Exploring the Relationships between Reading Behavior Patterns and Learning Outcomes Based on Log Data from E-Books: A Human Factor Approach

Chengjiu Yin, Masanori Yamada, Misato Oi, Atsushi Shimada, Fumiya Okubo, Kojima Kentaro, Hiroaki Ogata

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Online learning environments presently accumulate large amounts of log data. Analysis of learning behaviors from these log data is expected to benefit instructors and learners. This study was intended to identify effective measures from e-book materials used at Kyushu University and to employ these measures for analyzing learning behavioral patterns. In an evaluation, students were grouped into four clusters using k-means clustering, and their learning behavioral patterns were analyzed. We examined whether the learning behavioral patterns exhibited relations with the learning outcomes. The results reveal that the learning behavior of “backtrack” style reading exerts a significant positive influence on learning effectiveness, which can aid students to learn more efficiently.

Original languageEnglish
Pages (from-to)313-322
Number of pages10
JournalInternational Journal of Human-Computer Interaction
Volume35
Issue number4-5
DOIs
Publication statusPublished - Mar 16 2019

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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