Improving EFL students intonation acquisition through AI-powered shadowing

Successful and effective communication in the context of a foreign language relies not only on grammar and vocabulary but also on effective prosody, particularly intonation. This study investigates the effectiveness of integrating Artificial Intelligence (AI) with the shadowing technique to improve intonation performance among English as a Foreign Language (EFL) college students. In fact, intonation is regarded as a problematic feature of pronunciation among English as a Foreign Language (EFL) students, as it determines how an utterance is produced in relation to accent, stress, and rising/falling pitch. Many EFL students face difficulties in learning and differentiating rising/falling intonation patterns. They don’t know what intonation to use because English sentences can be statements, questions, commands, etc. A quantitative, one- group pre-test/post-test design was employed in conducting this study. Twenty second-year college students participated in a four-week intervention session using AI-supported shadowing exercises. Pre- and post-tests were administered to examine changes in their performance. The findings demonstrated a statistically significant improvement in the intonation performance of the participants (t = 9.659, df=19, p < .05) suggesting that integrating AI-assisted tools with shadowing practice enhances prosodic competence and provides an effective pedagogical model for pronunciation instruction.