Artificial Intelligence-Driven Inclusive Education Management: Enhancing Accessibility and Learning Outcomes for Students with Disabilities

Abstract

The education system is undergoing a significant transformation through the power of Artificial Intelligence (AI), which is making learning more accessible, personalized, and inclusive for students with disabilities. The present study explores the contribution of AI based inclusive education management to the improvement of accessibility and learning outcomes of students with disabilities. Designations of quantitative research type were used and the data collected were primary data that was gathered via a structured questionnaire from 210 respondents consisting of a student with disabilities, teachers, special educators, academic administrators, and educational support staff. Five aspects of AI in inclusive education management were studied: Accessibility Support Systems, AI-Based Assistive Technologies, Personalized Learning Systems, Intelligent Tutoring Systems, and Predictive Analytics and Student Monitoring. The data were analysed on SPSS by reliability analysis, descriptive statistics and multiple regression analysis. The results showed that the reliability of all constructs was good, as Cronbach's Alpha values were above 0.70. The regression results showed that all five dimensions had significant and positive influence on learning outcomes, meaning that all five dimensions explained 65.9% of the variance of the dependent variable. The main predictor of learning outcomes was Personalized Learning Systems. The study finds that AI-driven educational technologies have a significant impact in promoting the accessibility, participation, engagement, satisfaction, and academic outcomes of students with disabilities, which leads to more inclusive and equitable learning environments.