“I trained every part of myself beneath these technological wrappings”: exploring and defining foreign language PK–12 teachers’ critical multilingual and multimodal AI competence

Teachers’ AI competence is increasingly essential for language teaching with the rise of GenAI. Existing teacher AI competence frameworks, however, do not fully capture their temporal and dynamic nature, nor how teachers engage with GenAI through multilingual, multimodal, and social-contextually situated practices. This longitudinal qualitative study examines how multilingual teachers assess, perceive and develop AI competence, and how socio-technical, multilingual contexts shape it over time. Data were collected through journey plots, multimodal artifacts and semi-structured interviews. Findings reveal teachers’ multidimensional AI competence shaped by linguistic repertoires, cultural positioning, and ethical reflection. A domain-specific linguistically and culturally responsive teacher AI competence framework, called critical multilingual and multimodal AI competence, is proposed.