Artificial Intelligence in English Language Learning: Redefining Teaching Methods and Student Performance

Page No.: 90-106

Abstract

Artificial Intelligence is increasingly influencing the methods through which English is taught, practised, assessed, and learned. The emergence of generative AI, intelligent tutoring systems, automated writing evaluation, adaptive learning environments, conversational agents, speech-recognition applications, and AI-supported assessment has created opportunities to move beyond uniform teacher-centred instruction towards more personalized, interactive, feedback-rich, and learner-responsive approaches. This conceptual research paper examines how Artificial Intelligence is redefining teaching methods in English language learning and how such changes may influence student performance. The study adopts an integrative literature review and conceptual analysis of recent scholarship on AI-assisted language learning, generative AI, automated feedback, academic writing, learner autonomy, personalized instruction, and digital pedagogy. Particular attention is given to changes in teaching strategies, including differentiated instruction, AI-supported conversation, adaptive language practice, automated formative feedback, process-oriented writing instruction, and data-informed assessment. The paper distinguishes between performance enhancement, in which AI improves the immediate quality or speed of task completion, and learning improvement, in which learners demonstrate transferable language competence without technological dependence. Evidence from recent empirical research indicates that structured AI-supported instruction can improve academic writing performance and support English proficiency and self-regulation. However, excessive dependence may reduce cognitive engagement, originality, and independent problem-solving, and authentic human interaction. The paper proposes the PERFORM-AI Framework, which integrates personalization, engagement, responsive feedback, formative assessment, originality, reflective learning, monitored AI use, and independent transfer. It concludes that the most effective model for English language learning is not AI replacing teachers but an instructional partnership in which teachers redesign pedagogy, AI extends opportunities for individualized practice and feedback, and students remain active agents responsible for their own learning.