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Annals of Computer Science and Information Systems, Volume 21

Proceedings of the 2020 Federated Conference on Computer Science and Information Systems

Feasibility of computerized adaptive testing evaluated by Monte-Carlo and post-hoc simulations


DOI: http://dx.doi.org/10.15439/2020F197

Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 359367 ()

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Abstract. Computerized adaptive testing (CAT) is a modern alternative to classical paper and pencil testing. CAT is based on an automated selection of optimal item corresponding to current estimate of test-taker's ability, which is in contrast to fixed predefined items assigned in linear test. Advantages of CAT include lowered test anxiety and shortened test length, increased precision of estimates of test-takers' abilities, and lowered level of item exposure thus better security. Challenges are high technical demands on the whole test work-flow and need of large item banks.


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