The Impact of AI-Based Sign Language Translation on Reading Instruction for Students with Hearing Impairment: A Theoretical Analytical Study

Abstract

Artificial intelligence applications are undergoing rapid development in the field of special education, and AI-based sign language translation has emerged as one of the most promising technologies that can contribute to improving reading instruction for students with hearing impairments by enhancing access to educational content and facilitating the comprehension of written texts. This study aimed to analyse the role of intelligent sign language translation in the development of reading skills, review its educational applications, and highlight the potential for its integration with other AI technologies, such as adaptive learning, computer vision and large language models. The study adopted a qualitative approach through a theoretical-analytical study, based on an analysis of recent scientific literature using document analysis and qualitative content analysis. The results showed that AI-based sign language translation contributes to enhancing reading comprehension, developing vocabulary and improving interaction with texts; furthermore, its integration with other smart technologies supports the creation of more inclusive learning environments that are adapted to the needs of students with hearing impairments. The study also highlighted a number of challenges, most notably the diversity of sign languages, the lack of Arabic databases, and the need for more accurate models that take into account the linguistic and cultural characteristics of the deaf community. The study concludes that intelligent sign language translation represents a promising trend in the development of literacy education, and recommends the development of specialised educational applications and the conduct of pilot studies to verify the effectiveness of these technologies in various educational settings.