AI-DRIVEN ADAPTIVE LEARNING SYSTEMS IN ENGLISH LANGUAGE TEACHING: ENHANCING PERSONALIZATION AND LEARNER AUTONOMY

Abstract

This study explores the role of artificial intelligence-driven adaptive learning systems in enhancing personalization and learner autonomy in English language teaching. The primary aim is to investigate how AI-based platforms such as ChatGPT and Duolingo influence learners’ language competence, motivation, and self-directed learning abilities. The research adopts a mixed-method approach combining theoretical analysis with a quasi-experimental design, in which learners engage with AI-supported instructional environments over a structured period. The findings reveal that adaptive learning systems significantly improve learners’ engagement, facilitate individualized learning pathways, and enhance language acquisition through real-time feedback and automated assessment. The results also indicate that AI tools promote learner autonomy by enabling flexible, personalized, and continuous learning beyond the classroom context. This study contributes to the growing body of research on artificial intelligence in education and provides practical implications for integrating adaptive technologies into English language teaching