Artificial Intelligence and Inclusion: Adaptive Platforms in Teaching English to Children with Special Educational Needs

Abstract

Students with special educational needs (SEN) often encounter difficulties in participating in learning activities on an equal basis with their typically developing peers. Assistive technologies based on artificial intelligence (AI) or machine learning (ML) can provide critical support in ensuring an inclusive and equitable educational environment. In this article, we identifytools and technologies, which based on АІ (artificial intellіgenсеаnd МL (mасһіnеlеаrnіng) for inclusive education, explore the main factors neсssesary for the improvement of individual used learning plans using АІ, and present an approach for real-time adaptive models in teaching English language. This study identifies inclusive educational tools and technologies that use artificial intelligence and machine learning, as well as key factors shaping the development of personalized learning based on AI. The research proposes a systemic model incorporating components of learner engagement and adaptive learning in English language classes. The system utilizes Bloom’s taxonomy to continuously monitor learners’ development. A comprehensive list of AI and ML-based inclusive education tools and technologies is compiled, and key factors for designing personalized learning plans are identified, including emotional state, learner progress, preferences, learning styles, and learning outcomes. The findings indicate that artificial intelligence–based inclusive education can enhance the educational experience of learners with special educational needs by fostering a more equitable and inclusive learning environment.

Keywords: communication, AI tools, artificial intelligence tools, inclusion, assistive technologies, personalization, machine learning, gamification.