Uncovering MOOC Completion: A Comparative Study of Completion Rates from Different Perspectives
By: Berkan Celik and Kursat Cagiltay
References
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. 10.1016/0749-5978(91)90020-T
- Bozkurt, A. (2021). Surfing on three waves of MOOCs: an examination and snapshot of research in massive open online courses. Open Praxis, 13(3), 296–311. 10.5944/openpraxis.13.3.132
- Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom research into edX’s first MOOC. Research & Practice in Assessment, 8, 13–25.
https://www.rpajournal.com/dev/wp-content/uploads/2013/05/SF2.pdf - Chuang, I., & Ho, A. (2016). HarvardX and MITx: Four years of open online courses fall 2012-summer 2016. 10.2139/ssrn.2889436
- Cisel, M. (2014). Analyzing completion rates in the first French xMOOC. Proceedings of the European MOOC Stakeholder Summit, 26, 51.
- Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education. Routledge. 10.4324/9780203029053
- Crossley, S., Dascalu, M., McNamara, D. S., Baker, R., & Trausan-Matu, S. (2017). Predicting success in massive open online courses (MOOCs) using cohesion network analysis. The 12th International Conference on Computer Supported Collaborative Learning.
International Society of the Learning Sciences .June 18–22, 2017 . Philadelphia, USA.https://repository.isls.org/bitstream/1/220/1/17.pdf - Engle, D., Mankoff, C., & Carbrey, J. (2015). Coursera’s introductory human physiology course: Factors that characterize successful completion of a MOOC. The International Review of Research in Open and Distributed Learning, 16(2). 10.19173/irrodl.v16i2.2010
- Evans, B. J., & Baker, R. B. (2016). MOOCs and persistence: Definitions and predictors. New Directions for Institutional Research, 2015(167), 69–85. 10.1002/ir.20155
- Gil-Jaurena, I., Callejo-Gallego, J., & Agudo, Y. (2017). Evaluation of the UNED MOOCs implementation: Demographics, learners’ opinions and completion rates. The International Review of Research in Open and Distributed Learning, 18(7). 10.19173/irrodl.v18i7.3155
- Gündüz, M., & Karaman, S. (2020). Open education faculty and distance education students’ dropout reasons: The case of a Turkish state university. Open Praxis, 12(1), 7–25. 10.5944/openpraxis.12.1.970
- Halawa, S., Greene, D., & Mitchell, J. (2014). Dropout prediction in MOOCs using learner activity features. eLearning Papers.
https://oerknowledgecloud.org/sites/oerknowledgecloud.org/files/In_depth_37_1%20(1).pdf - Henderikx, M. A., Kreijns, K., & Kalz, M. (2017). Refining success and dropout in massive open online courses based on the intention–behavior gap. Distance Education, 38(3), 353–368. 10.1080/01587919.2017.1369006
- Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review, 12, 45–58. 10.1016/j.edurev.2014.05.001
- Ho, A. D., Reich, J., Nesterko, S., Seaton, D. T., Mullaney, T., Waldo, J., & Chuang, I. (2014). HarvardX and MITx: The first year of open online courses fall 2012–summer 2013 (HarvardX and MITx Working Paper No. 1). 10.2139/ssrn.2381263
- Jansen, R. S., van Leeuwen, A., Janssen, J., Conijn, R., & Kester, L. (2020). Supporting learners’ self-regulated learning in Massive Open Online Courses. Computers & Education, 146, 103771. 10.1016/j.compedu.2019.103771
- Jordan, K. (2014) Initial trends in enrolment and completion of massive open online courses. The International Review of Research in Open and Distance Learning, 15(1), 133–160. 10.19173/irrodl.v15i1.1651
- Jordan, K. (2015). Massive open online course completion rates revisited: Assessment, length and attrition. The International Review of Research in Open and Distributed Learning, 16(3). 10.19173/irrodl.v16i3.2112
- Kizilcec, R. F., & Halawa, S. (2015). Attrition and achievement gaps in online learning. The Second ACM Conference on Learning@ Scale.
ACM .March 14–18, 2015 . Vancouver, Canada. 10.1145/2724660.2724680 - Koller, D., Ng, A., & Chen, Z. (2013). Retention and intention in massive open online courses: In depth. EDUCAUSE Review Online, 48(3), 62–63.
https://er.educause.edu/articles/2013/6/retention-and-intention-in-massive-open-online-courses-in-depth - Kruchinin, S. (2019). An investigation into the attraction and completion rates of MOOCs. Knowledge Management & E-Learning, 11(1), 38–58. 10.34105/j.kmel.2019.11.003
- Lackner, E., Ebner, M., & Khalil, M. (2015). MOOCs as granular systems: design patterns to foster participant activity. eLearning Papers, 42, 28–37.
https://www.researchgate.net/publication/277890739_MOOCs_as_granular_systems_design_patterns_to_foster_participant_activity - Meinel, C., Willems, C., Renz, J., & Staubitz, T. (2014). Reflections on enrollment numbers and success rates at the openhpi MOOC platform. The Second MOOC European Stakeholders Summit.
February 10–12, 2014 . Lausanne, Switzerland. - Perna, L. W., Ruby, A., Boruch, R. F., Wang, N., Scull, J., Ahmad, S., & Evans, C. (2014). Moving through MOOCs: Understanding the progression of users in massive open online courses. Educational Researcher, 43(9), 421–432. 10.3102/0013189X14562423
- Pursel, B. K., Zhang, L., Jablokow, K. W., Choi, G. W., & Velegol, D. (2016). Understanding MOOC students: Motivations and behaviours indicative of MOOC completion. Journal of Computer Assisted Learning, 32(3), 202–217. 10.1111/jcal.12131
- Reeves, T. D., Tawfik, A. A., Msilu, F., & Şimşek, I. (2017). What’s in it for me? Incentives, learning, and completion in massive open online courses. Journal of Research on Technology in Education, 49(3–4), 245–259. 10.1080/15391523.2017.1358680
- Reich, J. (2014). MOOC completion and retention in the context of student intent. EDUCAUSE Review Online, 8.
https://er.educause.edu/articles/2014/12/MOOC-completion-and-retention-in-the-context-of-student-intent - Reich, J., & Ruipérez-Valiente, J. A. (2019). The MOOC pivot. Science, 363(6423), 130–131. 10.1126/science.aav7958
- Rieber, L. P. (2017). Participation patterns in a massive open online course (MOOC) about statistics. British Journal of Educational Technology, 48(6), 1295–1304. 10.1111/bjet.12504
- Shah, D. (2021). A decade of MOOCs: A review of MOOC stats and trends in 2021.
https://www.classcentral.com/report/MOOCs-stats-and-trends-2021 - Sheeran, P. (2002). Intention—behavior relations: a conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. 10.1080/14792772143000003
- Tschofen, C., & Mackness, J. (2012). Connectivism and dimensions of individual experience. The International Review of Research in Open and Distributed Learning, 13(1), 124–143. 10.19173/irrodl.v13i1.1143
- Wang, Y., Baker, R. S., & Paquette, L. (2017). Behavioral predictors of MOOC post-course development. The Proceedings of the Seventh International Learning Analytics & Knowledge Conference.
Association for Computing Machinery .March 13–17, 2017 . Vancouver, Canada. 10.1145/3027385.3029430 - Xiong, Y., Li, H., Kornhaber, M. L., Suen, H. K., Pursel, B., & Goins, D. D. (2015). Examining the relations among student motivation, engagement, and retention in a MOOC: A structural equation modeling approach. Global Education Review, 2(3), 23–33.
https://files.eric.ed.gov/fulltext/EJ1074099.pdf
DOI: https://doi.org/10.55982/openpraxis.16.3.606 | Journal eISSN: 2304-070X
Language: English
Page range: 445 - 456
Submitted on: Oct 22, 2023
Accepted on: Dec 24, 2023
Published on: Aug 29, 2024
Published by: International Council for Open and Distance Education (ICDE)
In partnership with: Paradigm Publishing Services
Keywords:
© 2024 Berkan Celik, Kursat Cagiltay, published by International Council for Open and Distance Education (ICDE)
This work is licensed under the Creative Commons Attribution 4.0 License.