Academic misconduct stemming from file-sharing websites is an increasingly prevalent challenge in tertiary education, including information technology and engineering disciplines. Current plagiarism detection methods (e.g., text matching) are largely ineffective for combatting misconduct in programming and mathematics-based assessments. For these…

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…

Identifying illicit behavior in survey research is inherently problematic, since self-reports are untrustworthy. We argue that fraudulent interviewers can, however, be identified through statistical deviance of the distributional parameters of their interviews. We document that a high proportion of the variation in the data is due to the…

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…

Contract cheating -- outsourcing student assignments for a fee -- presents a growing threat to the integrity of higher education. As contract cheating is based on students purchasing assignments that are original (albeit not created by the student), traditional plagiarism detection tools remain insufficient to detect contract cheating. Part of the…

Cheating behaviors have been construed as a continuing and somewhat vexing issue for academic institutions as they increasingly conduct educational processes online and impose metrics on instructional evaluation. Research, development, and implementation initiatives on cheating detection have gained new dimensions in the advent of artificial…

Artificial intelligence (AI) first made its entry into higher education in the form of paraphrasing tools. These tools were used to take passages that were copied from sources, and through various methods, disguised the original text to avoid academic integrity violations. At first, these tools were not very good and produced nearly…

As with any innovation, the adoption and diffusion of digital technologies in higher education have also brought unintended consequences. This article discusses the unintended misuse of these technologies in the higher education setting. Depending upon severity, these consequences discussed--distraction, addiction, academic dishonesty, and…

Because scores on high-stakes tests influence many decisions, tests need to be secure. Decisions based on scores affected by preknowledge of items are unacceptable. New methods are needed to detect the new cheating strategies used for computer-administered tests because item pools are typically used over time, providing the potential opportunity…

Practical and effective methods for detecting copying of multiple-choice test responses have been available for many years. These methods have been used routinely by large admissions and licensing testing programs. However, these methods are seldom applied in the areas of standardized or classroom testing in schools or colleges, and knowledge…