Prompts and recasts: Differential effects on second language morphosyntax
Bibliographic record
Abstract
The merits of recasts have been widely debated and investigated in and out of the language classroom. This quasi-experimental study examines the impact of recasts in comparison to prompts and no corrective feedback on francophone learners' acquisition of English third person possessive determiners. Sixty-four students from three intact intensive English as a second language classes carried out 11 communicative activities during which they received corrective feedback according to the condition they were assigned to. An oral picture-description task and a computerized fill-in-the-blank task that kept record of participants' latency to retrieve the correct forms were administered prior to the treatment and immediately after it ended. Four weeks later the oral picture description task was readministered. Analyses of individual participants' oral data revealed that prompts were more effective than recasts and no corrective feedback in helping learners move up to more advanced stages of a developmental possessive determiner scale. This was especially apparent for low-proficiency learners. Data from the computerized task showed that prompts allowed learners to retrieve possessive determiner knowledge faster than recasts.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".