Améliorer les programmes canadiens de sciences et technologies au primaire par l’ajout de compétences du 21e siècle
Bibliographic record
Abstract
Dans cet article, nous presentons les resultats d’une synthese des connaissances visant a decrire les competences du 21e siecle, les competences de durabilite et les competences en technologies d’information et de communication (TIC) que les chercheurs considerent comme essentielles a developper chez les travailleurs de la societe actuelle. Il s’agissait aussi de relever, parmi ces competences, celles qui figurent dans les programmes de sciences au primaire des provinces canadiennes. Certaines competences recommandees pour oeuvrer dans le monde contemporain se retrouvent peu dans les programmes etudies : creation et resolution de problemes avec les TIC, entrepreneuriat, gestion, action strategique, adaptabilite, pensees systemique, connective et prospective… Nous proposons des pistes pour inserer ces nouvelles competences dans les programmes de sciences.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".