Test takers wishing to gain an unfair advantage often share answers with other test takers, either sharing all answers (a full key) or some (a partial key). Detecting key sharing during a tight testing window requires an efficient, easily interpretable, and rich form of analysis that is descriptive and inferential. We introduce a detection method…

The rise of online proctoring potentially provides more opportunities for item harvesting and consequent brain dumping and shared "study guides" based on stolen content. This has increased the need for rapid approaches for evaluating and acting on suspicious test responses in every delivery modality. Both hiring proxy test takers and…

Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of…

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…

Distance learning has become a popular phenomenon across the world during the COVID-19 pandemic. This led to answer copying behavior among individuals. The cut point of the Kullback-Leibler Divergence (KL) method, one of the copy detecting methods, was calculated using the Youden Index, Cost-Benefit, and Min Score p-value approaches. Using the cut…

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…

Drasgow, Levine, and Zickar (1996) suggested a statistic based on the Neyman-Pearson lemma (e.g., Lehmann & Romano, 2005, p. 60) for detecting preknowledge on a known set of items. The statistic is a special case of the optimal appropriateness indices of Levine and Drasgow (1988) and is the most powerful statistic for detecting item…

A potential negative consequence of high-stakes testing is inappropriate test behaviour involving individuals and/or institutions. Inappropriate test behaviour and test collusion can result in aberrant response patterns and anomalous test scores and invalidate the intended interpretation and use of test results. A variety of statistical techniques…

In continuous testing programs, some items are repeatedly used across test administrations, and statistical methods are often used to evaluate whether items become compromised due to examinees' preknowledge. In this study, we proposed a residual method to detect compromised items when a test can be partitioned into two subsets of items: secure…

In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive…

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…

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…

Benefiting from item preknowledge (e.g., McLeod, Lewis, & Thissen, 2003) is a major type of fraudulent behavior during educational assessments. This paper suggests a new statistic that can be used for detecting the examinees who may have benefitted from item preknowledge using their response times. The statistic quantifies the difference in…

In this study Type I Error and the power rates of omega (?) and GBT (generalized binomial test) indices were investigated for several nominal alpha levels and for 40 and 80-item test lengths with 10,000-examinee sample size under several test level restrictions. As a result, Type I error rates of both indices were found to be below the acceptable…

Purpose: Several studies can be found in the literature that investigate the performance of ? under various conditions. However no study for the effects of item difficulty, item discrimination, and ability restrictions on the performance of ? could be found. The current study aims to investigate the performance of ? for the conditions given below.…