Transfert <i>ELA</i>-FLS : projet de développement professionnel d’enseignants pour encourager les élèves à transférer leurs apprentissages langagiers
Bibliographic record
Abstract
The Quebec French as a Second Language (FSL) programs explicitly mention the importance of linguistic transfer to develop language competencies. In 2013, the Quebec Ministère de l’Éducation et d l’Enseignement supérieur launched a professional development project to foster student language transfer and to support collaboration between English Language Arts ( ELA) and FSL teachers. In this paper, we present the ELA-FSL Transfer project, which is the result of a didactic transposition of psycholinguistic theories and praxis inspired by research on crosslinguistic pedagogy. We will illustrate two elementary school teachers’ perceptions of their professional development based on a semi-guided interview conducted three years after the project. The teachers affirmed their continued practice of teaching for transfer between the two language subjects. A thematic analysis of the interview transcript was done using the four key elements of the project, namely (1) activating background linguistic knowledge, (2) modelling language learning strategies, (3) reflecting on language, and (4) collaboration between teaching partners.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".