The Impact of Generative AI on Student Learning Outcomes: A Systematic Review of Empirical Studies (2020–2025)

Abstract

Higher education is undergoing a revolution due to the fast-developing generative artificial intelligence (AI) solutions, including ChatGPT, Whisper, and DALL E. This review will capture a synthesis of evidence-based articles published in the period 2020 onwards aimed at establishing the impact of generating AI on the learning capabilities of students, learning engagement and motivation, cognitive development, and performance in academic learning among higher education institutions. The search was done logically utilizing databases including Scopus, Web of Science, and Google Scholar. Peer-reviewed empirical studies on generative AI use in classroom situations were the target of inclusion criteria. The selection and screening process followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement framework which led to 12 empirical studies being included. Emotional well-being, AI literacy, and discipline specialization were determined as key moderators of effectiveness. The study revealed more productivity and less anxiety amongst students. However, issues of academic integrity, over-dependency, and correctness of content were prevalent. Students and teachers both expressed the importance of policies and support for the use of ethical AI. In conclusion, generative AI has great potential to change the learning experiences by improving engagement, personalization, and accessibility.

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