AI-Enhanced Strategies for Supporting Students with Deafblindness: Towards an Inclusive and Multisensory Educational Framework.

Abstract

The rapid advancement of artificial intelligence (AI) has created new possibilities for improving accessibility, personalisation, communication, and participation in education. However, the application of AI to students with deafblindness remains underexplored despite the complex barriers these learners encounter in accessing auditory and visual information. This conceptual review examines the potential of AI-enhanced strategies to support students with deafblindness and proposes an AI-Enhanced Multisensory Support Framework for Deafblind Education (AIMS-DB). Drawing upon recent scholarship on artificial intelligence in special and inclusive education, assistive technology, Universal Design for Learning (UDL), and human-centred AI, the paper identifies six interconnected dimensions of AI-supported deafblind education: AI-supported communication, adaptive and personalised learning, multimodal sensory transformation, intelligent environmental access, AI-assisted teacher decision-making, and ethical and human-centred implementation. Emerging technologies such as natural language processing, computer vision, speech recognition, generative AI, wearable technologies, and haptic interfaces could potentially transform inaccessible information into tactile, Braille, textual, auditory, or other individually accessible forms. Nevertheless, technological innovation alone cannot ensure inclusion. Significant challenges remain concerning algorithmic bias, accessibility, data privacy, technological reliability, digital inequality, teacher preparedness, and the limited representation of people with deafblindness in AI research and development. The paper argues that AI should augment rather than replace teachers, interveners, families, and human communication partners. The proposed AIMS-DB framework therefore positions AI as an intelligent accessibility mediator operating between learners and their educational environments. Future research should prioritise participatory design and empirical evaluation involving students with deafblindness to ensure that emerging AI technologies contribute to communication, learning, independence, agency, and meaningful educational participation....