CONCEPTION D’UN LIVRE NUMÉRIQUE SUR LES CIRCUITS ÉLECTRIQUES ET FORMATION DES ENSEIGNANTS / DESIGN OF A NUMERIC BOOK ON ELECTRIC CIRCUITS AND TEACHER EDUCATION
Bibliographic record
Abstract
Dans la présente recherche, nous présentons un résumé des travaux réalisés de par le monde sur la formation scientifique des enseignants des écoles primaires et nous verrons qu’elle est insuffisante pour initier les élèves aux sciences. Ensuite, nous esquissons une synthèse des recherches qui développent des environnements didactiques axés sur l’expérimentation, en vue d’aider les enseignants à acquérir les rudiments de la démarche expérimentale. Finalement, nous illustrons la structure générale d'un livre numérique portant sur l'expérimentation relative aux fonctionnements de circuits électriques simples, suivis de quelques commentaires d'étudiants québécois en formation qui l'ont étudié dans le cadre d'un cours universitaire portant sur la didactique des sciences et des technologies, au primaire. In this research, we present a summary of the work done around the world on the scientific training of primary school teachers and we will see that their training is deficient. Then, we sketch a synthesis of research that develops didactic environments focused on experimentation, to give teachers, the basics of the experimental approach. Finally, we illustrate the general structure of a digital book on experimentation related to the operation of simple electrical circuits, followed by some comments from Quebec students in training who experimented with it in a university course on the didactics of sciences and technologies at the primary level. Article visualizations:
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".