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Rahmat Sapaat Siregar
Universitas Isalam Negeri Alauddin Makassar

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Learning to Teach Alongside Machines: A Narrative Inquiry of In-Service English Teachers Transitioning to AI-Enhanced Classrooms Try Mahendra Siregar; Rahmat Sapaat Siregar
Journal of Innovation in English Education and Language Teaching Vol. 1 No. 2 (2025): APRIL 2025
Publisher : Barkah Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63228/gevp8269

Abstract

This narrative inquiry examines how eight in-service English teachers in secondary schools experienced and made meaning of their transition to AI-enhanced classrooms over an 18-month period. As generative AI tools rapidly penetrate language education, teachers confront not merely technical adjustments but fundamental disruptions to professional identity, pedagogical authority, and the relational core of teaching. Drawing on Clandinin and Connelly's (2000, 2020) three-dimensional narrative framework, we collected life story, transition story, and current practice interviews from four experienced (12+ years) and four novice (2–5 years) teachers. Narrative analysis revealed four emplotted identity positions: the reluctant adapter (negotiating imposed integration), the AI evangelist (embracing transformative potential), the pragmatic negotiator (selective, context-driven use), and the anxious skeptic (moral and pedagogical opposition). Cross-cutting themes included loss of craft knowledge, emergence of new forms of professional expertise (curation, verification, ethical reasoning), and persistent ethical unease regarding surveillance, data privacy, and learner autonomy. Temporal analysis identified characteristic transition challenges: initial shock and threat appraisal (months 1–4), experimental adaptation (months 5–10), and differential stabilization (months 11–18). Findings suggest that transitions to AI classrooms are neither linear nor technologically determined but are mediated by prior professional identities, institutional cultures, and opportunities for narrative reconstruction of practice. We argue for professional development that acknowledges grief, supports situated experimentation, and attends to the ethical affordances of AI as pedagogical partners rather than replacements.