Detecting and sharing praxeologies in solving interconnecting problems: some observations from teacher education viewpoint<br>Détecter et partager les praxéologies dans la résolution de problèmes d'interconnexion: quelques observations du point de vue de la formation des enseignants
Bibliographic record
Abstract
AbstractThis paper discusses praxeologies available at different levels of schooling in view of a problem, which permits multiple solutions ranging from elementary to more advanced mathematical approaches. Solutions of the problem produced by mixed groups of K-12 teachers included numerical, pictorial and algebraic methods, and allowed observing possible paths within a finalized activity of study and research. They also gave some insights regarding teachers’ readiness to support the continuity of students’ praxeological development, and more generally, the potential within teachers’ educational backgrounds to pursue the new paradigm of questioning the world.Keywords: Teacher education, Praxeological development, Mathematical problems with multiple solutions.RésuméCe texte discute les praxéologies disponibles à différents niveaux de la scolarité pour résoudre un problème qui permet des résolutions multiples, depuis des approches élémentaires aux plus avancées. Les résolutions proposées par un groupe mixte d’enseignants de l’école élémentaire jusqu’au lycée ont employé des méthodes numériques, graphiques et algébriques, et permettent d’observer les parcours possibles d’une activité finalisée d’étude et de recherche. Elles nous laissent aussi percevoir la capacité des enseignants pour soutenir la continuité du développement praxéologique des élèves, et plus généralement le potentiel résultant de la formation des enseignants à poursuivre le nouveau paradigme du questionnement du monde.Mots-clés: formation des enseignants, développement praxéologique, problèmes mathématiques aux solutions multiples.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".