Generative Artificial Intelligence in Higher Education: A Literature Review of Students’ Usage and Academic Integrity

Abstract

Generative artificial intelligence has rapidly become part of higher education learning environments. Students increasingly rely on applications such as ChatGPT to complete academic tasks and to support comprehension of complex content. This literature review examined patterns of student use of generative artificial intelligence its effects on academic integrity and the effectiveness of university policies that regulate such use. The review was guided by the Technology Acceptance Model which explains adoption through perceived usefulness and ease of use. A systematic literature review following the PRISMA framework was conducted using Google Scholar ERIC Web of Science and Scopus. The search covered empirical studies published between 2022 and 2025 and resulted in the inclusion of 22 peer reviewed studies. The findings show extensive student use of generative artificial intelligence for learning support and assignment preparation. The findings also show clear effects on academic integrity including challenges related to authorship originality and assessment credibility. University policies and practices have been introduced to address these challenges though effectiveness remains limited due to inconsistent implementation and limited staff and student capacity. The review concludes that generative artificial intelligence has reshaped academic practices while placing pressure on existing assessment systems. Stronger alignment between policy assessment design and ethical guidance is necessary to support responsible use of generative artificial intelligence in higher education.

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