Abstract
This paper presents an Agent-Based Web Learning System to facilitate each learner achieving his learning target. Agent is a software assistant for single user, which can be an expert in specific domain. The agent can generate a learning sequence to the learner based on DFPN (Dynamic Fuzzy Petri Net). Besides, we suggest that each course should define the study intensity function to normalize different exercise grade criteria. In DFPN, each learner should receive different learning suggestions based on evaluation degree of truth of any proposition. Therefore, ABWLS can make students feel that ”everyone is different”, and achieve one-to-one learning effect.
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Huang, YM., Chen, JN., Cheng, SC., Chu, W.C. (2004). Agent-Based Web Learning System Applying Dynamic Fuzzy Petri Net. In: Liu, W., Shi, Y., Li, Q. (eds) Advances in Web-Based Learning – ICWL 2004. ICWL 2004. Lecture Notes in Computer Science, vol 3143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27859-7_44
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DOI: https://doi.org/10.1007/978-3-540-27859-7_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22542-3
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