AI-Driven Assistive Technologies for Inclusive Learning in Special Education Environments

Abstract

Inclusive education of learners with disabilities is still limited by a lack of personalization, poor assistive infrastructure, and cognitive and sensory variability. Old methods of teaching are not usually dynamic and thus learners are not as engaged and do not learn effectively. This paper will solve these problems by suggesting an AI-based assistive learning model that can be used in a special education setting. The overall goal is to make intelligent technologies more accessible, personalized and adaptive to promote learning. The suggested research methodology is a combination of machine learning, natural language processing, and computer vision in order to create multimodal assistance systems, such as speech-to-text systems, emotion-aware tutoring agents, or adaptive content recommendation engines. The system capitalizes on real-time data about learners to customize the instructional plans according to cognitive profiles and behavioral reactions. The experimental assessment was done in a variety of learners groups and between the traditional assistive devices and the suggested AI-based system. Findings show a tremendous growth: learning engagement was enhanced by 42.6, task completion rates were enhanced by 37.8, accuracy to understand the content was improved by 33.4, and response time was reduced by 28.1% as compared to traditional techniques. Also, the level of accessibility to visually and hearing-impaired learners increased by 45.2, which means a strong inclusivity. The application of this study to scalable implementation into smart classrooms, integration with learning platforms, and real-time adaptive interventions to various disabilities are all applications of this study. The framework assists educators to have actionable information and encourages learner autonomy. To sum up, AI-based assistive technologies offer a revolutionary method of inclusive learning to allow personalized, efficient, and accessible learning. The suggested system shows a significant potential of bridging the educational gap and providing the students with special needs with equal educational opportunities.