PEER INTERACTION AND CORRECTIVE FEEDBACK FOR ACCURACY AND FLUENCY DEVELOPMENT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This quasi-experimental study is aimed at (a) teaching learners how to provide corrective feedback (CF) during peer interaction and (b) assessing the effects of peer interaction and CF on second language (L2) development. Four university-level English classes in Japan participated ( N = 167), each assigned to one of four treatment conditions. Of the two CF groups, one was taught to provide prompts and the other to provide recasts. A third group participated in only peer-interaction activities, and a fourth served as the control group. After one semester of intervention, the two CF groups improved in both overall accuracy and fluency, measured as unpruned and pruned speech rates, whereas the peer-interaction-only group outperformed the control group only on fluency measures. This study draws on monitoring in speech-production theory and the declarative-procedural model of skill-acquisition theory to interpret these results, thus contributing a new theoretical approach to CF research in the context of peer interaction in which learners can be providers of CF. It is concluded that whereas peer interaction offered opportunities for repeated production practice, facilitating proceduralization, CF sharpened learners’ ability to monitor both their own language production and that of their interlocutors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it