When Feedback Must Be Human: Pedagogical Resistance to AI in EFL Speaking Classrooms - Fadillah, Ega Nur; Ahad, Uwaimir (CV. Akademi Merdeka, 2026)
The rapid advancement of artificial intelligence (AI) has intensified debates about its role in language education, particularly in providing automated feedback. While existing research has largely focused on teachers’ acceptance and use of AI tools, limited attention has been given to teachers’ deliberate decisions not to use AI in specific pedagogical contexts. This qualitative study investigates EFL teachers’ pedagogical resistance to AI-mediated oral feedback in speaking classrooms. Drawing on in-depth semi-structured interviews and reflective accounts from EFL teachers, the study employs thematic analysis to explore how teachers explain their resistance and the pedagogical values underlying their decisions. The findings reveal that resistance is grounded in teachers’ concerns about interactional immediacy, learner affect, dialogic engagement, and ethical responsibility. Oral feedback is viewed as a relational practice that requires human sensitivity to timing, tone, and emotional cues, which teachers perceive as inadequately addressed by current AI technologies. Rather than signaling technological reluctance, pedagogical resistance emerges as an enactment of teacher agency and professional judgment. The study contributes to critical discussions on AI integration in education by reframing non-use as a principled pedagogical choice and highlighting the need for context-sensitive, human-centered approaches to AI use in EFL speaking instruction.