Speaker
Description
As AI speech technologies become increasingly integrated into English language education, their implications for professional identity construction remain underexplored. This qualitative multiple-case study examines how six pre-service English language teachers in Vietnam position themselves in response to AI-generated speech feedback and negotiate their emerging professional identities. Data were generated through individual speaking tasks using ELSA Speech Analyzer, followed by semi-structured interviews conducted in Vietnamese. Preliminary analysis suggests three interrelated patterns. Participants selectively accepted, questioned, or resisted automated evaluations, negotiating the boundaries between algorithmic authority and professional judgment. For some, speech-related feedback prompted emotional tensions concerning professional competence and legitimacy, particularly when automated evaluations were associated with their perceived readiness to teach. Across cases, participants articulated professional identities grounded in pedagogical autonomy, linguistic diversity, instructional clarity, empathy, and technology-supported teaching, extending beyond algorithmically defined standards of spoken performance. These patterns suggest that AI speech feedback can become a site of professional identity negotiation, where prospective teachers affirm or reconsider their professional values without necessarily undergoing identity transformation. The study contributes an identity-oriented perspective to AI-mediated language teacher education, highlighting the importance of critical engagement with automated feedback while preserving teachers' pedagogical agency.