2025 ASEE Annual Conference & Exposition

This empirical research, research brief paper, explores engineering students perceptions of AI-generated performance feedback reports (PFR) crafted from peer comments in a project-based learning (PBL) class. Peer feedback is an effective tool for promoting accountability and reducing social loafing among student teams. However, students are often ill-equipped to write constructive, actionable feedback that helps their peers effectively improve their teamwork behaviors. Therefore, feedback literacy has emerged as an important skill for students to develop in order to take action on the feedback they receive, and one of the key constructs of feedback literacy is appreciating feedback.
Our recent work has demonstrated the feasibility of utilizing generative AI to create summarized, personalized feedback reports for all students in an engineering PBL class based on written comments from their teammates. We have found that generative AI significantly improves the quality of peer feedback students receive by making it more constructive and actionable. Our broader work examines the impact of AI-summarized feedback reports on the various elements of feedback literacy by analyzing student reflection data. This research brief will focus on the appreciating feedback construct, specifically as it pertains to how students appreciate the use of generative AI for the summarized feedback reports.
We piloted the AI-generated feedback reports in six PBL classes as part of a larger study, and students in 2 of the classes completed reflections about the use of AI in developing the PFRs. Using a thematic analysis approach, we first analyzed the reflection data using a priori codes and then employed inductive coding to identify themes within our original codes. We found that students generally appreciated the feedback reports and expressed appreciation for the constructive and concise nature of the feedback, noting that it provided an effective and summarized way to receive feedback from their peers. However, others felt that the reports lacked the nuance present in raw peer comments and wished they could see the original comments. These findings suggest an opportunity to use generative AI as a stepping stone for developing students’ feedback literacy. Furthermore, we believe that by understanding students' perceptions of AI in this context, we will gain valuable insights to further refine the integration of AI in the classroom and equip educators with the necessary tools to utilize AI effectively within the current educational landscape.

Keywords: Generative AI, feedback, assessment