ARTIFICIAL INTELLIGENCE AND PERSONALIZED LEARNING FOR NEURODIVERGENT STUDENTS

Abstract

The research aimed to understand how artificial intelligence contributed to the personalization of learning for neurodivergent students, considering their cognitive and emotional specificities. The general objective was to analyze how AI acted in adapting pedagogical strategies that favored the development of attention, memory, and self-regulation. The study adopted a bibliographic methodology with a qualitative approach, based on the analysis of articles, book chapters, and conference proceedings published between 2020 and 2025. The review and interpretation of the selected sources revealed educational experiences supported by adaptive platforms, digital games, and virtual reality environments focused on inclusion. The results showed that artificial intelligence enabled the creation of personalized learning paths, strengthening students’ engagement, autonomy, and concentration. It was also observed that the teacher’s role remained essential for the pedagogical application of technology, emphasizing the importance of continuous training and human mediation in the teaching process. The analysis indicated that although AI expanded the possibilities for inclusion, ethical challenges related to data privacy and digital infrastructure still persisted. It was concluded that artificial intelligence represented a promising resource for inclusive education, provided that it was used with sensitivity, ethics, and pedagogical planning. Further studies were recommended to deepen the understanding of the effects of technological personalization on the learning of students with different neurodivergent profiles.