Elicitation and Reformulation and Their Relationship With Learner Repair in Dyadic Interaction
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 research investigates the usefulness of two major types of interactional feedback (elicitation and reformulation) in dyadic interaction. The focus is on the different ways in which each feedback type is provided and their relationship with learner repair. The participants were 42 adult intermediate English as a second language learners and two native English teachers performing dyadic task‐based interactions. Six different reformulation subtypes and five different elicitation subtypes were identified, differing from one another in feedback salience, and the degree to which they pushed the learner to respond to feedback. Analysis of data on output accuracy following feedback showed that both reformulation and elicitation resulted in higher rates of accurate repair when they were combined with explicit intonational or verbal prompts compared with less explicit prompts or no prompts. These findings confirm the role of salience and opportunities for pushed output as important characteristics of effective feedback.
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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 | 0.001 | 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 | 0.001 |
| 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