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Sinharay, Sandip; Johnson, Matthew S. – Journal of Educational and Behavioral Statistics, 2021
Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2021
Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
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Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), score differencing is one of six types of statistical methods used to detect test fraud. In this paper, we suggested the use of Bayes factors (e.g., Kass & Raftery, 1995) for score differencing. A simulation study shows that the suggested approach performs slightly better than an existing frequentist…
Descriptors: Cheating, Deception, Statistical Analysis, Bayesian Statistics
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Man, Kaiwen; Harring, Jeffery R.; Ouyang, Yunbo; Thomas, Sarah L. – International Journal of Testing, 2018
Many important high-stakes decisions--college admission, academic performance evaluation, and even job promotion--depend on accurate and reliable scores from valid large-scale assessments. However, examinees sometimes cheat by copying answers from other test-takers or practicing with test items ahead of time, which can undermine the effectiveness…
Descriptors: Reaction Time, High Stakes Tests, Test Wiseness, Cheating
Frary, Robert B.; Tideman, T. Nicolaus – 1976
The development of an index reflecting the probability that the observed correspondence between multiple choice test responses of two examinees was due to chance in the absence of copying was previously reported. The present paper reports the implementation of a statistic requiring less restrictive underlying assumptions but more computation time…
Descriptors: Bayesian Statistics, Cheating, Data Processing, Multiple Choice Tests