Updated Sep 07, 2026
Students may use AI feedback while placing greater trust in teachers. Michael Henderson and colleagues examine these perceptions in a cross-sectional survey across four Australian universities.
The analysis used 6,960 responses to the question about using generative AI for feedback, alongside 8,642 usable open-ended responses. These students had already indicated using generative AI for university study in some way; the results should not be described as the prevalence among all enrolled students.
Of this group, 49.7% reported seeking AI feedback. Among 3,328 users who compared feedback sources, 90.5% rated teacher feedback somewhat or very trustworthy, compared with 60.1% for AI feedback.
Students valued AI’s accessibility, speed and ease of understanding, and some perceived asking it as less risky than approaching teachers. Concerns included reliability and contextual or disciplinary expertise. The authors argue that the sources can be complementary, but are not interchangeable.
These are self-reported perceptions, not tests of factual accuracy or learning gains. Accessible publisher methods and results support the retained findings; this review did not retrieve every table or discussion section.
As editorial suggestions, ask separately about ease of use, trust, actual accuracy and opportunities to discuss feedback with a teacher. Evaluate the educational purpose and quality directly rather than treating uptake as evidence of effectiveness.
Michael Henderson, Margaret Bearman, Jennifer Chung, Tim Fawns, Simon Buckingham Shum, Kelly E. Matthews and Jimena de Mello Heredia. “Comparing Generative AI and teacher feedback: student perceptions of usefulness and trustworthiness.” Assessment & Evaluation in Higher Education. DOI: 10.1080/02602938.2025.2502582.
Corrected 7 September 2026: the earlier summary wrongly reported 18 institutions and 1,001 students. The study covers four Australian universities and 6,960 relevant respondents. This is a limited-access review.
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