Analysis of learners' navigational behaviour and their learning styles in an online course

S. Graf, T. C. Liu, Kinshuk

Research output: Contribution to journalJournal Articlepeer-review

141 Citations (Scopus)


Providing adaptive features and personalized support by considering students' learning styles in computer-assisted learning systems has high potential in making learning easier for students in terms of reducing their efforts or increasing their performance. In this study, the navigational behaviour of students in an online course within a learning management system was investigated, looking at how students with different learning styles prefer to use and learn in such a course. As a result, several differences in the students' navigation patterns were identified. These findings have several implications for improving adaptivity. First, they showed that students with different learning styles use different strategies to learn and navigate through the course, which can be seen as another argument for providing adaptivity. Second, the findings provided information for extending the adaptive functionality in typical learning management systems. Third, the information about differences in navigational behaviour can contribute towards automatic detection of learning styles, helping in making student modeling approaches more accurate.

Original languageEnglish
Pages (from-to)116-131
Number of pages16
JournalJournal of Computer Assisted Learning
Issue number2
Publication statusPublished - Apr. 2010


  • Learning management systems
  • Learning styles
  • Navigational behaviour
  • Sequential analysis


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