Child-to-child interaction and corrective feedback during eTandem ESL–FSL chat exchanges
Bibliographic record
Abstract
This study examined the role of corrective feedback in the context of an English as a second language (ESL) and French as a second language (FSL) eTandem chat exchange involving Grade 6 students. The students were enrolled in intensive programs in the provinces of Quebec and Ontario and had an elementary to low- intermediate level of language proficiency. Tasks were completed on a weekly basis over a 9-week period. Six tasks completed by 13 pairs were retained for analysis. The analysis showed that the ESL and FSL students provided three types of feedback: explicit feedback, recasts, and negotiation of form. Unlike the study by Morris (2005), which involved Grade 5 second language (L2) Spanish students, the preference in this study was for explicit feedback. This difference was attributed to the tandem approach which emphasizes training in how to give feedback as well as school culture. Differences between the amount of feedback provided during the ESL and FSL exchanges were also observed. Here, too, the influence of school culture appears to have been a factor. The ESL students appeared to be more positively oriented to L2 learning, reflected in a higher appreciation of the tandem learning exchange. Implications for teaching and the need of future research are discussed.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".