Reassessing academic integrity in the age of AI: A systematic literature review on AI and academic integrity

Abstract

Academic integrity is a key factor in the quality of education that represents honesty, trust, and ethical conduct. In today's rapidly changing educational landscape, artificial intelligence (AI) poses significant challenges to the educational ecosystem's ability to maintain academic integrity. It also affects the qualifications offered by institutes. Although AI supports students in completing academic tasks, it usually risks violating the basic rules of academic integrity. In addition, AI can be used to detect academic misconduct. This study aims to critically examine the impact of AI on academic integrity through a systematic literature review. The research question was developed using the PICO framework, and the articles considered in this study were collected from Scopus, PubMed, DOAJ, and Base. Of 1443 articles, 25 were selected based on the PRISMA framework. We used the Cochrane risk of bias tool (ROBINS-1) to analyse the risk of bias in the selected studies. The discussion section was developed based on PICO frameworks – population of the study, intervention with AI tools, comparison of modern and traditional methods, and outcome of AI use for academic activities – to answer the research question. This research contributes to the ongoing dialogue about AI and academic integrity by emphasising the importance of a balanced approach to using the benefits of AI in education while upholding ethical standards. This study concludes by emphasising the importance of creating a culture of academic integrity to ensure the ethical use of AI for educational purposes.