ARTIFICIAL INTELLIGENCE AND PERSONALIZATION OF EDUCATION: A SYSTEMATIC LITERATURE REVIEW

Abstract

The incorporation of artificial intelligence into education is transforming pedagogical practices, particularly through the personalization of teaching and the development of flexible, student-centered learning pathways. This article presents a systematic literature review aimed at identifying, analyzing, and synthesizing evidence on the use of artificial intelligence to personalize teaching in formal and hybrid educational contexts. The investigation followed the PRISMA protocol and included studies published between 2015 and 2025, retrieved from SciELO, Scopus, ERIC, Web of Science, and Google Scholar. A total of 312 studies were identified, of which 37 met the inclusion criteria. The results indicate that adaptive learning platforms, intelligent tutors, and recommendation algorithms contribute to increasing student motivation and performance by enabling more individualized pedagogical interventions. However, challenges related to algorithmic transparency, reduced human interaction, and teacher training were identified. It is concluded that artificial intelligence has the potential to enhance educational equity and effectiveness when implemented ethically, inclusively, and on a sound pedagogical basis, while maintaining the teacher as a mediator and curator of the educational process.