Content Provisioning for Ubiquitous Learning

  • Authors:
  • Zhiwen Yu;Yuichi Nakamura;Daqing Zhang;Shoji Kajita;Kenji Mase

  • Affiliations:
  • Kyoto University;Kyoto University;Institut TELECOM, France;Nagoya University;Nagoya University

  • Venue:
  • IEEE Pervasive Computing
  • Year:
  • 2008

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Abstract

In this article, the authors present an approach for context-aware and QoS-enabled learning content provisioning, one of the essential elements in ubiquitous learning. The essence of the system is recommending the right content, in the right form, to the right learner, based on a wide range of user context information and QoS requirements. To facilitate knowledge interoperability and sharing, they modeled the learner context, content knowledge, and domain knowledge using ontologies. They first propose a knowledge-based semantic recommendation method to acquire the content the user really wants and needs to learn. Then, a fuzzy logic-based decision-making strategy and an adaptive QoS mapping mechanism determine the appropriate presentation according to user's QoS requirements and device/network capability.