Enhancing Oral Fluency Competence In Future English Teachers Through Artificial Intelligence Tools And A Differentiated Approach
Keywords:
Artificial Intelligence in ELT, Oral Fluency, Differentiated InstructionAbstract
Oral fluency competence represents a fundamental yet persistently elusive outcome in the training of future English as a Foreign Language (EFL) teachers. Traditional instructional methodologies, constrained by the temporal and practical limitations of the physical classroom, often prove insufficient to meet the diverse proficiency needs of pre-service educators. This article critically analyzes the integration of Artificial Intelligence (AI) tools within a structured Differentiated Instruction (DI) framework as a transformative pedagogical strategy to refine oral fluency development. It explores how AI-powered speech recognition, intelligent tutoring systems, and natural language processing chatbots can personalize pronunciation coaching, provide immediate corrective feedback, and create psychologically safe, simulated immersion environments. When combined with tiered content delivery, flexible grouping, and multimodal practice, this methodology transcends the barriers of large class sizes and learner heterogeneity. The article proposes a refined implementation model that positions AI not as a replacement for human interaction, but as an indispensable cognitive partner that amplifies the teacher’s capacity to orchestrate a truly learner-centered, fluency-driven pedagogical ecosystem.
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