An exchange algorithm for optimal calibration of items in computerized achievement tests

Mahmood Ul Hassan and Frank Miller

Computational Statistics & Data Analysis, 2021, vol. 157, issue C

Abstract: The importance of large scale achievement tests, like national tests in school, eligibility tests for university, or international assessments for evaluation of students, is increasing. Pretesting of questions for the above mentioned tests is done to determine characteristic properties of the questions by adding them to an ordinary achievement test. If computerized tests are used, it has been shown using optimal experimental design methods that it is efficient to assign pretest questions to examinees based on their abilities. The specific distribution of abilities of the available examinees are considered and restricted optimal designs are applied. A new algorithm is developed which builds on an equivalence theorem. It discretizes the design space with the possibility to change the grid adaptively during the run, makes use of an exchange idea and filters computed designs. It is illustrated how the algorithm works through some examples as well as how convergence can be checked. The new algorithm is flexible and can be used even if different models are assumed for different questions.

Keywords: Achievement tests; Computerized tests; Exchange algorithm; Experimental design; Item response model; Optimal restricted design (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:157:y:2021:i:c:s0167947321000116

DOI: 10.1016/j.csda.2021.107177

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