ENHANCING EFL SPEAKING SKILLS THROUGH AI: ADDRESSING LEARNER AUTONOMY AND SPEAKING ANXIETY

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Authors: ASSANOVA ASSEL KARLYBAEVNA, KONYSKARA ZHUBANYSH ORAZBEKKYZY
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Abstract

This article examines foreign language speaking anxiety as a major affective barrier in school EFL classrooms, with particular attention to its impact on learners’ oral performance, motivation, and willingness to communicate. Speaking anxiety is conceptualised as a relatively stable psychological factor intensified by evaluative classroom practices and peer pressure typical of school settings. Drawing on recent empirical studies, the article explores the pedagogical potential of artificial intelligence–based speaking tools, such as chatbots and speech-enabled platforms, in reducing speaking anxiety and supporting oral development. In addition, the paper presents exploratory empirical insights based on a learner questionnaire administered to school students in Kazakhstan, highlighting the prevalence of speaking anxiety and learners’ attitudes toward AI-supported speaking practice. The findings suggest that AI-based speaking tools provide emotionally safe, non-judgmental, and personalised environments that not only alleviate speaking anxiety but also foster learner autonomy and self-directed learning. The article argues that AI-supported speaking practice represents a pedagogically valuable complement to classroom instruction in school EFL education.

Fields of Study & Subjects

EFL/ESL Teaching and Learning Communication in Education and Healthcare English Language Learning and Teaching

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
31 January 2026