Development of Speaking Skills in Children Versus Adult<scp>L2</scp>Learners
Bibliographic record
Abstract
The view that speaking cannot be taught challenges language teachers' goals of fulfilling one of second language learners' primary needs: They must be allowed to speak in order to develop speaking skills. Yet educators unaware that speaking can be taught may not orchestrate classroom instruction to promote its development. In this entry past and present stances on the topic are reviewed and key issues are raised, including the need to (a) understand the role of speaking in the BICS/CALP distinction, (b) draw on plurilingual students' full range of linguistic repertoires to support their development of fluency and accuracy in speaking, and (c) scaffold spoken interaction at all levels. The pedagogical implications of these issues relate to how to structure appropriate instructional spaces (including practices) to enable all learners—K‐12 ESL learners, EFL learners at the tertiary level, and even rank beginners—to develop speaking skills. The issues discussed here also relate to the need for educators' and learners' cross‐cultural awareness if optimal skill development is to be achieved.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".