From study tactics to learning strategies

an analytical method for extracting interpretable representations

Ed Fincham, Dragan Gasevic, Jelena Jovanovic, Abelardo Pardo

Research output: Contribution to journalArticleResearchpeer-review

13 Citations (Scopus)

Abstract

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather than how students actually employ study tactics and learning strategies. Accordingly, recent research has sought to assess students' learning strategies and, by extension, their self-regulated learning via trace data collected from digital learning environments. A number of studies have amply demonstrated the ability of educational data mining and learning analytics methods to identify patterns indicative of learning strategies within trace log data. However, many of these methods are limited in their ability to describe and interpret differences between extracted latent representations at varying levels of granularity (for instance, in terms of the underlying data of student actions and behaviour). To address this limitation, the present study proposes a new methodology whereby interpretable representations of student's self-regulating behaviour are derived at two theoretically inspired levels: that of learning strategies, and the study tactics that compose them.

Original languageEnglish
Pages (from-to)59-72
Number of pages14
JournalIEEE Transactions on Learning Technologies
Volume12
Issue number1
DOIs
Publication statusPublished - 2019

Keywords

  • Data mining
  • Education
  • Electronic mail
  • Hidden Markov models
  • Informatics
  • Task analysis
  • Tools

Cite this

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From study tactics to learning strategies : an analytical method for extracting interpretable representations. / Fincham, Ed; Gasevic, Dragan; Jovanovic, Jelena; Pardo, Abelardo.

In: IEEE Transactions on Learning Technologies, Vol. 12, No. 1, 2019, p. 59-72.

Research output: Contribution to journalArticleResearchpeer-review

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