ERIC Number: EJ1433994
Record Type: Journal
Publication Date: 2024-Aug
Pages: 28
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: EISSN-1935-1054
Utilizing Real-Time Test Data to Solve Attenuation Paradox in Computerized Adaptive Testing to Enhance Optimal Design
Jyun-Hong Chen; Hsiu-Yi Chao
Journal of Educational and Behavioral Statistics, v49 n4 p630-657 2024
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.
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design, Test Validity, Test Reliability, Test Construction, Test Items, Programming
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A