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Rule-based knowledge representation for modality learning style in AIWBES

Mokhtar, Rahmah and Mat Zin, Nor Azan and Sheikh Abdullah, Siti Norul Huda (2010) Rule-based knowledge representation for modality learning style in AIWBES. In: Knowledge Management International Conference 2010 (KMICe2010), 25-27 May 2010, Kuala Terengganu, Malaysia.

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This paper is emphasizing rule-based knowledge representation in Adaptive Intelligent Web Based Education System (AIWBES).The knowledge was extracted from modality learning style expert based on Dunn & Dunn Model.From the expert point of view, the rules were built up by the researcher.The objective of this paper is to show how knowledge can be represented, producing the rule and replacing questionnaire for learning style prediction.The prototype namely K-Stailo was developed and tested by the researcher.The finding shows that rule-based knowledge representation can be accepted as questionnaire replacement for predicting modality learning style.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN 978-983-2078-40-1 Organized by: UUM College of Art & Sciences, Universiti Utara Malaysia
Uncontrolled Keywords: Production Rule, Knowledge Representation, User model, modality learning style, AIWBES.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 05 Jun 2014 00:37
Last Modified: 05 Jun 2014 00:37

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