AI-Driven Translanguaging: Enhancing Plurilingual Proficiency in EFL Classrooms
DOI:
https://doi.org/10.69760/gsrh.0250205035Keywords:
AI-driven translanguaging, plurilingual proficiency, Generative AI in EFL, multilingual pedagogyAbstract
This article examines the emerging convergence between translanguaging pedagogy and Generative Artificial Intelligence (GenAI) in English as a Foreign Language (EFL) education. Drawing on sociocultural theory, the paper argues that Large Language Models (LLMs) function as powerful mediating tools that support multilingual learners through adaptive input, situational intelligence, and mixed-language interaction. These capabilities enable students to mobilize their full linguistic repertoires, fostering deeper comprehension, metalinguistic awareness, and the development of plurilingual proficiency. The study highlights how AI-driven translanguaging can enhance equity, motivation, and cognitive engagement while offering new pathways for personalized scaffolding and reflective learning. At the same time, it critically addresses systemic challenges, including algorithmic bias, the under-representation of low-resource languages, and tensions between standardized AI output and the creative, fluid nature of translanguaging. The paper concludes with recommendations for responsible integration, professional development, and future research aimed at capturing dynamic, plurilingual growth in AI-mediated classrooms.
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