Implementation of learning analytics in MOOC by using artificial unintelligence

Budi Yulianto; Harjanto Prabowo; Raymond Kosala; Manik Hapsara

doi:10.3844/jcssp.2018.317.323

Implementation of learning analytics in MOOC by using artificial unintelligence

Budi Yulianto
, Harjanto Prabowo
, Raymond Kosala
, Manik Hapsara

Binus University

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

69 Downloads (Pure)

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.

Original language	English
Pages (from-to)	317-323
Number of pages	7
Journal	Journal of Computer Science
Volume	14
Issue number	3
DOIs	https://doi.org/10.3844/jcssp.2018.317.323
Publication status	Published - 7 Jan 2018
Externally published	Yes

Bibliographical note

© 2018 Budi Yulianto, Harjanto Prabowo, Raymond Kosala and Manik Hapsara. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funder

This research is funded by the Ministry of Research, Technology and Higher Education of the Republic of Indonesia through Doctoral Dissertation Grant (contract number of 039A/VR.RTT/VI/2017); and supported by Doctor of Computer Science, Bina Nusantara University. Thanks to Winarti Iswin, Riyn Winesdyo Winarko and Tifany Inne for developing the prototype.

Funding

This research is funded by the Ministry of Research, Technology and Higher Education of the Republic of Indonesia through Doctoral Dissertation Grant (contract number of 039A/VR.RTT/VI/2017); and supported by Doctor of Computer Science, Bina Nusantara University. Thanks to Winarti Iswin, Riyn Winesdyo Winarko and Tifany Inne for developing the prototype.

Funders	Funder number
Binus University
Binus University
Kementerian Riset, Teknologi dan Pendidikan Tinggi	039A/VR, RTT/VI/2017

Keywords

Learner success factor
Learning analytics
MOOC

ASJC Scopus subject areas

Software
Computer Networks and Communications
Artificial Intelligence

Access to Document

10.3844/jcssp.2018.317.323Licence: CC BY

Hapsara2018VoRFinal published version, 728 KBLicence: CC BY

Cite this

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Implementation of learning analytics in MOOC by using artificial unintelligence

Abstract

Bibliographical note

Funder

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this