Investigating What Second Language Learners Do and Monitor under Careful Online Planning Conditions
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
Abstract: This study used quantitative analyses complemented by the retrospective data obtained through a stimulated recall procedure to address three interrelated issues: (a) whether second language learners use online planning opportunities to carefully plan their speech to enhance the quality of the language they produce, (b) what kinds of self-repair behaviour the pressured and careful online planning conditions are likely to induce speakers to make, and (c) the way careful online planning affects EFL learners’ oral L2 performance as measured in terms of complexity, accuracy, and fluency. Thirty intermediate EFL learners were asked to perform an oral narrative task under careful and pressured online planning conditions. Results of the qualitative and quantitative analyses revealed that L2 learners use the planning time to monitor their speech for grammatical accuracy, to retrieve and monitor the appropriate lexical items, and to plan the message they will communicate. In addition, it was found that careful online planning conditions induce learners to execute more error repairs and fewer appropriacy and different-information repairs compared to the pressured online planning condition. An analysis in terms of complexity, accuracy, and fluency measures testified to the positive effects of careful online planning on L2 oral performance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it