2016). Online course selection: Using course dashboards to inform student enrollment decisions. Open Learning, 31(3), 245–259. Scopus. 10.1080/02680513.2016.1227699
- Matcha, W., Gašević, D., Ahmad Uzir, N., Jovanović, J., Pardo, A., Lim, L., Maldonado-Mahauad, J., Gentili, S., Pérez-Sanagustín, M., & Tsai, Y.-S. (2020). Analytics of Learning Strategies: Role of Course Design and Delivery Modality. Journal of Learning Analytics, 7(2), 45–71. 10.18608/jla.2020.72.3
- Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1),
1 . 10.1186/2046-4053-4-1 - Naidu, S. (1997). Collaborative reflective practice: An instructional design architecture for the Internet. Distance Education, 18(2), 257–283. 10.1080/0158791970180206
- Nakamura, M. (2017). The state of distance education in Japan. Quarterly Review of Distance Education, 18(3), 75–87.
- Netanda, R. S., Mamabolo, J., & Themane, M. (2019). Do or die: Student support interventions for the survival of distance education institutions in a competitive higher education system. Studies in Higher Education, 44(2), 397–414. Scopus. 10.1080/03075079.2017.1378632
- Nuanmeesri, S., Poomhiran, L., Chopvitayakun, S., & Kadmateekarun, P. (2022). Improving Dropout Forecasting during the COVID-19 Pandemic through Feature Selection and Multilayer Perceptron Neural Network. International Journal of Information and Education Technology, 12(9), 851–857. Scopus. 10.18178/ijiet.2022.12.9.1693
- Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021, 372(71). 10.1136/bmj.n71
- Park, J. H., & Choi, H. J. (2009). Factors Influencing Adult Learners’ Decision to Drop Out or Persist in Online Learning. Educational Technology and Society, 12, 207–217.
- Petticrew, M., & Roberts, H. (2008). Systematic Reviews in the Social Sciences: A Practical Guide. Wiley & Sons.
- Price, F., & Kadi-Hanifi, K. (2011). E-motivation! The role of popular technology in student motivation and retention. Research in Post-Compulsory Education, 16(2), 173–187. 10.1080/13596748.2011.575278
- Quayyum, A., Zipf, S., Gungor, R., & Dillon, J. M. (2019). Financial aid and learner persistence in online education in the United States. Distance Education, 40(1), 20–31. 10.1080/01587919.2018.1553561
- Radovan, M. (2019). Should I stay, or should I go? Revisiting student retention models in distance education. Turkish Online Journal of Distance Education, 20(3), 29–40. 10.17718/tojde.598211
- Rahmani, A. M., Groot, W., & Rahmani, H. (2024). Dropout in online higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 21(1). 10.1186/s41239-024-00450-9
- Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., Koffel, J. B., PRISMA-S Group, Blunt, H., Brigham, T., Chang, S., Clark, J., Conway, A., Couban, R., De Kock, S., Farrah, K., Fehrmann, P., Foster, M., Fowler, S. A., … Young, S. (2021). PRISMA-S: An extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Systematic Reviews, 10(1),
39 . 10.1186/s13643-020-01542-z - Rotar, O. (2022). Online student support: A framework for embedding support interventions into the online learning cycle. Research and Practice in Technology Enhanced Learning, 17(1),
2 . 10.1186/s41039-021-00178-4 - Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. The Internet and Higher Education, 6(1), 1–16. 10.1016/S1096-7516(02)00158-6
- Schulze, S. (2016). Socialising postgraduate students to success in an open and distance learning environment. South African Journal of Higher Education, 30(4). 10.20853/30-4-578
- Siebra, C. A., Santos, R. N., & Lino, N. C. Q. (2020). A Self-Adjusting Approach for Temporal Dropout Prediction of E-Learning Students. International Journal of Distance Education Technologies, 18(2), N.PAG-N.PAG. 10.4018/IJDET.2020040102
- Siemens, G. (2013). Learning Analytics: The Emergence of a Discipline. American Behavioral Scientist, 57(10), 1380–1400. 10.1177/0002764213498851
- Simpson, O. (2004). The impact on retention of interventions to support distance learning students. Open Learning: The Journal of Open, Distance and e-Learning, 19(1), 79–95. 10.1080/0268051042000177863
- Simpson, O. (2013). Student retention in distance education: Are we failing our students? Open Learning, 28(2), 105–119. 10.1080/02680513.2013.847363
- Spady, W. G. (1971). Dropouts from higher education: Toward an empirical model. Interchange, 2(3), 38–62. 10.1007/BF02282469
- Stephens, C., & Myers, F. (2014). Signals from the Silent: Online Predictors of Non-success in Business Undergraduate Students. Business & Management Education in HE, 1(1), 47–60. 10.11120/bmhe.2013.00005
- Swan, K. (2001). Virtual interactivity: design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22(2), 306–331. 10.1080/0158791010220208
- Swan, K. (2003).
Learning effectiveness: what the research tells us . J. Bourne & J. C. Moore (Eds.). Elements of Quality Online Education, Practice and Direction (pp. 13–45). Needham, MA: Sloan Center for Online Education. - Thorpe, M. (2002). Rethinking Learner Support: The challenge of collaborative online learning. Open Learning: The Journal of Open, Distance and e-Learning, 17(2), 105–119. 10.1080/02680510220146887a
- Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1),
89 . 10.2307/1170024 - U.S. Office of Educational Technology. (2023). Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. U.S. Department of Education, Office of Educational Technology.
https://tech.ed.gov - Walsh, C., Mitala, A., Ratcliff, M., Yap, A., & Jamaleddine, Z. (2020). A public-private partnership to transform online education through high levels of academic student support. Australasian Journal of Educational Technology, 36(5), 30–45. Education Source. 10.14742/ajet.6107
- Waite, S., & Davis, B. (2006). Developing undergraduate research skills in a faculty of education: Motivation through collaboration. Higher Education Research & Development, 25(4), 403–419. 10.1080/07294360600947426
- Wavle, S., & Ozogul, G. (2019). Investigating the impact of online classes on undergraduate degree completion. Online Learning Journal, 23(4), 281–295. 10.24059/olj.v23i4.1558
- Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. 13(3). 10.24059/olj.v13i3.1659
- Xavier, M., & Meneses, J. (2020). A literature review on the definitions of dropout in online higher education. European Distance and E-Learning Network (EDEN). Proceedings of the 2020 Annual Conference: Human and artificial intelligence for the society of the future, 73–80. 10.38069/edenconf-2020-ac0004
- Xu, D., & Jaggars, S. S. (2013). The impact of online learning on students’ course outcomes: Evidence from a large community and technical college system. Economics of Education Review, 37, 46–57. 10.1016/j.econedurev.2013.08.001
- Yasmin. (2013). Application of the classification tree model in predicting learner dropout behaviour in open and distance learning. Distance Education, 34(2), 218–231. 10.1080/01587919.2013.793642
- Zawacki-Richter, O. (2009). Research Areas in Distance Education: A Delphi Study. The International Review of Research in Open and Distributed Learning, 10(3). 10.19173/irrodl.v10i3.674
- Zawacki-Richter, O., & Bozkurt, A. (2023).
Research Trends in Open, Distance, and Digital Education . In O. Zawacki-Richter & I. Jung (Eds.), Handbook of Open, Distance and Digital Education (pp. 199–220). Springer Nature Singapore. 10.1007/978-981-19-2080-6_12 - Zawacki-Richter, O., Kerres, M., Bedenlier, S., Bond, M., & Buntins, K. (Eds.) (2020). Systematic Reviews in Educational Research: Methodology, Perspectives and Application. Springer Fachmedien Wiesbaden. 10.1007/978-3-658-27602-7
- Zawacki-Richter, O., & Latchem, C. (2018). Exploring four decades of research in Computers & Education. Computers & Education, 122, 136–152. 10.1016/j.compedu.2018.04.001
- Zawacki-Richter, O., & Naidu, S. (2016). Mapping research trends from 35 years of publications inDistance Education. Distance Education, 37(3), 245–269. 10.1080/01587919.2016.1185079
Journal eISSN: 1027-5207
Language: English
Page range: 3 - 3
Submitted on: Sep 18, 2024
Accepted on: Feb 28, 2025
Published on: Jun 3, 2025
Published by: EDEN Digital Learning Europe
In partnership with: Paradigm Publishing Services
Keywords:
© 2025 Berrin Cefa, Olaf Zawacki-Richter, published by EDEN Digital Learning Europe
This work is licensed under the Creative Commons Attribution 4.0 License.