Writing Helpful Feedback: The Influence of Feedback Type on Students’ Perceptions and Writing Performance
Bibliographic record
Abstract
Written feedback on students’ assignments is a common method that instructors and teaching assistants use to inform students about their performance or guide revisions. Despite its frequency of use, written feedback often lacks sufficient detail to be beneficial to students, and additional empirical research should examine its effectiveness as a teaching tool. The current study examined the effectiveness of two different types of feedback, developed and undeveloped, in terms of its influence on students’ subsequent writing performance and students’ perceptions of the feedback. Results demonstrated that the type of feedback significantly affected students’ perceptions, with developed feedback related to higher ratings of fairness and helpfulness; however, this feedback did not have a significant positive effect on students’ written performance. Les commentaires écrits sur les travaux sont une méthode courante utilisée par les enseignants et les aides-enseignants pour renseigner les étudiants sur leurs performances ou pour orienter les révisions. Malgré leur fréquence, il arrive souvent que les commentaires écrits ne soient pas assez détaillés pour être profitables aux étudiants. De plus amples recherches empiriques devraient se pencher sur l’efficacité de cet outil d'enseignement. La présente étude porte sur l'efficacité de différents types de commentaires élaborés et sous-élaborés; sur leur influence sur la performance écrite subséquente des étudiants et sur la perception de ces derniers à propos des commentaires. Les résultats démontrent que le type de commentaires influe significativement sur la perception des étudiants, les commentaires élaborés entraînant des évaluations supérieures en ce qui a trait à l’impartialité et à l'utilité; cependant, ces commentaires n'ont pas d'effets positifs importants sur la performance écrite des étudiants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".