Abstract
To enhance the efficiency and effectiveness of e-learning in on-line course system, a semantic web-based learning system is proposed to support personalized recommendation for learning paths and experiences, where three ontologies are put forward to construct the knowledge of learners, course and learning objects. The learning paths can be established by similarity matching of the course ontology and learner ontology, or adopt the predecessor’s learning experiences. Then personalized learning contents are recommended by matching between learner’s features and learning object ontology. And personalized learning experiences are formed by evaluating the learning paths, and can be reused by recommendation based on the similar compare. Experimental results suggest that the proposed system can improve the learning performance.
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Huang, C., Liu, L., Tang, Y., Lu, L. (2011). Semantic Web Enabled Personalized Recommendation for Learning Paths and Experiences. In: Zhu, M. (eds) Information and Management Engineering. ICCIC 2011. Communications in Computer and Information Science, vol 235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24022-5_43
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DOI: https://doi.org/10.1007/978-3-642-24022-5_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24021-8
Online ISBN: 978-3-642-24022-5
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