Abstract
For a web-based dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner’s cognitive learning style should be taken into account. It is necessary to provide learners with an individualized learning support system. In this paper, a framework of web learning system based on genetic algorithm and Pervasive Agent Ontology is presented. The proposed framework utilizes genetic algorithm for representing and extracting a dynamic learning process and learning pattern to support students’ deep learning in web-based learning environment. Aiming at the problems in current Web environment, we put forward the information integration method of Semantic Web based on Pervasive Agent Ontology (SWPAO method), which will integrate, analyze and process enormous web information and extract answers for students on the basis of semantics. And experiments do prove that it is feasible to use the method to develop an individual Web-based learning system, which is valuable for further study in more depth.
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Guo, Q., Zhang, M. (2008). Implement Web Learning System Based on Genetic Algorithm and Pervasive Agent Ontology. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_32
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DOI: https://doi.org/10.1007/978-3-540-85984-0_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85983-3
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