EFL Teachers’ Identity Tensions and Transformation in AI-Driven Teaching in China: A Dialogical Approach

Abstract

The spread of artificial intelligence (AI) in tertiary education has remarkably influenced language teachers’ professional identity construction. However, little is known about the identity tensions EFL teachers experience during this shift. This study is built on a dialogical approach to identity and discusses the role of inner tensions in making sense of one’s AI-driven identity tensions. We used a qualitative case study design to collect data from narrative frames and interviews with ten EFL teachers. Thematic data analysis revealed that EFL teachers experienced three identity tensions. They include conflicting I-positions due to challenged beliefs and traditional values, new I-positions in teacher-student power relationships and pedagogical practices as well as constrained I-positions arising from students’ inadequate AI-digital literacy, technical limitations of AI-driven tools and contextual factors. While managing tensions in the teacher-AI-student triadic dynamic, participants’ Intelligent-TPACK, evolving conceptions of AI-driven teaching and adjustment in pedagogical decision-making and action-taking were highlighted to strengthen their AI-driven identity and professional development. Implications are provided for teacher educators, university administrators and policy makers to help EFL teachers better construct AI-driven identity.