Applying learning analytics to explore the effects of motivation on online students' reading behavioral patterns

Chih-Yuan Sun, Che Tsun Lin, Chien Chou

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study's participants consisted of 160 graduate students who were classified into three group types: low reading duration with low motivation, low reading duration with high motivation, and high reading duration based on a second-order cluster analysis. After performing a sequential analysis, this study reveals that highly motivated students exhibited a relatively serious reading pattern in a multi-tasking learning environment, and that online reading duration was a significant indicator of motivation in taking an online course. Finally, recommendations were provided to instructors and researchers based on the results of the study.

Original languageEnglish
Pages (from-to)209-227
Number of pages19
JournalInternational Review of Research in Open and Distance Learning
Volume19
Issue number2
DOIs
StatePublished - 1 Jan 2018

Keywords

  • Behavioral pattern
  • Learning analytics
  • Motivation
  • Online learning
  • Sequential analysis

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