Enhancing Technical Education for People with Visual Impairments Using Artificial Intelligence

People with visual impairments remain critically underrepresented in technical education and science, technology, engineering, and mathematics (STEM) disciplines worldwide. Despite decades of legislative mandates and accessibility standards, fundamental barriers persist: programming environments remain largely visual, mathematical notation is predominantly conveyed through sight-dependent formats, laboratory work assumes visual observation, and digital learning platforms frequently fail to meet even basic accessibility requirements. This paper presents a comprehensive examination of how artificial intelligence (AI) technologies can systematically address these barriers and enhance technical education for learners with visual impairments. We organise our analysis around six categories of AI-enabled interventions: (i) natural language processing (NLP) and large language models (LLMs) for intelligent content transformation and description generation; (ii) computer vision systems for real-time scene understanding, object recognition, and diagram interpretation; (iii) automatic speech recognition and synthesis for hands-free interaction with technical tools; (iv) adaptive learning systems that personalise instructional content based on individual needs and modalities; (v) AI-powered code accessibility tools including intelligent code navigation and auditory programming environments; and (vi) multimodal AI assistants that integrate vision, language, and speech for comprehensive educational support. We propose the AI-Enhanced Accessible Technical Education (AI-ATE) framework that maps specific AI capabilities to identified barriers across the technical education lifecycle. The paper concludes with a research agenda identifying priority directions for the field.

Keywords: visual impairment, technical education, artificial intelligence, accessibility, assistive technology, STEM education, natural language processing, computer vision, adaptive learning, inclusive education.