ARTIFICIAL INTELLIGENCE AS A FACILITATOR IN PERSONALIZED EDUCATION: POTENTIAL AND CHALLENGES IN THE BRAZILIAN EDUCATIONAL CONTEXT

Abstract

Personalized learning emerges as a crucial pedagogical approach to meet the diverse needs, paces, and learning styles of students. However, its large-scale implementation faces significant challenges, especially in complex educational systems like Brazil's. This article investigates the role of Artificial Intelligence (AI) as a potential facilitator of personalized learning in Brazil. Through a systematic literature review, we analyze how different AI applications – including Adaptive Learning Systems (ALS), Intelligent Tutoring Systems (ITS), Learning Analytics (LA), and Recommendation Systems – can contribute to adapting content, pace, support, and educational resources to the individual characteristics of each student. We discuss the potential of these technologies to promote engagement, autonomy, and performance improvement, with special attention to application possibilities in the Brazilian context, considering the guidelines of the National Common Curricular Base (BNCC) and equity challenges. However, the article also critically explores the obstacles to the effective adoption of AI in personalized learning in Brazil, such as the digital divide, the need for specific teacher training, ethical issues related to data privacy and algorithmic biases, the pedagogical quality of solutions, and the sustainability of initiatives. We conclude that, although AI offers promising tools, its contribution to effective and equitable personalized learning in Brazil depends on robust public policies, investments in infrastructure and training, development of contextually relevant solutions, and a pedagogical approach that places AI at the service of the student's integral development, mediated by critical and prepared educators.