Redefining Education in the Digital Age: The Role of GPT Models in Academic Fraud and Logistics

Abstract

The integration of artificial intelligence (AI), especially tools like generative pretrained transformer (GPT), in education has created new challenges, most notably a surge in academic misconduct such as plagiarism, exam cheating, and unethical collaboration. Guided by the fraud diamond theory, this study examines the factors that lead to academic cheating—pressure, opportunity, rationalization, and capability, with AI as a moderating factor. It involved 630 students selected through nonprobability sampling across general studies, natural sciences, and social sciences in Central Java, Indonesia. Using a quantitative approach, data were collected and analyzed using moderated regression analysis (MRA). Instrument testing confirmed strong validity and high reliability. Findings reveal that AI attenuates the effects of pressure, rationalization, and capability on academic fraud but exerts no moderating influence on opportunity. AI heightened the influence of capability, showing that technically skilled students with fraudulent intent are at greater risk of misconduct. This highlights the need for field‐specific strategies, structural changes, and ethical education. It further advocates for integrating AI ethics into curricula, enhancing faculty capacity, and adopting alternative assessment methods. While AI demonstrates potential as a mitigating tool, it must be combined with strong rules, support systems, and educational logistics to uphold academic integrity.