Vietnamese EFL Students’ Perceptions of Noticing-Based Collaborative Feedback on Their Writing Performance
Bibliographic record
Abstract
It has been theoretically and empirically acknowledged that collaborative feedback is beneficial to learning achievement. However, feedback research remains relatively contentious due to learners’ differing viewpoints on how feedback is best given. Although a large number of studies have explored learners’ perspectives on collaborative feedback, little classroom-based research has promoted noticing through collaborative feedback. To address this, this study aims to infuse noticing-based collaborative correction into secondary classrooms to explore students’ perceptions of such feedback practice on their written output. Forty-one students’ responses to the list of close-ended questionnaires revealed a strong consensus about this potential approach although there are indications that the participants’ dependent learning styles had influenced these findings. An obvious implication of this is that students might benefit from various scaffolding sources, and thus there is a need for teachers to be aware of the influence of reciprocal learning among learners so that the quality of feedback practices may be enhanced.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".