THE ROLE OF AI-POWERED FEEDBACK IN DEVELOPING EFL LEARNERS' SPEAKING ACCURACY

Abstract

Artificial intelligence (AI) has rapidly expanded the possibilities for providing immediate, individualized, and repeatable feedback to learners of English as a foreign language (EFL). This paper examines how AI-powered feedback can contribute to speaking accuracy, understood as the appropriate and intelligible use of pronunciation, grammar, vocabulary, and form during oral production. Drawing on research on corrective feedback, automatic speech recognition (ASR), AI speech-evaluation systems, and generative AI, the paper argues that AI can strengthen the feedback cycle by increasing opportunities for noticing errors, comparing learner output with target forms, self-repairing, and repeating practice. Recent studies report improvements in pronunciation, fluency, grammar, vocabulary, and learner confidence when AI-supported speaking tools are used in structured tasks (1,2,3). However, automated feedback remains vulnerable to recognition errors, accent bias, limited pragmatic sensitivity, and over-reliance. Therefore, the most pedagogically sound model is not full automation but a complementary AI-plus-teacher approach in which technology provides rapid formative feedback while teachers validate difficult cases, support interactional competence, and connect practice to meaningful communication. The paper concludes with practical principles for integrating AI-powered feedback into EFL speaking instruction.