Encourager le développement des cultures régénératrices dans le domaine de l'éducation : une approche axée sur l'apprentissage expansif
Bibliographic record
Abstract
In the face of the climate and collective well-being urgency in the contemporary world, it is possible to question the ontological and epistemological approach of the educational and productive system in our societies. The reconceptualization of our relationship with the living requires a transformation of practices that can be considered from the perspective of expansive learning. In this article, we analyze the collective design process of a group of secondary school teachers engaged in creating teaching and learning sequences incorporating sustainable development goals (SDGs). We draw on the cultural-historical activity theory (CHAT) to analyze the design process. The formative intervention implemented with these teachers helps identify manifestations of contradictions present when integrating a sustainable development approach into disciplinary learning. Levers to overcome these contradictions are also identified. The results of this formative intervention, which led to a guide for interdisciplinary activities on the SDGs, are also presented.
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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 | 0.037 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".