Cross-cultural influences on corrective feedback preferences in English language instruction
Bibliographic record
Abstract
This cross-cultural study examined the preferences of 137 Taiwanese EFL students and 97 ESL Quebecois students for specific types of corrective feedback, as well as their attitudes and beliefs about error correction, and those of 12 Taiwanese English instructors and 12 native English teachers in Quebec. All participants completed two questionnaires, the first eliciting overall preferences and attitudes for corrective feedback, and the second eliciting preferences for specific types of feedback aurally modeled through a digital recording designed for the purpose of this study. In addition, a subsample of participants was selected for follow-up interviews. Descriptive analysis of the initial questionnaire coupled with trends found in interview data revealed cross-cultural differences in preferences for types of errors to correct, the use of correction, rates of correction and affective reactions to error correction. However, statistical analysis of the data yielded by the main elicitation instrument revealed similar preferences within both cultural groups, with explicit correction being ranked highest, followed by recasts and then prompts.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".