Adaptív tesztek minimális hosszának, hibájának, értékelési szintjének és  a megoldók számának összefüggései - általános megoldási aránnyal

Kárász, Judit T.; Takács, Szabolcs

doi:10.37070/aml.2021.38.1.04

Cited by 1 publication

(2 citation statements)

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“…T. Kárász and Takács (2021), based on the above observations, under certain conditions, gave a closed formula for the sample size required for a sufficiently accurate item estimation and the generally sufficient test length.…”

Section: Resultsmentioning

confidence: 95%

“…Depending on the purpose of the measurement, reaching the limit of some estimation error or „certainty” of categorization may also be part of the former, which is just the focus of our current study. T. Kárász and Takács (2021) using Wright’s formulas, came to the following general formula for the performance error of the test subject B : where L is the length of the test for test subject, B and p is the probability of solving each item.…”

Section: Resultsmentioning

confidence: 99%

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

Kárász

Széll

Takács

2023

QAE

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Purpose 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.

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Section: Resultsmentioning

confidence: 95%

Section: Resultsmentioning

confidence: 99%