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 emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…

The development of statistical methods for detecting test collusion is a new research direction in the area of test security. Test collusion may be described as large-scale sharing of test materials, including answers to test items. Current methods of detecting test collusion are based on statistics also used in answer-copying detection.…

Explored, using simulations, the use of disclosed items on continuous testing conditions under a worse-case scenario that assumes that disclosed items are always answered correctly. Some item pool and test designs were identified in which the use of disclosed items produces effects on test scores that may be viewed as negligible. (Author/MAK)