Research Summary: AI as a conditional accessibility resource in deaf EFL higher education: instructor perceptions from an Iranian university context

A qualitative study explored the perceptions of university instructors regarding the use of Artificial Intelligence (AI) tools in teaching English to Deaf and hard-of-hearing (DHH) students within an Iranian higher education context. The research involved semi-structured interviews with 12 instructors to understand their views on generative AI, machine translation, captioning, speech-to-text, grammar feedback, image generation, and visualization tools, particularly in a multilingual and multimodal learning environment.

Why it matters

This study is strategically important for understanding how AI can enhance educational accessibility for specific student populations, particularly DHH learners in complex linguistic environments. Insights gained can inform the development of more inclusive educational technologies and teaching methodologies, fostering equitable learning opportunities globally.

Key insights

• The study focused on instructor perceptions of AI tools for teaching English to Deaf and hard-of-hearing students.
• The research context was an Iranian university, characterized by DHH students with varied prior exposure to Esharani/ISL, Persian, and English.
• Interviews were conducted with 12 instructors, including 10 hearing English as a Foreign Language (EFL) instructors and 2 Deaf instructors.
• The study investigated actual, informal, and prospective uses of various AI technologies.
• Specific AI tools examined included generative AI, machine translation, captioning, speech-to-text tools, grammar feedback mechanisms, and image generation/visualization tools.
• Reflexive thematic analysis identified five themes, with one explicitly mentioned as 'AI as visual-semantic'.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1951268