Artificial Intelligence and Personalised Learning in Higher Education: An Approach from Learning Analytics

Abstract

Artificial intelligence and learning analytics have significantly transformed higher education by strengthening personalised learning and optimising teaching and learning processes within contemporary university environments. The study focused on analysing the influence of these technologies on educational personalisation, considering their pedagogical, technological and ethical implications in strengthening university training processes. The research was developed from a qualitative and interpretative approach through a systematic process of collecting, selecting and analysing specialised scientific sources, complemented by the PRISMA model to ensure rigour, transparency and methodological organisation in the treatment of information. To achieve this, academic articles, books, theses and specialised reports related to artificial intelligence, learning analytics and higher education were examined. The findings revealed that intelligent technologies favour content adaptation, continuous monitoring of academic performance and the generation of more flexible, inclusive and student-centred learning experiences. Likewise, it was identified that learning analytics strengthens institutional decision-making and contributes to the early detection of academic difficulties. Nevertheless, challenges related to ethics, data privacy, the digital divide and teacher training within contemporary university contexts were also recognised.