Artificial intelligence models applied to personalised and adaptive learning in higher education

Abstract

University education is undergoing a profound transformation driven by technological advancement and artificial intelligence (AI), which enables the personalisation and adaptation of learning to the individual characteristics and needs of each student. This approach overcomes the limitations of traditional methods, fostering more dynamic, efficient, and student-centred educational experiences. Adaptive learning, based on intelligent algorithms and data analysis, optimises educational processes, enhances academic performance, and encourages student autonomy. However, the heterogeneity of learning styles and paces presents a challenge that many traditional pedagogical models do not effectively address, potentially leading to demotivation and dropout. Despite the availability of technology, many universities have yet to systematically integrate personalised AI models, limiting their potential. This study, through a rigorous documentary review and the application of the PRISMA protocol, examines AI models in higher education to identify advantages, challenges, and impacts, emphasising their capacity to transform and improve tertiary teaching.