It is argued that generative AI in TESOL teacher education (TTE) must be reconceptualized to address the risk of teacher de‐skilling and GenAI dependency, and that effective GenAI integration is predicated on teacher competence and professional judgment.
Abstract
This focused article argues that generative AI (GenAI) in TESOL teacher education (TTE) must be reconceptualized to address the risk of teacher de‐skilling and GenAI dependency. Otherwise, teachers may offload professional work onto GenAI before developing evidence‐informed pedagogies and safeguards. Drawing on the five dimensions of professional GenAI competence (P‐GenAI‐C), we outline how TTE programs can organize sustainable teacher learning for the GenAI age. We then offer practical design principles and activities for pre‐service and in‐service contexts, including low‐stakes tool engagement, scenario‐based microteaching, feedback routines, and structured reflection. Across these approaches, we emphasize teacher agency, transparency, and ethical responsibility, including attention to digital exclusion, labor conditions, and environmental impacts. We argue that effective GenAI integration is predicated on teacher competence and professional judgment.
The Responsible AI Literacy in Education (RAIL-Ed) framework is introduced, developed through a systematic review and qualitative framework analysis of 67 studies (2023-2025), grounded in critical, pragmatist, sociocultural, and human-centered traditions.
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