Student-voted Good feedback was associated with far fewer attempts and shorter solution times than Poor feedback, and thematic analysis identified outdated references and false positives as common failure modes¶
Claim · All claims
Evidence · 1 study · causalr2·q1
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.
q1 i? Assignments with Good-voted feedback were solved in far fewer attempts and shorter time than Poor-voted ones; thematic analysis of Poor feedback found outdated technology references (n=12) and cases where the materials implemented the same functionality the LLM flagged (n=12) as the most common error themes. → Tsvetomila Mihaylova 2026
Evidence¶
Tsvetomila Mihaylova 2026¶
Tsvetomila Mihaylova, Evanfiya Logacheva, Arto Hellas, Jing Fan, Francisco Castro, Bita Akram, Narges Norouzi, Peter Brusilovsky, Juho Leinonen. (2026). The Effects of Structured LLM-Generated Feedback on Programming Assignment Performance. https://arxiv.org/abs/2605.16933 doi:10.48550/arxiv.2605.16933
q1 · i? · causal · r2
Qualitative analysis of the small set of student-voted feedback messages (14 Good, 31 Poor votes across 45 votes; Table 5). Good-voted pairs averaged 2.92±1.04 attempts versus 13.95±17.34 for Poor. Thematic coding of Poor messages found outdated-version references (n=12) and no-actual-error cases (n=12) most common.
"Non-surprisingly, when Good feedback is given, the assignment is solved in a much fewer attempts and for much shorter time than when Poor feedback is shown."
Discussion¶
Related Claims¶
- Attempt-reduction patterns differed across course parts: Diagnostic and General Feedback were associated with fewer attempts for New Content, Single-Issue for Old Content — related
- AI grading errors concentrate in graphical tasks and include both false positives on incorrect equations and false negatives from misread sketches and labels — related
- All three LLM-generated feedback types are associated with faster time to solution than a compiler-errors-only baseline, with Single-Issue Feedback showing the largest reduction — related
- Advanced students showed reduced attempts with all hint types, while novices did not clearly benefit and made slightly more submissions with Single-Issue Feedback — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
student-voted-poor-feedback-failure-modes |
title |
Student-voted Good feedback was associated with far fewer attempts and shorter solution times than Poor feedback, and thematic analysis identified outdated references and false positives as common failure modes |
description |
Student-voted Good feedback was associated with far fewer attempts and shorter solution times than Poor feedback, and thematic analysis identified outdated references and false positives as common failure modes |
status |
review |
evidence_strength |
weak |
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 — tsvetomila-mihaylova-2026 |
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