Detection of learning strategies: a comparison of process, sequence and network analytic approaches

Wannisa Matcha, Dragan Gašević, Nora'ayu Ahmad Uzir, Jelena Jovanović, Abelardo Pardo, Jorge Maldonado-Mahauad, Mar Pérez-Sanagustín

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

12 Citations (Scopus)


Research in learning analytics proposed different computational techniques to detect learning tactics and strategies adopted by learners in digital environments through the analysis of students’ trace data. While many promising insights have been produced, there has been much less understanding about how and to what extent different data analytic approaches influence results. This paper presents a comparison of three analytic approaches including process, sequence, and network approaches for detection of learning tactics and strategies. The analysis was performed on a dataset collected in a massive open online course on software programming. All three approaches produced four tactics and three strategy groups. The tactics detected by using the sequence analysis approach differed from those identified by the other two methods. The process and network analytic approaches had more than 66% of similarity in the detected tactics. Learning strategies detected by the three approaches proved to be highly similar.

Original languageEnglish
Title of host publicationTransforming Learning with Meaningful Technologies
Subtitle of host publication14th European Conference on Technology Enhanced Learning, EC-TEL 2019 Delft, The Netherlands, September 16–19, 2019 Proceedings
EditorsMaren Scheffel, Julien Broisin, Viktoria Pammer-Schindler, Andri Ioannou, Jan Schneider
Place of PublicationCham Switzerland
Number of pages16
ISBN (Electronic)9783030297367
ISBN (Print)9783030297350
Publication statusPublished - 2019
EventEuropean Conference on Technology Enhanced Learning (EC-TEL) 2019 - Delft, Netherlands
Duration: 16 Sep 201919 Sep 2019
Conference number: 14th (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceEuropean Conference on Technology Enhanced Learning (EC-TEL) 2019
Abbreviated titleEC-TEL 2019
Internet address


  • Data analytics
  • Learning analytics
  • Learning strategy

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