Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment

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 thi...

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Main Authors: Ting, , Choo-Yee, Zadeh,, M. Reza Beik
Format: Article
Published: 2005
Subjects:
Online Access:http://shdl.mmu.edu.my/2362/
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author Ting, , Choo-Yee
Zadeh,, M. Reza Beik
author_facet Ting, , Choo-Yee
Zadeh,, M. Reza Beik
author_sort Ting, , Choo-Yee
building MMU Institutional Repository
collection Online Access
description 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.
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spelling mmu-23622011-08-23T01:47:19Z http://shdl.mmu.edu.my/2362/ Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment Ting, , Choo-Yee Zadeh,, M. Reza Beik QA75.5-76.95 Electronic computers. Computer science 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. 2005 Article NonPeerReviewed 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
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Ting, , Choo-Yee
Zadeh,, M. Reza Beik
Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title_full Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title_fullStr Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title_full_unstemmed Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title_short Probabilistic Learner Modeling in Scientific Inquiry Exploratory Learning Environment
title_sort probabilistic learner modeling in scientific inquiry exploratory learning environment
topic QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2362/