Research Article Open Access

Implementation of Learning Analytics in MOOC by Using Artificial Unintelligence

Budi Yulianto1, Harjanto Prabowo1, Raymond Kosala1 and Manik Hapsara1
  • 1 Bina Nusantara University, Indonesia
Journal of Computer Science
Volume 14 No. 3, 2018, 317-323

DOI: https://doi.org/10.3844/jcssp.2018.317.323

Submitted On: 23 November 2017 Published On: 7 January 2018

How to Cite: 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

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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Keywords

  • MOOC
  • Learner Success Factor
  • Learning Analytics