Assistive Generative AI for Visually Impaired Learners: Personalization and Inclusion in Higher Education

Synthesis: Assistive Generative AI for Visually Impaired Learners: Personalization and Inclusion in Higher Education — Khlaif, Alshakhshir, Hamamra & Joma (2026) present a qualitative case study of 21 visually impaired undergraduate students across three Palestinian universities, examining how generative AI functions as an assistive technology for inclusive learning. Thematic analysis of semi-structured interviews reveals that GenAI enables personalized adaptation, inclusive access, teacher augmentation, educational parity, and lifelong learning, while six technological attributes — interactivity, user-friendliness, affordability, multimodality, integration, and scalability — underpin Accessibility in low-resource contexts. The study extends digital equity discourse by framing inclusion as both infrastructural and cultural, contributing to SDG 4 in a Global South higher education setting.

Key Findings

• Personalized adaptation — GenAI tailors pace, content, and delivery to individual learning profiles, giving visually impaired learners a sense of autonomy and confidence in class participation, extending adaptive learning theories to emphasize modality flexibility and immediacy.
• Inclusive access — GenAI simplifies complex academic texts, converts content across modalities (text, audio, visual), and provides real-time feedback, making materials usable that were previously inaccessible; immediacy is framed as a foundational accessibility requirement rather than a convenience.
• Teacher augmentation — Learners consistently view GenAI as complementing rather than replacing teachers, supporting teacher capacity through adaptive content creation and engaging pedagogies while preserving human connection.
• Educational parity and lifelong learning — GenAI levels the playing field across digital, geographic, and socioeconomic divides and supports continuous skill development beyond graduation.
• Six interdependent technological features — interactivity, user-friendly design, economic accessibility, Multimodal AI capabilities, seamless integration (e.g., with LMS platforms), and scalable access collectively determine whether GenAI is genuinely accessible; usability, affordability, and accessibility are mutually reinforcing rather than separate design considerations.
• Equity, fairness, and global collaboration — GenAI bridges the digital divide, supports responsible use and bias mitigation, removes linguistic and cultural barriers, and enables cross-border intercultural exchange, broadening inclusion to encompass belonging, voice, and representation.
• Theoretical contributions — The findings extend technology acceptance models to disability contexts by showing the interdependence of usability, affordability, and accessibility, and reframe digital equity as both an infrastructural and a cultural matter.

Connected Concepts

• Accessibility
• Inclusive Learning
• Assistive Technology
• Equity
• Generative AI
• Higher Education
• Qualitative Research
• Global South

Connected Articles

• Perceptions Of Generative AI in the Global South: A Scoping Review
• Same Question, Different Answer? Measuring and Mitigating Prompt Privilege for Equitable AI Access
• Touching and Feeling the Data: A Reusable Software Pipeline for Tactile Statistical Graphs in Accessible Education
• Access is Not Enough: Human Support Improves Engagement with AI Tutoring

Citation

Khlaif, Z. N., Alshakhshir, R., Hamamra, B., & Joma, A. (2026). Assistive generative AI for visually impaired learners: Personalization and inclusion in higher education. International Journal of Artificial Intelligence in Education, 36, 100008.