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Research Article · Open access · Published 7 January 2018

Implementation of Learning Analytics in MOOC by Using Artificial Unintelligence

Budi Yulianto1, Harjanto Prabowo1, Raymond Kosala1 & Manik Hapsara1

Journal of Computer Science, Volume 14, Issue 3, pp. 317–323 · doi.org/10.3844/jcssp.2018.317.323

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Abstract

Massive Open Online Course (MOOC), a web-based e-learning tool, is growing to be used by current educational institutions. To prevent high non-passing rate, instructor needs to know which learner has the potential to pass the course or not. Learner who will fail the course also need advices immediately from instructor or system to overcome it. Learning Analytics (LA) is needed to collect and analyze learners’ activity logs on MOOC and predict their passing potential. The prototype application is developed by using Rational Unified Process (RUP) software development method. Implementation of LA in MOOC is feasible and suggested to analyze learners’ success factors by consuming learners’ activity logs and visualizing it in scatter diagram and node-link diagram. Instructor can provide advices to learners based on success factors generated by LA.

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Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

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Yulianto, B., Prabowo, H., Kosala, R. & Hapsara, M. (2018). Implementation of Learning Analytics in MOOC by Using Artificial Unintelligence. Journal of Computer Science, 14(3), 317–323. https://doi.org/10.3844/jcssp.2018.317.323

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Volume 14, Issue 3
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Implementation of Learning Analytics in MOOC by Using Artificial UnintelligenceJournal of Computer Science · Volume 14, Issue 3 · pp. 317–323 · CC BY 3.0Download