Abstract:

This study addresses the need to provide effective support to students with learning disorders, such as Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), in the secondary education context. Considering that ADHD affects 5-7% of children globally and ASD affects approximately 1 in every 160 children, this work highlights the importance of inclusive and personalized educational strategies to ensure the academic and socio-emotional success of these students. Faced with resource scarcity and stigmatization, alongside the complexity in secondary education, where greater autonomy and academic competence are demanded, we propose the use of Large Language Models (LLMs) as an innovative solution for personalization. Specifically, a tool is proposed that develops individualized educational profiles and automatically adapts teaching material using LLMs, thus providing an adaptive response to unique learning needs. Preliminary results from two phases of usability testing with teachers and students with ADHD and ASD suggest a significant improvement in the adaptability and effectiveness of educational interventions, opening a pathway for research and development towards the inclusion and educational success of students with special needs and those with ADHD and ASD.

Keywords:

LLMs, ASD, ADHD, App, Student, Teacher.