AI versus teachers and peers: a comparative study on speaking performance, willingness to communicate, self-perceived communicative competence and foreign language anxiety
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Chenghao Wang
Bio:
Chenghao Wang is a PhD student at the Department of Applied Linguistics, Xi’an Jiaotong-Liverpool University and University of Liverpool. His research interests include computer-assisted language learning (CALL), AI-CALL, AIGC, and VR-enhanced language learning. His work recently appears on
System, InJAL, IJHCI and Computers & Education. 
and
Bin Zou
Boi:
Bin Zou received his PhD degree in TESOL and Computer Technology from the University of Bristol, UK. He is a Senior Associate Professor and PhD supervisor at the Department of Applied Linguistics, Xi’an Jiaotong-Liverpool University. His research interests include Computer-Assisted Language Learning (CALL), AI, EAP, and ELT. He is the Founding Editor and Co-Editor-in-Chief of two international journals:
the International Journal of Computer- Assisted Language Learning and Teaching (IJCALLT) andthe International Journal of EAP: Research and Practice.
Abstract
While online language education is widely accepted for its convenience, it often leads to a relatively isolated learning experience. In response to positive psychology’s emphasis on learner engagement and well-being, this study investigated how an instructional AI chatbot and an AI-based speaking assessment system, introduced midway through the course, could enhance instruction and support speaking practice. Utilizing three-round speaking tests and questionnaires, supplemented by semi-structured interviews, this study examined how AI-supported language learning influenced learners’ speaking performance, along with key affective variables closely related to the speaking experience: Willingness to Communicate (WTC), Self-Perceived Communicative Competence (SCC), and Foreign Language Anxiety (FLA). A total of 103 Chinese EFL learners participated in the experiment. The quantitative results indicated that AI, compared to human teachers and peers, was more effective in enhancing learners’ speaking performance, WTC, and SCC. The qualitative data suggest that this may be attributed to learners feeling more comfortable and secure when producing English in AI-mediated online environments, which reduced social pressure and fostered greater self-expression. In addition to identifying the limitations of AI-supported speaking instruction, the study offers practical guidance for teachers seeking to incorporate diverse AI tools into online classroom activities to foster both linguistic development and positive emotional experiences.
Funding source: Reform of Foreign Language Teaching under the Background of High-Quality Development in Universities of Jiangsu Province
Award Identifier / Grant number: Key project (2024WYJG018)
Funding source: University Research Centre for Culture, Communication and Society (CCCS) at Xi’an Jiaotong-Liverpool University
About the authors
Bio:
Chenghao Wang is a PhD student at the Department of Applied Linguistics, Xi’an Jiaotong-Liverpool University and University of Liverpool. His research interests include computer-assisted language learning (CALL), AI-CALL, AIGC, and VR-enhanced language learning. His work recently appears on System, InJAL, IJHCI and Computers & Education.
Boi:
Bin Zou received his PhD degree in TESOL and Computer Technology from the University of Bristol, UK. He is a Senior Associate Professor and PhD supervisor at the Department of Applied Linguistics, Xi’an Jiaotong-Liverpool University. His research interests include Computer-Assisted Language Learning (CALL), AI, EAP, and ELT. He is the Founding Editor and Co-Editor-in-Chief of two international journals: the International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT) and the International Journal of EAP: Research and Practice.
Acknowledgments
We would like to extend our sincere thanks to Mr Zixun Wang and Ms Wenying Xu for the assistance with participants recruitment.
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Research ethics: This study has received approval from the Research Ethics Committee of the first and second authors’ university.
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Informed consent: Each participant completed an informed consent form prior to taking part in the experiment.
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Author contributions: Chenghao Wang: writing – review & editing, writing – original draft, resources, methodology, investigation, formal analysis, data curation. Bin Zou: writing – review & editing, resources, methodology, investigation, funding acquisition, conceptualization.
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Use of Large Language Models, AI and Machine Learning Tools: This paper used ChatGPT-4o to check the grammar of certain sentences; however, the author remains responsible for the content of the entire text.
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Conflict of interest: The authors declare no conflict of interest with the research, authorship, and/or publication of this article.
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Research funding: This study was funded by the Reform of Foreign Language Teaching under the Background of High-Quality Development in Universities of Jiangsu Province (Key project): (2024WYJG018) and the University Research Centre for Culture, Communication and Society (CCCS) at Xi’an Jiaotong-Liverpool University.
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Data availability: Due to ethical considerations, the experimental data are available upon reasonable request from the corresponding author.
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