Shijun (Cindy) Chen and David Carless, Faculty of Education, University of Hong Kong
We are living in a complex and fast-changing world, shaped by technology, policies, and global developments. We have witnessed how artificial intelligence has rapidly permeated our lives and offered new opportunities and challenges for higher education.
As teachers, we have often wanted to try new ideas and do things differently. Yet, we often felt constrained by factors, such as students’ and institutional expectations; our own priorities and workloads; and fear of failure or negative student evaluations. We believe these kinds of feeling are shared by many university teachers, including those we interviewed for our recent study, “Teacher feedback dilemmas and the use of GenAI: Challenges or opportunities”. We interviewed 26 university teachers in mainland China and explored what their feedback dilemmas are, and how these dilemmas were tackled. We positioned the study from a ‘light’ socio-material perspective (Tai et al., 2023) and unpacked the network of varied dilemmas linked to teacher feedback practices.
Scale and time limitations emerged as the most commonly reported challenges. Large class sizes, limited contact hours, and heavy workload seem to be inevitable challenges for university teachers. As teacher Lily reported, “I teach large classes, and it’s impossible to initiate one-on-one feedback dialogues or multiple rounds of feedback for each student, even if we wanted to.” While technology and learning spaces offer new possibilities for learning, they also create challenges for teachers. For example, GenAI may lead to student over-reliance and reduced critical engagement. Another dilemma we identified is social, relational, and power dilemmas. These seem to be deeply rooted in the Chinese context, where the teacher’s authority has long been embedded in students’ minds. Teacher Neil tried to promote critical thinking by initiating dialogues with students, but this was interpreted as an exercise of authority because students just wanted some praise and acknowledgement.
Feedback dilemmas are more than challenges; for some teachers, they open up opportunities to develop innovative feedback practices. Many teachers flexibly replaced the delivery of teacher feedback with exemplars, peer feedback, or whole-class generic feedback to foster students’ self-reflection and self-regulated learning behaviors.
We specifically investigated how Riley, a lecturer with over 15 years of teaching experience, integrated GenAI in her innovative feedback practices to tackle her dilemmas. Riley employed GenAI feedback within an internal feedback process (Nicol, 2021), congruent with hybrid human-AI feedback principles (Banihashem et al., 2025). GenAI was deployed not as a feedback source but as exemplar generator based on tailored prompts from teacher Riley. The design sequence involved student drafts, exposure to GenAI exemplars, then student reflections and revisions to their drafts.
This use of GenAI not only reduced Riley’s feedback dilemmas of scale and technology but also shifted the roles of teacher, students, and GenAI. Teacher Riley took on the role of a learning collaborator. Students became more proactive in self-reflection, critical evaluation, and feedback seeking. GenAI was no longer a copy-and-paste machine for easy answers but instead an actant that triggered process-oriented learning, enabling students to internalize feedback and revise their work.
We reconceptualize teacher feedback dilemma not only as challenges but as opportunities for pedagogical adjustments, in that these dilemmas simulate reflection and offer potential for teacher professional growth. Tackling feedback dilemmas can be regarded as an element of teacher feedback literacy (Carless & Winstone, 2023). When GenAI meets teacher feedback dilemmas, what new challenges or opportunities can it bring? We call for further research into the potential of GenAI to reduce teacher feedback dilemmas across different disciplinary domains.
References
Banihashem, S. K., Noroozi, O., Khosravi, H., Schunn, C. D., & Drachsler, H. (2025). Pedagogical framework for hybrid intelligent feedback. Innovations in Education and Teaching International, 63(2), 554–570. https://doi.org/10.1080/14703297.2025.2499174
Carless, D., & Winstone, N. (2023). Teacher feedback literacy and its interplay with student feedback literacy. Teaching in Higher Education, 28(1), 150–163. https://doi.org/10.1080/13562517.2020. 178237
Chen, S. (Cindy), & Carless, D. (2026). Teacher feedback dilemmas and the use of GenAI: Challenges or opportunities? Innovations in Education and Teaching International, 1–14. https://doi.org/10.1080/14703297.2026.2648040
Nicol, D. (2021). The power of internal feedback: Exploiting natural comparison processes. Assessment and Evaluation in Higher Education, 46(5), 756–778. https://doi.org/10.1080/02602938.2020.1823314
Tai, J., Bearman, M., Gravett, K., & Molloy, E. (2023). Exploring the notion of teacher feedback literacies through the theory of practice architectures. Assessment and Evaluation in Higher Education, 48(2), 201–213. https://doi.org/10.1080/02602938.2021.1948967
