Teacher-Student Trust in Higher Education Amid AI Availability: A Scoping Review

The rapid uptake of generative AI in Higher Education is reshaping not only assessment practices but also the relational foundations of learning, particularly in regard to trust between students and teachers. As institutions navigate questions of academic integrity, authorship, and the role of human judgement, trust has emerged as a critical yet under-examined dimension of AI’s impact on Higher Education. This session presents findings of a scoping review which aims to map and critically synthesises existing research on teacher-student trust in higher education within contexts of generative AI availability and use. In particular, the review examines the theoretical frameworks used to understand changing teacher-student relationships in AI-mediated educational environments, the opportunities, tensions and challenges identified within the existing literature, and the methodological approaches employed to look at this phenomenon. Insights from the scoping review inform the design, implementation, and analysis of further research at the University of St Andrews.

Scoping Review Research Questions
1. What theoretical and conceptual frameworks are being used to examine teacher-student trust in AI-mediated higher education contexts?
2. What opportunities, tensions, and challenges relating to teacher-student trust are identified within the literature on generative AI in higher education?
3. What methodological approaches have been used to study this phenomenon?

Conference attendees will gain an overview of how teacher-student trust is currently being conceptualised within emerging research on generative AI in Higher Education, including the key theoretical frameworks shaping this area of enquiry. The session will also provide insight into how AI mediates the processes of trust building between lecturers and students in Higher Education learning and teaching contexts, as well as providing an overview of the methodological approaches researchers are using to investigate these issues. More broadly, the presentation will invite participants to reflect critically on the relational and ethical implications of AI for teaching, assessment, academic integrity, and student experience within Higher Education.