THE USE OF ARTIFICIAL INTELLIGENCE IN DETECTING ACADEMIC FRAUD
This article aims to examine the use of artificial intelligence in identifying academic fraud, with a particular focus on the situation in Romania. Nowadays Academic fraud is a persistent problem in higher education, including in Romania, where practices such as plagiarism and cheating in examinations have long been tolerated, even at the highest levels. The emergence of new technologies, particularly artificial intelligence (AI), has both amplified these phenomena through tools such as text generators like ChatGPT, used to obtain ostensibly original work with minimal effort and spurred the development of advanced countermeasures. At present, universities and authorities in Romania rely on anti-plagiarism software based on artificial intelligence algorithms to screen academic papers. Automated online proctoring systems and stylometric methods of text analysis are also being piloted, with a view to identifying both traditional plagiarism and more subtle forms of academic fraud, such as contract cheating and AI-generated content. This paper examines the role of AI in detecting academic fraud, with a focus on the Romanian context: from the techniques used to uncover plagiarism and other breaches (including the use of AI to counter cheating facilitated by modern technologies) to recent institutional initiatives and the associated ethical challenges. Although artificial intelligence holds out the promise of increasingly powerful tools for safeguarding academic integrity, it simultaneously raises concerns regarding accuracy, fairness, and the protection of students’ rights. This study concludes by arguing for the need to strike a balance between the adoption of technology and the promotion of a culture of integrity adapted to the challenges of the digital age.
Authors
- ZAMFIR PAUL - BOGDAN
Institutions
- Constantin Brâncuși University of Targu Jiu (RO)
Publication Details
- Journal
- SHILAP Revista de lepidopterología
- Published
- 2025-10-01
- Primary Topic
- Academic integrity and plagiarism
- Type
- article
- Field-Weighted Citation Impact
- 0.00