Examining generative AI–mediated informal digital learning of English practices with social cognitive theory: a mixed-methods study

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Abstract

This study explores the integration of generative artificial intelligence (GenAI) in informal digital learning of English (IDLE) practices, focusing on its potential to enhance language learning outcomes and addressing the technological challenges language teachers face in utilising AI-based tools to facilitate second language acquisition. Based on the research context of IDLE and holistic learning ecology and drawing on the theoretical frameworks of technological pedagogical and content knowledge and social cognitive theory, we performed a mixed-methods investigation with an empirical experiment to assess the effectiveness of GenAI followed by semi-structured interviews. The results suggest that the GenAI-mediated IDLE practices effectively improve college students’ oral proficiency in English from both technological and humanistic perspectives. However, results also indicate that the GenAI conversational partner alone is not adequate to provoke continuous extramural GenAI-mediated IDLE practices. We discuss the theoretical and pragmatic significance of GenAI-mediated IDLE in educational equity and reformation.

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Guan, L., Zhang, E. Y., & Gu, M. M. (2025). Examining generative AI–mediated informal digital learning of English practices with social cognitive theory: a mixed-methods study. ReCALL, 37(3), 315–331. https://doi.org/10.1017/S0958344024000259

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