ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A GLOBAL REVIEW OF AI-POWERED TEACHING AND LEARNING
DOI:
https://doi.org/10.5281/zenodo.20817569Keywords:
artificial intelligence, higher education, generative AI, teaching and learning, Technology Acceptance Model, TPACK, adaptive learning, academic integrity, AI literacy, UNESCO, self-regulated learningAbstract
Artificial intelligence, particularly generative AI systems such as ChatGPT, Gemini, and Claude,
has moved from the periphery to the mainstream of higher education in less than four years. By 2025, several
international surveys had reached a common conclusion: AI use among university students is approaching
universality, while institutional governance, faculty competence, and pedagogical theory are gradually adapting
to this rapid development. This article synthesises peer-reviewed empirical research published in 2020–2026,
together with reports by UNESCO, the OECD, the Russell Group, the Digital Education Council, the Higher
Education Policy Institute, Ellucian, and EDUCAUSE, to provide a global and theoretically grounded analysis of
the current state of AI-powered teaching and learning. The article examines adoption trends, key technologies,
theoretical frameworks, opportunities and challenges, policy responses across different jurisdictions, and future
directions, including AI literacy as a graduate attribute, hybrid human–AI pedagogies, and the redefined role of
the educator. The analysis concludes that AI adoption in higher education is no longer a question of trajectory
but of governance, and that the pedagogy of integration, rather than the technology itself, determines whether
AI strengthens or limits learning outcomes.
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