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arXiv · 2607.16115

Student Evaluation of Repeated AI Feedback Across a Semester of Writing

Andres Karjus·Janika Leoste·Tiia Õun
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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.

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Andres Karjus, Janika Leoste, Tiia Õun. 2026-07-17. Student Evaluation of Repeated AI Feedback Across a Semester of Writing. https://arxiv.org/abs/2607.16115

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