BRIGHTMINDS - Adaptive Learning Platform with Focus Tracking for Autistic Children
Abstract
Educators working with autistic students face challenges in addressing highly individualized learning and attention patterns using conventional e-learning platforms. These systems lack the adaptability required to respond to the cognitive and neurological diversity of autistic learners, limiting learning effectiveness. This paper presents an AI-driven neuroadaptive learning framework that integrates electroencephalography (EEG) sensors to continuously monitor attention and cognitive
engagement. A Generative Artificial Intelligence (GenAI) model is employed to produce personalized instructional content and
assessments, while a reinforcement learning (RL) agent uses quiz outcomes and EEG-derived attention scores as reward
signals to adapt content difficulty, modality, and pacing. The framework also includes a personalized analytics dashboard
that provides educators with insights into attention trends and learning progress. By aligning instructional content with realtime
neurophysiological feedback, the proposed system enhances engagement, personalization, and learning efficiency for autistic
students, demonstrating the potential of neuroadaptive AI in inclusive education.
Keywords:
Autism Spectrum Disorder (ASD),, Neuroadaptive Learning,, Electroencephalography (EEG),, Generative Artificial Intelligence, Reinforcement Learning.Published
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Copyright (c) 2026 International Journal on Emerging Research Areas

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