Exploring AI Opportunities in Deaf Education: Understanding Design Needs Through Teacher and Parent Perspectives in Bangladesh

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Authors: Md. Ataur Rahman Bhuiyan, Nadim Mahmud Dipu, Tanvir Rahman, Oindri Aurunima Sarker, Shidhartha Chakrabarty Turzo, Jannatun Noor
Cited by: 1
References: 102

Abstract

AI-driven educational technologies are expanding rapidly, yet their design rarely reflects the linguistic and infrastructural realities of Deaf learners in low-resource contexts. This qualitative study investigates how teachers, parents, and Deaf students in Bangladesh navigate fragile visual access, inconsistent Bangla Sign Language, and unreliable technology in everyday learning. Through interviews and focus groups with 13 teachers, eight parents, and five Deaf students, we show how small disruptions in sightlines, pacing, or sign clarity can quickly collapse comprehension, making accessibility a condition that must be constantly protected. We identify opportunities for AI to act as access support by stabilizing visual information, ensuring teacher-validated Bangla Sign Language, enabling offline use, and protecting emotional safety when seeking help. We contribute a model of learning continuity that explains how visual, linguistic, and affective stability interact in Deaf education and offer concrete design directions for AI-driven learning tools in the Global South.

Fields of Study & Subjects

Hearing Impairment and Communication Hand Gesture Recognition Systems Assistive Technology in Communication and Mobility

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–18
Publication date
13 April 2026