Citation

Ting, Choo-Yee and Mohammad Reza Beik Zadeh, (2007) Assessing Learner’s Scientific Inquiry Skills Across Time: A Dynamic Bayesian Network Approach. In: User Modeling 2007. Lecture Notes in Computer Science (4511). Springer Berlin Heidelberg, pp. 207-216. ISBN 978-3-540-73077-4

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Abstract

In this article, we develop and evaluate three Dynamic Bayesian Network (DBN) models for assessing temporally variable learner scientific inquiry skills (Hypothesis Generation and Variable Identification) in INQPRO learning environment. Empirical studies were carried out to examine the matching accuracies and identify the models’ drawbacks. We demonstrate how the insights gained from a preceding model have eventually led to the improvement of subsequent models. In this study, the entire evaluation process involved 6 domain experts and 61 human learners. The matching accuracies of the models are measured by (1) comparing with the results gathered from the pretest, posttest, and learner’s self-rating scores; and (2) comments given by domain experts based on learners’ interaction logs and the graph patterns exhibited by the models.

Item Type:	Book Section
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	19 Nov 2013 04:14
Last Modified:	19 Nov 2013 04:14
URII:	http://shdl.mmu.edu.my/id/eprint/4422

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