Artificial Intelligence in English Language Teaching: Pedagogical Innovations, Critical Scaffolding, and Sociolinguistic Challenge

Abstract

The integration of Artificial Intelligence (AI) into English Language Teaching (ELT) represents a foundational paradigm shift from traditional, standardized instructional models toward adaptive, learner-centric, and data-informed pedagogy. This paper examines the transformative role of AI across the core language competencies: Listening, Speaking, Reading, and Writing (LSRW). By leveraging Natural Language Processing (NLP), intelligent tutoring systems, and generative AI models, contemporary language education offers low-anxiety speaking environments, dynamically leveled reading materials, and formative automated feedback that scaffolds the writing process. Furthermore, AI functions as a high-utility instructional prosthesis for educators, streamlining differentiated curriculum design, targeted remedial interventions, and continuous formative assessment. Alongside these pedagogical advantages, the paper critically addresses essential challenges, including digital divide disparities, sociolinguistic biases inherent in standard-dialect training data, academic integrity concerns, and the preservation of humanistic teacher agency. Ultimately, the study advocates for a balanced, hybrid pedagogical framework where AI serves not to supplant the language educator, but to augment instructional efficacy and foster inclusive, autonomous language acquisition.