In-depth Exploration of Engagement Patterns in MOOCs
Lei, S.; Cristea, A.I.
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.
Lei, S., & Cristea, A. (2018). In-depth Exploration of Engagement Patterns in MOOCs. In H. Hacid, W. Cellary, H. Wang, H. Paik, & R. Zhou (Eds.), Web information systems engineering - WISE 2018 : 19th International Conference, Dubai, United Arab Emirates, November 12-15, 2018. Proceedings. Part II (395-409). https://doi.org/10.1007/978-3-030-02925-8_28
|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|
|Series Title||Lecture notes in computer science|
|Book Title||Web information systems engineering - WISE 2018 : 19th International Conference, Dubai, United Arab Emirates, November 12-15, 2018. Proceedings. Part II|
Accepted Conference Proceeding
The final publication is available at Springer via https://doi.org/10.1007/978-3-030-02925-8_28.
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