Closed formula of test length required for adaptive testing with medium probability of solution

dc.contributor.authorT. Kárász Judit
dc.contributor.authorSzéll Krisztián
dc.contributor.authorTakács Szabolcs
dc.date.accessioned2023-11-30T09:00:03Z
dc.date.available2023-11-30T09:00:03Z
dc.date.issued2023
dc.description.abstractPurpose Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in the case of calibrated items, determine the required test length given number of respondents. Design/methodology/approach Empirical results have been obtained on computerized or multistage adaptive implementation. Simulation studies and classroom/experimental results show that adaptive tests can measure test subjects’ ability to the same quality over half the test length compared to linear versions. Due to the complexity of the problem, the authors discuss a closed mathematical formula: the relationship between the length of the tests, the difficulty of solving the items, the number of respondents and the levels of ability. Findings The authors present a closed formula that provides a lower bound for the minimum test length in the case of adaptive tests. The authors also present example calculations using the formula, based on the assessment framework of some student assessments to show the similarity between the theoretical calculations and the empirical results. Originality/value With this formula, we can form a connection between theoretical and simulation results.
dc.identifier.doi10.1108/QAE-03-2023-0042
dc.identifier.issn1758-7662
dc.identifier.mtmt34058861
dc.identifier.urihttps://krepozit.kre.hu/handle/123456789/552
dc.language.isoen
dc.relation.ispartofQuality Assurance in Education 31 : 3 p. 1 (2023)
dc.titleClosed formula of test length required for adaptive testing with medium probability of solution
dc.typeArticle
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