Detecting Item Preknowledge Using Revisits With Speed and Accuracy

Onur Demirkaya, Ummugul Bezirhan and Jinming Zhang
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Onur Demirkaya: University of Illinois at Urbana-Champaign
Ummugul Bezirhan: Boston College
Jinming Zhang: University of Illinois at Urbana-Champaign

Journal of Educational and Behavioral Statistics, 2023, vol. 48, issue 4, 521-542

Abstract: Examinees with item preknowledge tend to obtain inflated test scores that undermine test score validity. With the availability of process data collected in computer-based assessments, the research on detecting item preknowledge has progressed on using both item scores and response times. Item revisit patterns of examinees can also be utilized as an additional source of information. This study proposes a new statistic for detecting item preknowledge when compromised items are known by utilizing the hierarchical speed–accuracy revisits model. By simultaneously evaluating abnormal changes in the latent abilities, speeds, and revisit propensities of examinees, the procedure was found to provide greater statistical power and stronger substantive evidence that an examinee had indeed benefited from item preknowledge.

Keywords: item preknowledge; likelihood ratio test; response time; item revisit (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:48:y:2023:i:4:p:521-542

DOI: 10.3102/10769986231153403

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