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[2602.16820] AI-Mediated Feedback Improves Student Revisions: A Randomized Trial with FeedbackWriter in a Large Undergraduate Course
Summary
This study investigates the effectiveness of AI-mediated feedback on student revisions in a large undergraduate course, revealing that AI suggestions significantly enhance the quality of student essays.
Why It Matters
As educational institutions increasingly integrate AI tools, understanding their impact on learning outcomes is crucial. This research provides evidence that AI can improve the feedback process, potentially leading to better student performance and more efficient teaching practices.
Key Takeaways
- AI-mediated feedback leads to higher-quality student revisions.
- TAs found AI suggestions beneficial for identifying gaps in student work.
- The effectiveness of AI feedback increases with TA adoption of AI suggestions.
- This study contributes to the understanding of AI's role in education.
- Randomized controlled trials provide robust evidence for the findings.
Computer Science > Human-Computer Interaction arXiv:2602.16820 (cs) [Submitted on 18 Feb 2026] Title:AI-Mediated Feedback Improves Student Revisions: A Randomized Trial with FeedbackWriter in a Large Undergraduate Course Authors:Xinyi Lu, Kexin Phyllis Ju, Mitchell Dudley, Larissa Sano, Xu Wang View a PDF of the paper titled AI-Mediated Feedback Improves Student Revisions: A Randomized Trial with FeedbackWriter in a Large Undergraduate Course, by Xinyi Lu and 4 other authors View PDF HTML (experimental) Abstract:Despite growing interest in using LLMs to generate feedback on students' writing, little is known about how students respond to AI-mediated versus human-provided feedback. We address this gap through a randomized controlled trial in a large introductory economics course (N=354), where we introduce and deploy FeedbackWriter - a system that generates AI suggestions to teaching assistants (TAs) while they provide feedback on students' knowledge-intensive essays. TAs have the full capacity to adopt, edit, or dismiss the suggestions. Students were randomly assigned to receive either handwritten feedback from TAs (baseline) or AI-mediated feedback where TAs received suggestions from FeedbackWriter. Students revise their drafts based on the feedback, which is further graded. In total, 1,366 essays were graded using the system. We found that students receiving AI-mediated feedback produced significantly higher-quality revisions, with gains increasing as TAs adopted more AI...