Corrective Feedback in SLA: Theoretical Relevance and Empirical Research
Bibliographic record
Abstract
<p>Corrective feedback (CF) refers to the responses or treatments from teachers to a learner’s nontargetlike second language (L2) production. CF has been a crucial and controversial topic in the discipline of second language acquisition (SLA). Some SLA theorists believe that CF is harmful to L2 acquisition and should be ruled out completely while others regard CF as an essential catalyst for L2 development. The last two decades have witnessed a dramatic increase in empirical research on the effectiveness of CF. This article, with an aim to provide an informed knowledge of the potential role of CF, briefly traces the history of research on CF and proposes some recommendations for further studies. It starts by surveying a range of theoretical stances on the role of error and error correction (also known as CF) in SLA. It then moves into detailed discussion of three issues on CF heatedly debated either within a cognitive or a sociocultural framework. By examining the empirical findings, some possible topics for further studies are uncovered.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".