ENHANCING SPEAKING PROFICIENCY OF ESL STUDENTS IN HIGHER EDUCATION THROUGH AI-BASED FEEDBACK SYSTEMS

Abstract

The integration of Artificial Intelligence (AI) into higher education has significantly transformed English language teaching, particularly in the development of speaking skills among ESL learners. Oral academic communication remains one of the most challenging competencies due to limited individualized feedback, speaking anxiety, and insufficient opportunities for authentic interaction. AI-driven feedback systems provide innovative solutions by utilizing automated speech recognition, natural language processing, and adaptive learning analytics to deliver real-time, personalized evaluation of speaking performance. This paper examines the pedagogical potential of AI-mediated feedback systems in enhancing oral communication among ESL students in higher education. It discusses their impact on pronunciation development, learner autonomy, engagement, and assessment practices, while also addressing challenges related to technological accessibility and ethical considerations. The study concludes that AI-based feedback tools offer transformative opportunities for improving speaking instruction, though they should complement rather than replace human pedagogical interaction