Evaluating AI-Powered Assistive Technologies in Inclusive Education: A Systematic Review of Literature on Efficacy and Accessibility

This study aims to This study explores the potential of artificial intelligence (AI) tools to enhance accessibility and foster inclusive education for students with diverse learning needs. It also seeks to identify the challenges and limitations in integrating these technologies into educational practices. A comprehensive search was conducted across multiple academic databases, including EBSCOhost, ERIC, JSTOR, ScienceDirect, and Google Scholar, to assure the inclusion of high-quality studies and facilitate a comprehensive literature selection process. The data collected were processed using advanced data mining techniques, which enabled the systematic extraction of meaningful patterns, trends, and relationships from large and diverse datasets. These techniques included text mining for thematic analysis, as well as clustering and classification methods to group similar data points. The results show that AI integration in inclusive education significantly enhances learning outcomes, accessibility, and personalized support for diverse learners. AI technologies hold significant promise for advancing inclusive education by enhancing personalization, support, and learning outcomes for students with diverse needs. While effective in improving academic performance and engagement, successful integration requires addressing challenges such as resource constraints, ethical considerations, and educator readiness. Realizing AI’s full potential demands inclusive frameworks and collaboration among educators, developers, and policymakers. Key recommendations include educator training, inclusive design, infrastructure development, cross-sector collaboration, and ongoing evaluation to ensure equitable and empowering learning experiences for all.