In-depth Exploration of Engagement Patterns in MOOCs

Lei, S.; Cristea, A.I.

Abstract

With the advent of ‘big data’, various new methods have been proposed, to explore data in several domains. In the domain of learning (and e-learning, in particular), the outcomes lag somewhat behind. This is not unexpected, as e-learning has the additional dimensions of learning and engagement, as well as other psychological aspects, to name but a few, beyond ‘simple’ data crunching. This means that the goals of data exploration for e-learning are somewhat different to the goals for practically all other domains: finding out what students do is not enough, it is the means to the end of supporting student learning and increasing their engagement. This paper focuses specifically on student engagement, a crucial issue especially for MOOCs, by studying in much greater detail than previous work, the engagement of students based on clustering students according to three fundamental (and, arguably, comprehensive) dimensions: learning, social and assessment. The study’s value lies also in the fact that it is among the few studies using real-world longitudinal data (6 runs of a course, over 3 years) from a large number of students.

Citation

Lei, S., & Cristea, A. (2018, December). In-depth Exploration of Engagement Patterns in MOOCs. Presented at Web Information Systems Engineering (WISE 2018), Dubai

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Web Information Systems Engineering (WISE 2018)
• Acceptance Date: Jul 17, 2018
• Online Publication Date: Oct 21, 2018
• Publication Date: Oct 21, 2018
• Deposit Date: Jul 11, 2018
• Publicly Available Date: Aug 2, 2018
• Print ISSN: 0302-9743
• Pages: 395-409
• Series Title: Lecture notes in computer science
• Series Number: 11234
• Series ISSN: 0302-9743,1611-3349
• Book Title: Web information systems engineering - WISE 2018 : 19th International Conference, Dubai, United Arab Emirates, November 12-15, 2018. Proceedings. Part II
• ISBN: 9783030029241
• DOI: https://doi.org/10.1007/978-3-030-02925-8_28
• Public URL: https://durham-repository.worktribe.com/output/1146488