Translanguaging and AI synergy in multilingual EFL classrooms
Year: 2025
Type: article
Abstract: This study explored the synergy between translanguaging and artificial intelligence (AI) in multilingual English as a Foreign Language (EFL) classrooms in China, addressing the limited research on their combined pedagogical value. Using a qualitative phenomenographic design, 40 first-year undergraduates from diverse linguistic backgrounds, including Mandarin, Cantonese, Uyghur, and Korean, engaged with AI platforms such as ChatGPT, Baidu ERNIE Bot, and Youdao Translate across ten weeks of classroom activities. Data from observations, reflective journals, AI interaction logs, and semi-structured interviews were analysed thematically, revealing six key themes: bilingual and multilingual scaffolding through AI, confidence and affective support, negotiation of meaning and identity, customisation and personalisation of learning, classroom participation and collaboration, and critical awareness of AI’s limitations. Findings showed that AI-mediated translanguaging reduced cognitive load, enhanced comprehension, boosted confidence, and affirmed minority linguistic identities, while offering learners autonomy and opportunities for collaboration. At the same time, participants expressed concerns about mistranslations, over-reliance, and reduced opportunities for authentic English practice, highlighting the need for critical AI literacy. The study extends translanguaging scholarship by demonstrating how AI operationalises multilingual scaffolding in tangible ways and contributes to AI-in-education research by situating technology use within inclusive, multilingual pedagogies. It concludes that AI-mediated translanguaging has the potential to create more participatory and equitable EFL classrooms in China, provided it is implemented with careful attention to balance, sustainability, and reflective practice.
Author: Shen Yanzhou
Institution: Northeast Normal University
Language: English
Subfield: Linguistics and Language
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4414580145
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