Speaker
Description
Generative artificial intelligence (GenAI) raises questions about language teachers’ expertise, authority, and distinctive contribution to learning. This study explores how AI-related critical emotional incidents become sites of professional identity negotiation among six novice English language teachers in Vietnam. Guided by an interpretivist approach, the study drew on incident-focused interviews, follow-up exchanges, and participant-provided artefacts. Analysis combined thematic interpretation with a narrative orientation and IPA-informed attention to individual meaning-making before examining shared and divergent patterns across participants. Three themes captured vulnerable professional credibility, retaining responsibility while reworking AI use, and changed practices alongside continuing identity tensions. Participants described verifying generated materials, redesigning assessment, reducing dependence on live technology, and clarifying their contribution to AI-assisted feedback. These adjustments coexisted with concerns about workload, fairness, institutional expectations, and authenticity. Contrasting accounts of routine AI use showed that positive emotion and practical usefulness did not necessarily prompt identity change. Emotionally salient encounters could also affirm existing professional commitments without resolving uncertainty. The findings locate identity negotiation in how teachers interpret competence, responsibility, recognition, and care within particular relationships and working conditions. For TESOL, the study suggests that AI-related professional development creates space for reflection on emotional experiences and professional commitments alongside the development of technological competence.