Problem
Research questions and friction points this paper is trying to address.
AI feedback
student evaluation
writing reflection
generative AI
over-reliance
Student Evaluation of Repeated AI Feedback Across a Semester of Writing
🤖 AI Summary
This study addresses the paucity of empirical research on the longitudinal, repeated use of generative AI for writing feedback in higher education, particularly regarding students’ perceived effectiveness and learning impacts. Drawing on 2,988 reflective essays from 283 Estonian undergraduates over one semester, the research integrates student-selected AI-generated feedback—elicited via a standardized prompt—and students’ evaluations thereof. Employing a mixed-methods approach combining manual content analysis and a validated AI text classifier, this work provides the first large-scale, longitudinal classroom evidence of evolving student attitudes toward AI feedback: while most students initially found it helpful and actionable, approximately 10% developed negative perceptions over time. Findings underscore that although AI offers rapid suggestions, its benefits depend on students’ critical and selective engagement to avoid overreliance, which may otherwise compromise reflective depth and learning outcomes.
📝 Abstract
Generative AI is increasingly used for feedback in higher education, but evidence from repeated classroom use remains limited. This short paper analyses 2988 reflective essay-feedback-appraisal instances from 283 Estonian bachelor students across one semester. Students obtained and assessed feedback from a self-selected AI tool using a uniform prompt. The present analysis of the anonymized text corpus covers essay content, AI feedback, and its perceived helpfulness. Students found feedback helpful and actionable more often than not; about a tenth thought AI unhelpful, more so towards the end of the semester. We also analyzed essay reflection depth, and used a validated AI text classifier to estimate the share of essays that could be treated as likely unaided student writing. The study contributes descriptive classroom evidence on integration of AI feedback - a fast and scalable way to provide immediate writing advice, but not a self-contained route to better reflection. Benefits depend on whether students learn to use AI selectively and critically, without sliding into over-use harmful for the learning process.
Innovation
Methods, ideas, or system contributions that make the work stand out.
generative AI
student writing feedback
classroom integration
reflective writing
AI overuse
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