Students found AI feedback helpful and actionable more often than not across a semester of reflective writing¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Across 2988 annotated appraisals, 57% of student appraisals were coded helpful, 34% mixed, and 9% unhelpful, and 99% of AI feedback was rated 4 or 5 on a 1–5 specificity scale. → Andres Karjus 2026
Evidence¶
Andres Karjus 2026¶
Andres Karjus, Janika Leoste, Tiia Õun. (2026). Student Evaluation of Repeated AI Feedback Across a Semester of Writing. arXiv:2607.16115 [cs.CY]. https://arxiv.org/abs/2607.16115 doi:10.48550/arxiv.2607.16115
q2 · i? · associational · r2
Observational analysis of 2988 essay–feedback–appraisal triplets from one semester course, LLM-assisted annotation validated against human coding (96% match for helpfulness). The corpus shows over half the students found feedback helpful and 99% of feedback scored 4 or 5 on specificity.
"AIproducedspecificfeedback(99%4or5onascaleof1–5),whichoverhalfthestudentsfoundhelpful(57%;34%mixed,9%unhelpful,answeringourfirstRQ;seeFig. 2)"
Discussion¶
Related Claims¶
- Student appraisals became more critical over the semester, with actionable-support themes falling from 67% to 43% — related
- Most student essays remained at a descriptive reflection level despite repeated AI feedback — related
- Expressed helpfulness of AI feedback showed no association with next essay reflection depth — related
- Thematic coding of student reflections shows peers seen as understanding context and AI feedback seen as actionable, with one quarter of reflections expressing skepticism of AI — related
- After PAIRR, most students prefer combined peer and AI feedback over either source alone — related
- AI and peer feedback differed in complementary ways: AI gave general, rubric-driven, actionable feedback while peers gave more specific, contextual feedback — related
- Students who preferred AI feedback cited clarity, understandability, consistency, specificity, and 24/7 availability — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
students-find-ai-feedback-helpful-more-often-than-not |
title |
Students found AI feedback helpful and actionable more often than not across a semester of reflective writing |
description |
Students found AI feedback helpful and actionable more often than not across a semester of reflective writing |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — andres-karjus-2026 |
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