A Machine Learning Based Framework for Adaptive Mobile Learning

  • Authors:

  • Ahmed Al-Hmouz;Jun Shen;Jun Yan

  • Affiliations:

  • School of Information Systems & Technology Faculty of Informatics, University of Wollongong, Wollongong, Australia NSW 2522;School of Information Systems & Technology Faculty of Informatics, University of Wollongong, Wollongong, Australia NSW 2522;School of Information Systems & Technology Faculty of Informatics, University of Wollongong, Wollongong, Australia NSW 2522

  • Venue:
  • ICWL '009 Proceedings of the 8th International Conference on Advances in Web Based Learning
  • Year:
  • 2009

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Abstract

Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.