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AI as a driver of quality education in public universities. A bibliometric review

<p><span>Artificial intelligence (AI) is transforming teaching in public universities, enabling improvements and aiming for quality education. The purpose of this bibliometric research was to analyse the impact of AI on educational quality in public universities. The methodology used was a qualitative approach at a descriptive level, which included terms related to artificial intelligence and quality education in public universities; analysing 488 Scopus documents between 1987 and 2024, through the Vosviewer and Bibliometrix tools; and a review of 43 authors cited between 2020 and 2024 in the introduction and literature. The results reveal a growing interest in AI to personalise learning, provide high-quality resources and promote sustainability. Its potential to differentiate teaching and address specific needs of diverse learners is highlighted. It is concluded that AI can improve educational quality and equity, but strategies for ethical and responsible implementation are required, addressing challenges such as teacher training and change management.</span></p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0