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Adaptive Weight Estimation of Latent Ability: Application to Computerized Adaptive Testing With Response Revision

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  • Shiyu Wang

    (14589University of Georgia)

  • Houping Xiao

    (1373Georgia State University)

  • Allan Cohen

    (1355University of Georgia)

Abstract

An adaptive weight estimation approach is proposed to provide robust latent ability estimation in computerized adaptive testing (CAT) with response revision. This approach assigns different weights to each distinct response to the same item when response revision is allowed in CAT. Two types of weight estimation procedures, nonfunctional and functional weight, are proposed to determine the weight adaptively based on the compatibility of each revised response with the assumed statistical model in relation to remaining observations. The application of this estimation approach to a data set collected from a large-scale multistage adaptive testing demonstrates the capability of this method to reveal more information regarding the test taker’s latent ability by using the valid response path compared with only using the very last response. Limited simulation studies were concluded to evaluate the proposed ability estimation method and to compare it with several other estimation procedures in literature. Results indicate that the proposed ability estimation approach is able to provide robust estimation results in two test-taking scenarios.

Suggested Citation

  • Shiyu Wang & Houping Xiao & Allan Cohen, 2021. "Adaptive Weight Estimation of Latent Ability: Application to Computerized Adaptive Testing With Response Revision," Journal of Educational and Behavioral Statistics, , vol. 46(5), pages 560-591, October.
    • Handle: RePEc:sae:jedbes:v:46:y:2021:i:5:p:560-591
    DOI: 10.3102/1076998620972800
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    References listed on IDEAS

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