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

Shiyu Wang, Houping Xiao and Allan Cohen
Additional contact information
Shiyu Wang: 14589University of Georgia
Houping Xiao: 1373Georgia State University
Allan Cohen: 1355University of Georgia

Journal of Educational and Behavioral Statistics, 2021, vol. 46, issue 5, 560-591

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.

Keywords: adaptive weight estimation; robust estimation; computerized adaptive testing; response revision (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998620972800 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:46:y:2021:i:5:p:560-591

DOI: 10.3102/1076998620972800

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().