Teachers between authority and automation: professional agency and pedagogical decision-making in AI-mediated language education - Shahzadi Hina Sain (CV Narasi Khatulistiwa Indonesia, 2026)
Background: AI-mediated language education has intensified debates about whether teachers remain authoritative pedagogical agents or become procedural supervisors of automated instructional systems. Objective: This study examines how teacher authority, professional agency, and pedagogical decision-making are represented in public documents on artificial intelligence in education and language learning. Method: Using qualitative corpus-assisted document analysis, this study analysed 18 public documents published between 2022 and 2026 through pedagogical decision episodes related to planning, feedback, assessment, language support, ethical governance, and curriculum implementation. Results: Findings indicate that teacher authority is not directly displaced by AI but redistributed through ethical oversight, human judgement, and AI literacy. Professional agency emerges as an institutional and ethical condition, shaped by policy frameworks, accountability expectations, professional learning, and teachers’ capacity to evaluate or reject AI-generated output. Implication: Language-pedagogical alignment remains uneven, with stronger attention to writing support, feedback, translation, and implementation than to pragmatic appropriateness, cultural meaning, learner identity, and inclusive multilingual practice. Novelty: This study contributes a decision-centred framework for understanding AI-mediated language education as a professional negotiation space where automation must be governed through context-sensitive teacher judgement.