Generative AI and English language teaching: A global Englishes perspective

Abstract

Abstract Generative AI (GenAI) offers potential for English language teaching (ELT), but it has pedagogical limitations in multilingual contexts, often generating standard English forms rather than reflecting the pluralistic usage that represents diverse sociolinguistic realities. In response to mixed results in existing research, this study examines how ChatGPT, a text-based generative AI tool powered by a large language model (LLM), is used in ELT from a Global Englishes (GE) perspective. Using the Design and Development Research approach, we tested three ChatGPT models: Basic (single-step prompts); Refined 1 (multi-step prompting); and Refined 2 (GE-oriented corpora with advanced prompt engineering). Thematic analysis showed that Refined Model 1 provided limited improvements over Basic Model, while Refined Model 2 demonstrated significant gains, offering additional affordances in GE-informed evaluation and ELF communication, despite some limitations (e.g., defaulting to NES norms and lacking tailored GE feedback). The findings highlight the importance of using authentic data to enhance the contextual relevance of GenAI outputs for GE language teaching (GELT). Pedagogical implications include GenAI–teacher collaboration, teacher professional development, and educators’ agentive role in orchestrating diverse resources alongside GenAI.

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