bibtype	C - Conference Paper (international conference)
ARLID	0506836
utime	20240111141021.6
mtime	20190725235959.9
WOS	000418391500019
title (primary) (eng)	Question Selection Methods for Adaptive Testing with Bayesian Networks
specification	page_count 12 s. media_type P
serial	ARLID cav_un_epca*0480157 ISBN 978-80-7464-932-5 title Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty page_num 164-175 publisher place Ostrava name University of Ostrava year 2017 editor name1 Novák name2 V. editor name1 Inuiguchi name2 M. editor name1 Štěpnička name2 M.
keyword	Computerized Adaptive Testing
keyword	Question Selection Methods
keyword	Bayesian Networks
author (primary)	ARLID cav_un_auth*0329423 full_dept Department of Decision Making Theory name1 Plajner name2 Martin institution UTIA-B full_dept (cz) Matematická teorie rozhodování full_dept (eng) Department of Decision Making Theory department (cz) MTR department (eng) MTR country CZ fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author	ARLID cav_un_auth*0377505 name1 Magauina name2 A. country KZ
author	ARLID cav_un_auth*0101228 full_dept Department of Decision Making Theory name1 Vomlel name2 Jiří institution UTIA-B full_dept (cz) Matematická teorie rozhodování full_dept Department of Decision Making Theory department (cz) MTR department MTR fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source	source_type soubor PDF url http://library.utia.cas.cz/separaty/2019/MTR/plajner-0506836.pdf source_size 8 MB
cas_special	project ARLID cav_un_auth*0332303 project_id GA16-12010S agency GA ČR country CZ project ARLID cav_un_auth*0361640 project_id SGS17/198/OHK4/3T/14 agency GA ČTU country CZ abstract (eng) 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. action ARLID cav_un_auth*0377506 name The 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty dates 20170917 mrcbC20-s 20170920 place Pardubice country CZ RIV JD FORD0 20000 FORD1 20200 FORD2 20204 reportyear 2020 num_of_auth 3 presentation_type PR inst_support RVO:67985556 permalink http://hdl.handle.net/11104/0297993 confidential S mrcbC86 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied mrcbC86 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied mrcbC86 3+4 Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied arlyear 2017 mrcbU14 SCOPUS mrcbU24 PUBMED mrcbU34 000418391500019 WOS mrcbU56 soubor PDF 8 MB mrcbU63 cav_un_epca*0480157 Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty University of Ostrava 2017 Ostrava 164 175 978-80-7464-932-5 mrcbU67 340 Novák V. mrcbU67 340 Inuiguchi M. mrcbU67 340 Štěpnička M.