Machine learning has evolved and expanded as an interdisciplinary research method for educational sciences. However, cheating detection of test collusion among multiple examinees or sets of examinees with unusual answer patterns using machine learning techniques has remained relatively unexplored. This study investigates collusion on…

Randomized response techniques (RRTs) are useful survey tools for estimating the prevalence of sensitive issues, such as the prevalence of doping in elite sports. One type of RRT, the unrelated question model (UQM), has become widely used because of its psychological acceptability for study participants and its favorable statistical properties.…

When considering a paradigm shift in higher education, it is imperative to focus on removing obstacles against maintaining integrity in academia. One such obstacle is contract cheating sites that have mushroomed disproportionately during the 18 months of emergency distance learning threatening graduate quality and university reputations (McKie,…

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…

The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…

One of the most serious forms of cheating occurs when examinees have item preknowledge and prior access to secure test material before taking an exam for the purpose of obtaining an inflated test score. Examinees that cheat and have prior knowledge of test content before testing may have an unfair advantage over examinees that do not cheat. Item…

This article contributes to an emerging body of research on the role of assessment design in the prevention and detection of contract cheating. Drawing on the largest contract cheating dataset gathered to date (see cheatingandassessment.edu.au), this article examines the types of assignments and exams in which students self-reported having engaged…

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…

Researchers frequently use machine-learning methods in many fields. In the area of detecting fraud in testing, there have been relatively few studies that have used these methods to identify potential testing fraud. In this study, a technical review of a recently developed state-of-the-art algorithm, Extreme Gradient Boosting (XGBoost), is…

Wollack, Cohen, and Eckerly suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This article suggests two modifications of the EDI for…

Wollack, Cohen, and Eckerly (2015) suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly (2017) extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This paper suggests two modifications of…

The primary objective of this paper is to help institutions respond to the stipulation of the Higher Education Opportunity Act of 2008 by adopting cost-effective academic integrity solutions without compromising the convenience and flexibility of online learning. Current user authentication solutions such as user ID and password, security…

Physical separation of students and instructors creates the gap of anonymity and limited control over the remote learning environment. The ability of academic institutions to authenticate students and validate authorship of academic work at various points during a course is necessary for preserving not only perceived credibility but also public…

This study explored undergraduate teaching faculty's perceptions regarding using biometric-based technologies to reduce academic dishonesty in online classes. The first objective was to develop a baseline of the respondents' concerns toward and experience with using biometrics; attitudes, experience, and mitigation strategies used to…