Original title: Question Selection Methods for Adaptive Testing with Bayesian Networks
Authors: Plajner, Martin ; Magauina, A. ; Vomlel, Jiří
Document type: Papers
Conference/Event: The 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, Pardubice (CZ), 20170917
Year: 2017
Language: eng
Abstract: The performance of Computerized Adaptive Testing systems, which are used for testing of human knowledge, relies heavily on methods selecting correct questions for tested students. In this article we propose three different methods selecting questions with Bayesian networks as students’ models. We present the motivation to use these methods and their mathematical description. Two empirical datasets, paper tests of specific topics in mathematics and Czech language for foreigners, were collected for the purpose of methods’ testing. All three methods were tested using simulated testing procedure and results are compared for individual methods. The comparison is done also with the sequential selection of questions to provide a relation to the classical way of testing. The proposed methods are behaving much better than the sequential selection which verifies the need to use a better selection method. Individually, our methods behave differently, i.e., select different questions but the success rate of model’s predictions is very similar for all of them. This motivates further research in this topic to find an ordering between methods and to find the best method which would provide the best possible selections in computerized adaptive tests.
Keywords: Bayesian Networks; Computerized Adaptive Testing; Question Selection Methods
Project no.: GA16-12010S (CEP), SGS17/198/OHK4/3T/14 (CEP)
Funding provider: GA ČR, GA ČTU
Host item entry: Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, ISBN 978-80-7464-932-5

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2019/MTR/plajner-0506836.pdf
Original record: http://hdl.handle.net/11104/0297993

Permalink: http://www.nusl.cz/ntk/nusl-399150


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers