Utilizing Real-Time Test Data to Solve Attenuation Paradox in Computerized Adaptive Testing to Enhance Optimal Design

Jyun-Hong Chen and Hsiu-Yi Chao
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Jyun-Hong Chen: National Cheng Kung University
Hsiu-Yi Chao: Soochow University

Journal of Educational and Behavioral Statistics, 2024, vol. 49, issue 4, 630-657

Abstract: To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test constraints to reversely assembled shadow tests for item selection to prevent the attenuation paradox by integer programming. A simulation study was conducted to thoroughly investigate IPRD performance. The results indicate that the IPRD method can efficiently improve CAT performance in terms of the precision of trait estimation and satisfaction of all required test constraints, especially for conditions with stringent exposure control.

Keywords: computerized adaptive testing; attenuation paradox; shadow test; integer programming; optimal design (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:49:y:2024:i:4:p:630-657

DOI: 10.3102/10769986231197666

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