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Artificial Intelligence in Language Teaching: Exploring Translanguaging, Eco-Linguistics, and Community-Based Learning

Artificial Intelligence in Language Teaching: Exploring Translanguaging, Eco-Linguistics, and Community-Based Learning
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Author(s): Chandan Kumar (Christ University, India)and Nivea Thomas K. (Christ University, India)
Copyright: 2026
Pages: 32
Source title: Community-Based Language Learning and Cultural Competence
Source Author(s)/Editor(s): Princy Pappachan (National Chiayi University, Taiwan)and Harlinda Syofyan (Esa Unggul University, Indonesia)
DOI: 10.4018/979-8-3373-0030-6.ch002

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Abstract

This chapter critically examines the role of Artificial Intelligence (AI) in second and foreign language teaching through the lens of eco-linguistics, with a particular focus on translanguaging. It explores three key dimensions of AI's impact: the theory of language, the theory of language learning, and the evolving role of the teacher. Using an argumentative and experimental methodology, the chapter integrates theoretical insights from eco-linguistics and translanguaging to evaluate AI-assisted tools. It highlights the opportunities these tools provide, such as personalized learning and adaptive feedback, while addressing their limitations, including challenges to emotional connection, language standardization, and the diminishing role of human interaction. The chapter proposes a hybrid model that combines AI with community-based language teaching to mitigate these issues, preserving the communication ecology and fostering more holistic language learning practices.

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