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IJIET 2023 Vol.13(2): 211-222 ISSN: 2010-3689
doi: 10.18178/ijiet.2023.13.2.1798

Creating and Collecting e-Learning Event Logs to Analyze Learning Behavior of Students through Process Mining

Anake Nammakhunt*, Parham Porouhan, and Wichian Premchaiswadi

Abstract—Many traditional educational management models are being switched or shifted into online platforms; thus, assessing behavioral aspects of learners is essential to improving the quality of online teaching and learning processes. Currently, a problem in managing online teaching of courses is that instructors do not have the appropriate tools and techniques to be fully aware of students’ behavioral patterns in a data-driven and process-aware approach. This study is divided into three main parts. In the first part, a dataset of online students is transformed and preprocessed. In the second part, the Fuzzy Miner algorithm supported by Fluxicon Disco is applied to the dataset to understand the learning process of the students in terms of the duration and length of the tutorial videos watched online (i.e., fully watched, partially watched, paused, and resumed intervals) and in terms of the frequencies of all activities. In the third part, a comparison between behavioral patterns of high-performance group of students versus their low-performance counterparts attending the same course was conducted, and we used the Dotted Chart Analysis technique supported by ProM to conduct and make the comparisons. The results of the study showed significant differences between the two groups in terms of the duration spent on the tutorial videos and in terms of the sequence and order of the activities performed and executed. The findings of the research can be used by instructors, administrators, and educational managers to improve the course curriculum management process or to boost effective coaching and teaching styles, leading to the optimization of students’ learning process by increasing educators’ awareness about students’ weaknesses and strengths.

Index Terms—Education data mining, education process mining, data analytics, learning behavior, collecting event logs, e-learning system, process discovery, student learning behavior.

Anake Nammakhunt, Parham Porouhan, and Wichian Premchaiswadi are with Graduate School of Information Technology, Siam University, Bangkok, Thailand.
*Correspondence: anake_cc@thonburi-u.ac.th


Cite: Anake Nammakhunt*, Parham Porouhan, and Wichian Premchaiswadi, "Creating and Collecting e-Learning Event Logs to Analyze Learning Behavior of Students through Process Mining," International Journal of Information and Education Technology vol. 13, no. 2, pp. 211-222, 2023.

Copyright © 2023 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 (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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