Corrective Feedback on Pronunciation: Students’ and Teachers’ Perceptions
Bibliographic record
Abstract
The aim of this research was to find out similarities and differences between teacher and student perceptions of corrective feedback (CF) on pronunciation for students’ presentations in advanced English class through a group interview and a questionnaire survey. Both teachers and students agreed that CF is not only important but necessary since junior and senior students still have pronunciation problems and the best time to provide CF is soon after presentation. However, they differed in concern about students’ self-respect, the types of errors that should receive CF and preference for the types of CF. In particular, students’ eagerness to learn exceeded their concern about self-respect. Teachers turned to offer CF to repeated errors, while students would like to receive more than teachers could offer. Moreover, teachers regarded prompt as being more effective, whereas students preferred recast to prompt considering the latter to be more demanding though they held similar views about explicit correction. It is suggested that taking into consideration both teachers’ and students’ perceptions of CF would help improve senior and junior students’ pronunciation.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".