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

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 populat...

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Bibliographic Details
Published inJournal of educational and behavioral statistics Vol. 49; no. 4; pp. 630 - 657
Main Authors Chen, Jyun-Hong, Chao, Hsiu-Yi
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.08.2024
American Educational Research Association
Subjects
Design optimization
Educational tests & measurements
Integer programming
Real time
optimal design
shadow test
attenuation paradox
integer programming
computerized adaptive testing
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Summary: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.
ISSN:1076-9986
1935-1054
DOI:10.3102/10769986231197666