Teachers’ and Students’ Beliefs and Perspectives about Corrective Feedback
Bibliographic record
Abstract
The current chapter focuses on two main stakeholders of corrective feedback: teachers and learners, and it discusses whether and how teachers’ and learners’ beliefs or attitudes toward corrective feedback impact the effectiveness of corrective feedback. Previous research on both oral and written corrective feedback is reviewed. In terms of teachers’ beliefs of corrective feedback and their feedback practices, some research findings showed that teachers’ beliefs are not always in line with their actual classroom practices related to the use of different types of oral corrective feedback. Learners’ beliefs about the effectiveness of corrective feedback, particularly written corrective feedback, were found to be an important factor of learner engagement with corrective feedback. Recent corrective feedback research claims that teacher and learner beliefs are not static. Accordingly, the current literature review shows methodological changes over time, capturing the situational and dynamic patterns of learners’ and teachers’ beliefs about corrective feedback. The overall findings suggest that teachers’ and learners’ beliefs about CF are multifaceted and could be impacted by various contextual factors.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".