Adaptable learning pathway generation with Ant Colony Optimization

Lung-Hsiang WONG, Chee Kit LOOI

Research output: Contribution to journalArticlespeer-review

44 Citations (Scopus)


One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with respective to deriving the most apt learning pathway to recommend to the learner. Our proposal suggests a novel way of modeling learning pathways that combines rule-based prescriptive planning, which could be found in many of the classic Intelligent Tutoring Systems, and Ant Colony Optimization-based inductive planning, for recommending learning paths by stochastically computing past learners' traveled paths and their performances. A web-based prototype has been developed using C# and .NET technologies. Copyright © 2009 International Forum of Educational Technology & Society (IFETS).

Original languageEnglish
Pages (from-to)309-326
JournalEducational Technology & Society
Issue number3
Publication statusPublished - Jul 2009


Wong, L.-H., & Looi, C.-K. (2009). Adaptable learning pathway generation with Ant Colony Optimization. Educational Technology & Society, 12(3), 309-326.


  • Web-based learning
  • Learning pathway planning
  • Course sequencing
  • Personalized e-Learning
  • Swarm Intelligence (Self-Organizing Agents)
  • Ant Colony Optimization
  • Learning on Demand


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