Impact of generative artificial intelligence on university educational quality: A systematic review
DOI:
https://doi.org/10.5281/zenodo.21302613Keywords:
generative artificial intelligence, higher education, educational qualityAbstract
Generative artificial intelligence has emerged as one of the most influential technological innovations in higher education, transforming teaching, learning, assessment, and institutional management processes. This has generated growing interest in understanding its impact on the quality of university education. In this context, the present study aimed to analyze recent scientific evidence on the influence of generative artificial intelligence on educational quality, considering its implications for academic performance and institutional management during the period 2021–2025. To this end, a systematic literature review was conducted following the PRISMA 2020 guidelines. The search was carried out in the Scopus, Web of Science, ERIC, SciELO, DOAJ, Dialnet, and Latindex databases, supplemented with specialized sources, resulting in a final corpus of 24 studies that met the established inclusion criteria. The results show that generative artificial intelligence promotes personalized learning, immediate feedback, the strengthening of digital skills, and the optimization of academic management processes. Challenges were also identified related to academic integrity, algorithmic bias, data protection, equity in access to technology, and the need to strengthen ethical and regulatory frameworks for its implementation. It is concluded that generative artificial intelligence constitutes a strategic resource for the transformation of higher education; however, its contribution to educational quality depends on pedagogical, ethical, and institutional integration that promotes innovation, inclusion, and the development of critical thinking.
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