Integrating Artificial Intelligence with Assistive Technology to Expand Educational Access through Speech to Text, Eye Tracking and Augmented Reality

Abstract

This study investigates the integration of artificial intellig3ence-powered assistive technologies (speech-to-text, eye-tracking, and augmented reality) within educational curricula to enhance accessibility for students with diverse learning needs and physical disabilities. Through a mixed-methods approach involving 240 students across 12 educational institutions, we implemented and evaluated an AI-driven assistive technology framework that adapts to individual learner profiles and provides real-time accessibility support. Results demonstrate significant improvements in learning outcomes (Cohen’s d = 1.23), student engagement (78% increase), and curriculum accessibility (92% of previously inaccessible content became accessible). The integrated AI system successfully personalized assistive interventions, reducing cognitive load by 34% and improving task completion rates by 56% among students with disabilities. These findings provide evidence for the transformative potential of AI-integrated assistive technologies in creating truly inclusive educational environments and offer a scalable framework for institutional implementation.