Forum-based Prediction of Certification in Massive Open Online Courses

Alsheri, Mohammed A.; Alamri, Ahmed; Cristea, Alexandra I.; Stewart, Craig D.

Abstract

Massive Open Online Courses (MOOCs) have been suffering a very level of low course certification (less than 1% of the total number of enrolled students on a given online course opt to purchase its certificate), although MOOC platforms have been offering low-cost knowledge for both learners and content providers. While MOOCs forums generated textual data (forums) have been utilized for the purpose of addressing many MOOCs key challenges like the high rate of dropout and tutor timely intervention, analysing learners’ textual interaction for the purpose of predicting certification, remains limited. Thus, this paper investigates if MOOC learner’s comments can predict their purchasing decision (certification) using a relatively large dataset of 5 MOOCs of 23 runs. Our model achieved promising accuracies, ranging between 0.71 and 0.96 across the five courses. The outcomes of this study are expected to help design future courses and predict the profitability of future runs.

Citation

Alsheri, M. A., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021, September). Forum-based Prediction of Certification in Massive Open Online Courses. Presented at 29th International Conference on Information systems and Development (ISD2021), Valencia, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 29th International Conference on Information systems and Development (ISD2021)
• Start Date: Sep 8, 2021
• End Date: Sep 10, 2021
• Acceptance Date: Aug 9, 2021
• Online Publication Date: Aug 9, 2021
• Publication Date: 2021-08
• Deposit Date: Nov 3, 2021
• Publicly Available Date: Nov 3, 2021
• Publisher: Association for Information Systems
• Public URL: https://durham-repository.worktribe.com/output/1138639
• Publisher URL: https://aisel.aisnet.org/isd2014/proceedings2021/methodologies/9/