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A Knowledge Integration Framework for Adaptive Learning Systems Based on Semantic Web Languages

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2 Author(s)
Feng-Hsu Wang ; Dept. of Comput. Sci. & Inf. Eng., Ming Chuan Univ., Taipei ; Dai-Yan Chen

Adaptive learning (AL) systems have long been one of the promising solutions to web-based personalized learning. This paper proposes a framework to solve the problem of integrating knowledge resources on the Web based on Semantic Web languages. As a consequence, knowledge modules of an AL system can be shared and reused on the Internet, resulting a service-based approach to developing distributed AL systems. Based on this framework, a prototype AL system was implemented to demonstrate how the knowledge modules of an AL system can be developed and integrated. Finally, a preliminary prototype evaluation result shows that the performance of the service-based approach is acceptable under light to middle traffics of requests based on current web service implementations.

Published in:

2008 Eighth IEEE International Conference on Advanced Learning Technologies

Date of Conference:

1-5 July 2008