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…

This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

Academic misconduct and academic integrity are issues of importance to Higher Education Institutions (HEIs). Phraseologies and practices may conflate unintentional mistakes with attempts to gain illegitimate advantage, with some groups potentially at higher risk. HEIs across the United Kingdom (UK) responded to a Freedom of Information Act (FOI)…

Fraudulent published papers were once thought to be rare, but in recent years, there has been growing awareness of coordinated activities by for-profit organizations that charge authors a fee to sell articles and submit them to reputable journals. These are known as paper mills. We reflect here on how "Mind, Brain and Education" suffered…

This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…

The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…

This research aimed to identify patterns, intellectual structure, contributions, social interactions, gaps, and future research directions in the field of academic integrity (AI). A bibliometric analysis was conducted with 1406 publications covering the period 1966-2023. The results indicate that there has been significant growth in AI literature…

Detecting and punishing violations of research integrity requires first having to prove them. However, establishing proof of research misconduct presents a number of challenges. Firstly, it has to be conducted in a variety of contexts, including before research integrity officers, university disciplinary committees, civil courts, criminal courts,…

Anonymous marking, as a means to mitigate bias in grading, involves evaluating student work with their identities withheld. Anonymous marking is explored in this self-study to mitigate implicit bias, which negated a practitioner-researcher's educational values. The mixed methods action research findings show withholding student identities during…

The convenience and flexibility of online assessments can be beneficial in a variety of ways, but they can also pose risks and challenges, such as potential academic dishonesty by students. This study included 73 master's and doctoral students and investigated the relationship among their attitudes, experiences, and performance in an online…

Teaching staff play a pivotal role in the prevention, detection and management of cheating in higher education. They enact curriculum and assessment design strategies, identify and substantiate suspected cases, and are positioned by many as being on the 'front line' of a battle that threatens to undermine the integrity of higher education. Against…

The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…

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,…

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…

Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…