10 September 2025

In this post, CRADLE PhD candidate Kaiyu Huang reflects on CRADLE’s recent webinar “Student perspectives on AI in higher education”, the first in CRADLE’s New Directions in AI Research and Practice series.

Kaiyu is a cotutelle PhD candidate at CRADLE and the Centre for Global Learning (GLEA) of Coventry University.

Webinar #1: Student Perspectives on AI in Higher Education

The webinar began with Dr Jack Walton introducing the findings of a large-scale student survey (see Henderson et al., 2025 and the AIinHE.org project). It was followed by an interactive Q&A session where Professor Kelly Matthews, Professor Michael Henderson, Associate Professor Tim Fawns, and Associate Professor Nicole Pepperell shared valuable insights into student perspectives on GenAI. They challenged the existing assumptions about students’ GenAI use (e.g., cheating, copy-and-paste), shifting attention toward how students are interacting and grappling with AI.

How students percieve GenAI

Building on the webinar discussions, it is evident that GenAI has increasingly become an indispensable part of the higher education experience. Findings from the student survey indicated that half of the student participants reported GenAI use for feedback, and GenAI feedback complements teacher feedback.

However, students perceive GenAI as a “double-edged sword”, as they express concerns about overreliance, reduced efforts, and the ethical issues.

Such mixed perceptions are compounded by the conflicts between institutional policies and actual practices, leading to student confusion about the appropriateness of GenAI use. As the speakers noted, the threat of GenAI detectors, along with social, economic and environmental objections and ethical concerns, may discourage students from using it. Both students and staff experience uncertainty and anxiety about their expertise and preparedness for GenAI.

In response to the challenges, speakers emphasised the value of student perspectives in shaping research directions and called for more conversations among educators, students, and industry partners through co-design. They highlighted both relational aspects of GenAI interaction, and the importance of cross-disciplinary insights to understand the diversity of student experiences with GenAI.

How does this influence my research?

The webinar inspires me to reflect on my research on peer feedback and underperformance in an educational landscape where GenAI is ubiquitous. The project’s research provides evidence of increasing GenAI use among students, likely including those who underperform. However, we still know very little about these students’ unique GenAI experiences: whether it empowers or inhibits them, and how they interact with GenAI in the context of peer feedback (e.g., evaluating peers’ work, interpreting peers’ comments, or generating revision plans).

The voices of students who underperform are especially critical to understand the role GenAI plays in feedback processes, and to shape the educational design for productive feedback experiences. In addition, the relational aspects, such as peer interactions and emotions, can shape student interactions with GenAI for peer feedback purposes, which deserves further attention in my research.

About Kaiyu Huang

Kaiyu Huang is a cotutelle PhD candidate at CRADLE and the Centre for Global Learning (GLEA) of Coventry University. Her research interests include peer assessment and digital learning in higher education. Kaiyu’s doctoral project explores how peer feedback in collaborative assignments influences students who underperform.

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References

Henderson, M., Bearman, M., Chung, J., Fawns, T., Buckingham Shum, S., Matthews, K. E., & de Mello Heredia, J. (2025). Comparing Generative AI and teacher feedback: student perceptions of usefulness and trustworthiness. Assessment & Evaluation in Higher Education. Advance Online Publication. https://doi.org/10.1080/02602938.2025.2502582

CRADLE has been busy researching GenAI – find our latest publications on our blog.

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Wednesday 17 September at 2.30pm

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