Differences in perceptions of generative AI feedback by non-native English speakers

This article explores how non-native English-speaking (NNES) students and higher education educators perceive AI-generated feedback through dialogic feedback framework and ethical lens. Using a quantitative ethnography approach, Study 1 employed focus group interviews with 17 NNES students and nine educators, identified three themes: (1) instrumental efficiency vs. holistic understanding, (2) emotional comfort and social dynamics , and (3) ethical issues for trustable feedback. Study 2 employed epistemic network analysis (ENA) to identify that educators’ epistemic frames integrated broader ethical considerations, while students’ frames emphasized emotional and relational aspects to human educators. Findings indicate that while AI-generated feedback offers emotional neutrality and immediacy, it lacks contextual depth, relational continuity, and interpretive richness in human feedback. This suggests that AI-generated feedback should be designed to work alongside, not replace human educators’ feedback, offering implications for responsible and dialogically informed feedback practices in higher education.

Otaki, B., Naganuma, S., Jin, T., & Oshima, J. (2025). Differences in perceptions of generative AI feedback by non-native English-speaking students and educators in higher education. Educational Psychology, 1–38. https://doi.org/10.1080/01443410.2025.2564893