Learners’ Beliefs About Corrective Feedback in the Language Classroom: Perspectives from Two International Contexts
Bibliographic record
Abstract
This study compared the beliefs college-level students hold about corrective feedback in different learning contexts: English as a second language (Canada, n = 197) and English as a foreign language (Russia, n = 224). The participants completed a 40-item questionnaire that dealt with various aspects of feedback found in the literature. While the factor analyses revealed underlying beliefs that were shared by the two populations, the Mann-Whitney-Wilcoxon test identified aspects that differed from one setting to another. To determine possible effects of the background factors, these were correlated with the average belief scores calculated for each participant. The results validate the questionnaire, point to certain background factors that may predict beliefs, and suggest that some beliefs about feedback may be shared across contexts. Cette étude a comparé les croyances qu’ont des étudiants universitaires par rapport à la rétroaction corrective dans divers contextes d’apprentissage: anglais langue seconde (Canada, n = 197) et anglais langue étrangère (Russie, n = 224). Les participants ont complété un questionnaire à 40 items portant sur divers aspects de la rétroaction puisés dans la littérature spécialisée. Alors que des analyses factorielles ont révélé des croyances communes aux deux groupes, le test Wilcoxon-Mann-Whitney a identifé des aspects qui distinguaient les deux milieux d’apprentissage. Pour déterminer les e ets possibles de ces facteurs fondamentaux, nous avons évalué la corrélation entre les résultats moyens sur les croyances tels que calculés pour chaque participant. Les résultats obtenus confirment le questionnaire, révèlent certains facteurs de base qui pourraient prédire les croyances et indiquent que certaines croyances sur la rétroaction se retrouvent dans différents contextes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".