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How Can AI-Powered Chatbots Drive EFL Learners' Learning Performance?: Mediation by Social Perceptions and Moderation by Usage Frequency

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  • Yung-Ming Cheng

    (Chaoyang University of Technology, Taiwan)

Abstract

This study proposes research based on the stimulus-organism-response model to examine determinants affecting English as a foreign language (EFL) learners' continuance intention of artificial intelligence (AI)-powered chatbots and learning outcomes, and to test whether usage frequency can moderate path relationships within the research model. Sample data for this study were collected from learners who had experience with using AI-powered chatbots to learn English in Taiwan, and 395 usable questionnaires were analyzed using structural equation modeling. The results demonstrate that EFL learners' perceived anthropomorphism and perceived intelligence of AI-powered chatbots positively influenced the perceived warmth and perceived competence elicited by the chatbots, which together encouraged their continuance intention of using AI-powered chatbots, and in turn improved their learning outcomes. Further, this study showed that EFL learners' usage frequency of using AI-powered chatbots partially and significantly moderated path relationships in the research model.

Suggested Citation

  • Yung-Ming Cheng, 2026. "How Can AI-Powered Chatbots Drive EFL Learners' Learning Performance?: Mediation by Social Perceptions and Moderation by Usage Frequency," International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), IGI Global Scientific Publishing, vol. 16(1), pages 1-27, January.
    • Handle: RePEc:igg:jcallt:v:16:y:2026:i:1:p:1-27
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