Artificial Intelligence in Higher Education: a systematic review across academic disciplines

STAVROULA DIMITRIADOU, STAVROS ATHANASSOPOULOS, VASSILIS KOMIS, STAMATIOS PAPADAKIS, KONSTANTINOS LAVIDAS (Greece)

Abstract

This systematic review examines how higher education students use artificial intelligence (AI) across academic disciplines, including its benefits and concerns. Following PRISMA guidelines, 100 Scopus-indexed studies were analyzed. Findings show disciplinary differences in AI adoption, with Linguistics and Language-related Studies and Medical and Health Sciences reporting the highest use. Benefits include personalized feedback, increased engagement, self-regulated learning, and improved academic performance. However, concerns such as academic integrity risks, over-reliance on AI, ethical and privacy issues, uneven AI literacy, and limited pedagogical alignment persist. The review highlights the need for coherent frameworks, institutional policies, and discipline-specific AI training in higher education.

Keywords

Artificial Intelligence in education, Higher Education, Generative AI, AI literacy, pedagogical integration

DOI: https://doi.org/10.26220/rev.5651

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Re S M ICT E | ISSN: 1792-3999 (electronic), 1791-261X (print) | Laboratory of Didactics of Sciences, Mathematics and ICT, Department of Educational Sciences and Early Childhood Education - University of Patras.

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