Exploring AI-Enabled Educational Support Systems for Blind and Visually Impaired Students
Abstract
This study investigates the role of AI-enabled educational support systems in improving learning experiences for blind and visually impaired students. The research addresses three main questions: identifying current AI tools and their core functionalities, evaluating their effectiveness in addressing accessibility, engagement, affordability, and adaptability, and exploring their strengths, limitations, and potential improvements from the perspectives of students, educators, and accessibility experts. Recognizing the growing role of artificial intelligence in education, this study focuses on its potential to bridge learning gaps for one of the most underserved student populations. A qualitative research design was adopted, using purposive sampling to select 25 participants, including visually impaired students, educators, and technology specialists. Data were collected through semi-structured interviews and analyzed thematically to identify patterns and insights. The analysis revealed six key themes: accessibility enhancement, personalized learning, content accessibility, engagement and motivation, skill development, and challenges. Findings indicate that AI tools such as screen readers, real-time text recognition software, adaptive learning platforms, and automated content conversion technologies significantly improve content accessibility and personalize learning experiences. The study concludes that AI-enabled systems offer considerable benefits but require thoughtful integration with human support to maximize effectiveness and address emotional as well as academic needs. This research contributes to the growing body of knowledge on inclusive education technology by highlighting both the transformative potential and the limitations of AI for visually impaired learners. The findings provide actionable recommendations for policymakers, educators, and technology developers to create more equitable and effective educational environments.
Keywords: AI, Educational Support, Systems for Blind and Visually Impaired Students
