Mining students' behavior in web-based learning programs

Man Wai Lee, Sherry Y. Chen, Kyriacos Chrysostomou, Xiaohui Liu

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

There has been a proliferation of web-based learning programs (WBLPs). Unlike traditional computer-based learning programs, WBLPs are used by a population of learners who have diverse background. How different learners access the WBLPs has been investigated by several studies, which indicate that cognitive style is an important factor that influences learners' preferences. However, these studies mainly use statistical methods to analyze learners' preferences. In this paper, we propose to analyze learners' preferences with a data mining technique. Findings in our study show that Field Independent learners frequently use backward/forward buttons and spent less time for navigation. On the other hand, Field Dependent learners often use main menu and have more repeated visiting. Implications for these findings are discussed.

Original languageEnglish
Pages (from-to)3459-3464
Number of pages6
JournalExpert Systems with Applications
Volume36
Issue number2 PART 2
DOIs
StatePublished - Mar 2009

Keywords

  • Cognitive styles
  • Data mining
  • Field dependence
  • Web-based learning

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