A Corrective Feedback Intervention in a Minority French Language School
Bibliographic record
Abstract
Abstract Educators in French schools in southern Ontario are challenged with the task of increasing their students’ oral linguistic ability in French within their predominantly English-speaking surroundings. Additionally, teachers wonder how they can provide guidance without discouraging students’ efforts and negatively affecting their self-efficacy. The purpose of this study was to examine whether or not corrective feedback (CF) from teachers and peers decreased the number of anglicisms and grammatical errors that students typically make and how an intervention based on CF would affect students’ self-efficacy with respect to their beliefs about their own communication skills. The research was premised on sociocultural and skills acquisition theory. The study employed a convergent mixed methods design that took place in a Grade 3/4 classroom in a French school in southern Ontario for a period of 4 months. Quantitative data were collected from oral communication tests, standardized vocabulary tests, and attitudinal tests. Qualitative data were derived from field notes taken from observations and interviews. The quantitative results indicated that the number of anglicisms and grammatical errors did not diminish significantly but students’ behaviour showed an increased awareness of language form and an increased willingness to improve. Qualitative and quantitative findings suggest that CF did not negatively affect students’ self-efficacy. As well, the findings indicated that students’ self-confidence and pride, their perceptions of improvement, and collaboration skills all increased during the CF intervention. Overall, this research provides implications for practice, research, and theory that can be used to implement effective ways of improving oral communication skills in minority language instruction through CF.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".