Citation

Ting, , Choo-Yee and Zadeh,, M. Reza Beik (2005) Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment. TOWARDS SUSTAINABLE AND SCALABLE EDUCATIONAL INNOVATIONS INFORMED BY LEARNING SCIENCES , 133 . pp. 500-507. ISSN 0922-6389

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Abstract

Research on learning has shown that although computer-based exploratory learning environments have been proven to be beneficial to learners, effectively inferring a learner's actions under a sound teaching and learning model that enhances exploratory behaviours remains uncertain. To address this problem, this article aims at discussing and highlighting the detail methodological approach for designing, and integrating the probabilistic learner modeling leveraging Bayesian networks into Scientific Inquiry Exploratory Learning Model. This integration mainly serves as a basis to support learners with adaptive instructions and facilitating the acquisition of both domain knowledge as well as scientific inquiry skills. To visualize the proposed methodological approach, a computer-based scientific inquiry exploratory learning environment named InQPro is developed. This article ends with presenting the preliminary investigation on employing Artificial Students technique to investigate the propagation of probabilities between subnetworks, and identifying threshold parameters in the probabilistic learner model.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	23 Aug 2011 01:47
Last Modified:	23 Aug 2011 01:47
URII:	http://shdl.mmu.edu.my/id/eprint/2362

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