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Applying Process Mining to Analyze the Behavior of Learners in Online Courses

Poohridate Arpasat, Nucharee Premchaiswadi, Parham Porouhan, and Wichian Premchaiswadi

Abstract—The most critical challenge in analyzing the data of Massive Open Online Courses (MOOC) using process mining techniques is storing event logs in appropriate formats. In this study, an innovative approach for extraction of MOOC data is described. Thereafter, several process-discovery techniques, i.e., Dotted Chart Analysis, Fuzzy Miner, and Social Network Miner, are applied to the extracted MOOC data. In addition, behavioral studies of high- and low-performance students taking online courses are conducted. These studies considered i) overall behavioral statistics, ii) identification of bottlenecks and loopback behavior through frequency- and time-performance-based approaches, and iii) working together relationships. The results indicated that there are significant behavioral differences between the two groups. We expect that the results of this study will help educators understand students’ behavioral patterns and better organize online course content.

Index Terms—Process mining, event log, fuzzy miner, social network, dotted chart analysis.

Poohridate Arpasat, Parham Porouhan, and Wichian Premchaiswadi are with Graduate School of Information Technology, Siam University, Bangkok, Thailand (e-mail: yoisakstudio@gmail.com, parham@siam.edu, wichian@siam.edu).
Nucharee Premchaiswadi is with College of Creative Design and Entertainment Technology, Dhurakij Pundit University, Bangkok, Thailand (e-mail: nucharee@dpu.ac.th).


Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (Since 2019), INSPEC (IET), UGC-CARE List (India), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net

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