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Exploring AI-mediated informal digital learning of English (AI-IDLE): a mixed-method investigation of Chinese EFL learners’ AI adoption and experiences
Open accessAbstract
Recent advancements in natural language processing and large language models have ushered language learning into the age of artificial intelligence (AI).Recognizing the affordances of generative AI tools, this paper aims to examine the degree to which L2 learners accepted and leveraged large language model platforms (e.g.ChatGPT, Bing Chat) for the informal digital learning of English (IDLE) purposes.Employing an explanatory sequential mixed-method design, this study draws on the technology acceptance model (TAM) and collects data via an adapted TAM questionnaire and an interview guide.A total of 867 Chinese EFL (English as a foreign language) learners answered the online survey, while 20 attended the post-survey interviews.Drawing on a validated structural model that elucidates the inter-factor relationships of perceived ease of use, perceived usefulness, intention to use, and actual use, the quantitative analysis provides statistical accounts for EFL learners' adoption of Generative Pre-trained Transformer (GPT) technologies.The qualitative findings, derived from the interview data, reveal three key themes: (1) how perceived usefulness of chatbots for IDLE emerges from hands-on experimentation with these tools; (2) how intention to use increases as learners negotiate chatbot affordances and constraints; and (3) how actual use of chatbots for IDLE involves using these tools as tutors or conversation partners.Connections between quantitative and qualitative findings enhance our understanding of how EFL learners negotiate the affordances and constraints of highly capable AI technologies to participate in creative IDLE practices.By understanding these practices, this study draws attention to the attitudes and practices that constitute AI literacies, ultimately offering implications for future classroom practices and research.
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“ChatGPT's ability to deliver immediate feedback and contextualized examples appears to have contributed to learners' vocabulary gains (Karataş et al., 2024;Liu et al., 2024).”
From Integrating ChatGPT for vocabulary learning and retention: A classroom-based study of Saudi EFL learners (2025) · cites this paper as Liu et al., 2024
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Metadata
- Authors
- Liu, G. L., Darvin, R., & Ma, C.
- Affiliations
- Chinese University of Hong Kong (HK)
- University of British Columbia (CA)
- City University of Hong Kong (HK)
- Corresponding author
- Liu, Guangxiang Leon
- Venue
- Computer Assisted Language Learning
- Publisher
- Informa UK Limited
- Published
- 2024-02-02
- Volume
- 38
- Issue
- 7
- Pages
- 1632-1660
- ISSN
- 0958-8221 (ISSN-L)
- 1744-3210
- OpenAlex
- W4391473908
- Cited by
- 299
- References
- 59
- Citations by year
- 2026: 145 · 2025: 125 · 2024: 29
- FWCI
- 470.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Computer Assisted Language Learning (publishedVersion, cc-by-nc-nd)
- CityU Scholars (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Social Sciences › Education › English Language Learning and Teaching
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- generative AI in language learning, large language models, informal digital learning, English as a foreign language, Chinese learners of English, artificial intelligence adoption, technology acceptance model, perceived usefulness, perceived ease of use, intention to use, AI literacy, ChatGPT, Bing Chat
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