Updated Sep 10, 2026
Updated, 7 September 2026: We have removed claims about demonstrated effects on trust or teaching quality that go beyond the reported perceptions.
Bodong Yang’s study, published online in Studies in Higher Education on 26 March 2026, examines how students perceive teachers’ use of Generative AI. In the quantitative phase, 422 participants were randomly assigned to assess teachers described as fully using AI, collaborating with it or not using it. A qualitative phase involved 12 participants.
Both AI-use conditions received lower perceived-care assessments than non-use. The qualitative accounts were more nuanced: participants could appreciate critical collaboration with AI while criticising excessive reliance; some also regarded non-use as inflexible.
The study reports perceptions under the study’s conditions. It does not establish how actual teacher AI use affects learning, retention or long-term trust.
Our suggested starting point is to describe the actual use of AI before asking students to evaluate it. Drafting a teaching resource, preparing feedback and answering a student’s question are different activities. Make clear which one the question concerns and what the teacher checked.
Invite students to explain what felt helpful or concerning. Keep those accounts alongside the specific task and the guidance they received, so the team can decide what needs clarification. These are proposed local review steps, not a method tested by this study.
When reporting results, distinguish perceived care from evidence about learning. Neither a favourable nor an unfavourable comment settles the effectiveness of a teaching method. The student comment analysis governance checklist can help plan how local feedback will be interpreted and used.
Yang, B. (2026). ‘If GAI has finished her job, why would I need her?’: a mixed-methods study on students’ perceptions of GAI-using teachers. Studies in Higher Education. Publisher record. DOI: 10.1080/03075079.2026.2648696.
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