Ontology-based semantic recommendation for context-aware e-learning

Authors:
Zhiwen Yu;Yuichi Nakamura;Seiie Jang;Shoji Kajita;Kenji Mase
Affiliations:
Academic Center for Computing and Media Studies, Kyoto University, Japan and Information Technology Center, Nagoya University, Japan;Academic Center for Computing and Media Studies, Kyoto University, Japan;Information Technology Center, Nagoya University, Japan;Information Technology Center, Nagoya University, Japan;Information Technology Center, Nagoya University, Japan
Venue:
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
Year:
2007

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Abstract

Nowadays, e-learning systems are widely used for education and training in universities and companies because of their electronic course content access and virtual classroom participation. However, with the rapid increase of learning content on the Web, it will be time-consuming for learners to find contents they really want to and need to study. Aiming at enhancing the efficiency and effectiveness of learning, we propose an ontology-based approach for semantic content recommendation towards context-aware e-learning. The recommender takes knowledge about the learner (user context), knowledge about content, and knowledge about the domain being learned into consideration. Ontology is utilized to model and represent such kinds of knowledge. The recommendation consists of four steps: semantic relevance calculation, recommendation refining, learning path generation, and recommendation augmentation. As a result, a personalized, complete, and augmented learning program is suggested for the learner.