Trust, resistance, and transformation: A Q-methodological study of teachers' perspectives on AI-generated feedback in second language writing

Abstract

The integration of artificial intelligence (AI) into second language (L2) writing instruction has generated an ongoing debate concerning its pedagogical value, ethical implications, and classroom implementation. While existing research highlights AI's potential to enhance writing development, teachers' subjective views remain underexplored. This study uses Q-methodology to examine educators' perspectives on the pedagogical role of AI, particularly AI-generated feedback, in L2 writing instruction. Forty teachers sorted 42 statements that captured pedagogical, emotional, and ethical concerns related to AI-supported writing practices. By-person factor analysis revealed four distinct viewpoints: (1) Instructor-Led Guided Trust, (2) Institution-Dependent Conditional Trust, (3) Strategic Resistance, and (4) Transformative Embrace. These perspectives reflect varying degrees of trust in AI, informed by beliefs about instructional quality and teacher roles. The findings emphasize the need for teacher agency, contextual responsiveness, and targeted professional development in AI adoption. This study contributes to a deeper understanding of how educators reconcile emerging technologies with pedagogical integrity, offering practical implications for policy, training, and future research in technology-enhanced education.