Assessing learner's Scientific Inquiry Skills across time: A Dynamic Bayesian Network approach

Ting, Choo-Yee and Mohammad Reza Beik, Zadeh (2007) Assessing learner's Scientific Inquiry Skills across time: A Dynamic Bayesian Network approach. In: 11th International Conference on User Modeling, 25-29 JUN 2007 , Corfu, GREECE.

Full text not available from this repository.
Official URL: http://apps.webofknowledge.com/full_record.do?prod...

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: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 04 Oct 2011 00:58
Last Modified: 04 Oct 2011 00:58
URI: http://shdl.mmu.edu.my/id/eprint/3131

Actions (login required)

View Item View Item