Using Copilot to Foster Utterance Fluency of Undergraduates: A Multiple Case Study
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Keywords

speaking fluency, AI-driven learning, Copilot voice mode, fluency development, EFL learners

How to Cite

Using Copilot to Foster Utterance Fluency of Undergraduates: A Multiple Case Study. (2025). Computer-Assisted Language Learning Electronic Journal, 26(4), 396-417. https://doi.org/10.54855/

Abstract

Utterance fluency in a second language (L2) is essential for communicative competence, yet many learners face psychological barriers such as speaking anxiety and fear of social judgment. In EFL contexts like Vietnam, where English learning is primarily classroom-based, opportunities for authentic oral interaction are limited. This study explores the potential of Copilot voice mode, an AI-driven conversational tool, to support speaking fluency development and reduce psychological barriers. Using a multiple case study design, three Vietnamese university students, at Beginner, Pre-Intermediate, and Intermediate proficiency levels, participated in an eight-week intervention. Data sources included pre- and post-tests analyzed using ELSA Speech Analyzer, participant audio recordings, and self-reflections coded thematically. Results suggest that Copilot may facilitate improvements in utterance fluency and learner confidence, particularly for lower-proficiency learners. While limitations in AI accuracy and voice recognition were noted, the tool offered accessible, low-pressure speaking opportunities. This study highlights the value of integrating AI tools like Copilot into language education and offers practical insights for supporting speaking development in resource-constrained EFL contexts.

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References

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