Transforming English Language Learning For Students With Disabilities Through AI-Driven Inclusive Strategies

Abstract

Inclusive education necessitates the provision of seamless ELL for students when it comes to diverse students with disabilities; however, there is often a disconnect in traditional teaching practices. This paper explores how AI can revolutionize ELL for students with disabilities, allowing for a personalized, adaptive, accessible learning experience. Technologies for artificial intelligence (AI), including speech recognition, natural language processing, and intelligent tutoring systems, can be used to automatically personalize content and feedback for learners across a wide range of cognitive, sensory, and physical challenges. It surveys the current AI-based applications and assesses their efficacy in addressing the challenges (e.g., reduced mobility, speech disorders, or processing cognitive limitations) that act as brakes to acquiring language. Using a system literature review and a data-driven analysis of learner performance and data from AI-enabled ELL platforms, this paper identifies the key AI strategies that enhance learner engagement, learner autonomy and communication abilities. Ethical and human-AI working issues are reported to overcame to create empathetic, cross-culturally appropriate educational settings. The use of AI in inclusive ELL ensures equal opportunity in access and language learning progression and confidence. A framework is offered for AI in TESOL in broader classroom contexts, focusing on the cooperative roles of teachers, technology builders and legislators toward scalable, and stable, language learning ecosystems. This paper underscores the transformative nature of AI to address educational disparities and supports for continued and increased interdisciplinary research and investment to realize English language education that is truly inclusive for all learners.