Sequential Detection of Compromised Items Using Response Times in Computerized Adaptive Testing

Edison M. Choe (), Jinming Zhang () and Hua-Hua Chang ()
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Edison M. Choe: Graduate Management Admission Council® (GMAC®)
Jinming Zhang: University of Illinois at Urbana-Champaign
Hua-Hua Chang: University of Illinois at Urbana-Champaign

Psychometrika, 2018, vol. 83, issue 3, No 7, 650-673

Abstract: Abstract Item compromise persists in undermining the integrity of testing, even secure administrations of computerized adaptive testing (CAT) with sophisticated item exposure controls. In ongoing efforts to tackle this perennial security issue in CAT, a couple of recent studies investigated sequential procedures for detecting compromised items, in which a significant increase in the proportion of correct responses for each item in the pool is monitored in real time using moving averages. In addition to actual responses, response times are valuable information with tremendous potential to reveal items that may have been leaked. Specifically, examinees that have preknowledge of an item would likely respond more quickly to it than those who do not. Therefore, the current study proposes several augmented methods for the detection of compromised items, all involving simultaneous monitoring of changes in both the proportion correct and average response time for every item using various moving average strategies. Simulation results with an operational item pool indicate that, compared to the analysis of responses alone, utilizing response times can afford marked improvements in detection power with fewer false positives.

Keywords: test security; response time; computerized adaptive testing; sequential analysis; change-point detection; repeated significance tests (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11336-017-9596-3

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