Toward Inclusive Artificial Intelligence Literacy in Language Teacher Education: A Conceptual Framework for Linguistic Accessibility

Abstract

Generative artificial intelligence has rapidly become consequential for language education, yet its benefits are not distributed equally across the diverse population of language learners, which includes disabled learners and multilingual learners affected by structural inequality. The central argument is that teacher competence for generative AI in language education should be reframed from technical fluency toward the design of accessible linguistic participation. Existing frameworks for teachers and AI, including teacher digital competence models, AI-extended technological pedagogical content knowledge, and AI-literacy frameworks, are well developed but border rather than enter a critical intersection: none places linguistic accessibility at its center or treats disability and linguistic diversity as constitutive concerns. Using a structured conceptual synthesis with transparent source identification and tests of differentiation and application, this study constructs the Inclusive AI Literacy for Linguistic Accessibility framework for language teacher education. The framework positions the teacher as a reflective designer of accessible linguistic participation and articulates four interdependent dimensions: Critical-Functional AI Knowledge, Accessibility-Oriented Pedagogical Design, Inclusive Linguistic Mediation, and Ethical-Equity Stewardship. Two cross-cutting commitments distinguish the framework from existing models: the social model of disability and linguistic justice, which guard against deficit and assimilationist logics. The framework is differentiated from competing teacher-AI frameworks, illustrated through a worked teacher-education case, and translated into learning objectives. Throughout, competence is treated as a matter of design rather than technical fluency. The article engages objections of de-skilling, surveillance, and standardization, and sets out an agenda for participatory and empirical validation.