An AI Gen and LLM-Based Platform for Pedagogical Support and Sensory Accommodations for Neurodivergent Students
Year: 2025
Type: conference-paper
Abstract: Context This research focuses on inclusive, personalized learning for neurodivergent students within educational contexts. The motivation arises from the need for sensory accommodations due to sensory processing challenges commonly experienced by individuals with conditions like ASD and ADHD. Problem Neurodivergent individuals often face sensory integration challenges that impact their school, family, and clinical environments. Without proper accommodations, these challenges hinder development and learning, placing additional demands on teachers and therapists. This problem spans technological, social, and educational dimensions, as inadequate support systems may compromise well-being and intervention effectiveness. Solution The proposed solution is a generative AI platform that uses Small and Large Language Models (SLMs and LLMs) to suggest personalized pedagogical activities and sensory accommodations. It supports teachers, families, and therapists by continuously adjusting approaches to meet students’ individual needs. IS Theory The research is grounded in Sociotechnical Systems Theory, examining the interplay between technology and human factors to ensure a balanced, effective solution within its usage environment. Method A Proof of Concept was employed with qualitative and quantitative methods, including expert interviews and platform testing to gather feedback on functionality and effectiveness. Results Summary Preliminary findings show high user acceptance and improved sensory adaptation for students. The platform demonstrates potential for dynamic, individualized sensory support. Contributions and Impact on IS This research expands generative AI applications in inclusive education, offering an innovative approach for personalized sensory accommodations. Insights from this study could guide academics and practitioners in developing scalable, human-centered support systems for educational and clinical settings.
Authors: Vanderlene C. Rocha, Jacqueline T. de Queiroz, Carlo M. R. da Silva
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410160016