Addressing Academic Dishonesty in Higher Education: A Systematic Review of Generative AI’s Impact

Abstract

Generative Artificial Intelligence (GAI) introduces new opportunities for society. While some universities have adopted GAI with a more hostile stance, others have done so with a more progressive perspective. In light of this contradiction, the main query is what is causing this controversy. The ethical issues surrounding GAI and academic dishonesty in higher education, however, are the special focus of the current study. 23 previous studies published between 2022 and 2024 served as the foundation for this systematic literature review (SLR). Three educational theories—digital innovation, diffusion of innovation, and thing ethnography—form the basis of this study. A content analysis of the research corpus was done to find important themes. The findings are synthesized by employing a novel thematic analysis approach. Research questions determine the feasibility of academic integrity in the face of plagiarism or cheating. Considering GAI, existing curricula and assessment procedures show room for modification. There are technological, institutional, or individual issues around academic dishonesty. Furthermore, problems with legitimacy and ethics are also evident. The current guidelines are consistent rather than cohesive. Based on this idea, the current researchers proposed a thorough set of guidelines for the education community. The results of this study are thought to offer comprehensive insights into addressing academic dishonesty in higher education, especially in the age of GAI. The proposed ethical framework explains how it can theoretically contribute to higher education.

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