Quand les contextes se comparent et se parlent
Bibliographic record
Abstract
L’idée de départ du projet TEEC consiste à intégrer le contexte dans l’apprentissage des sciences et d’étudier les modalités de cette intégration. Face à un enseignement trop souvent détaché du contexte, le rôle de ce dernier pourrait être mis en lumière au bénéfice des élèves en provoquant un choc entre deux contextes contrastés, dans le cadre de l’étude d’une même notion scientifique. Ce projet s’appuie sur des apprentissages collaboratifs synchrones et asynchrones menés par des élèves de Guadeloupe et du Québec. La méthodologie retenue est de type Design-Based Research (DBR), et se matérialise par la mise en œuvre de plusieurs itérations in situ. Ces itérations portent sur l’histoire sociale, la géothermie, l’éducation au développement durable, et le conte. L’enjeu de ce projet de recherche est d’étudier les relations entre modélisation des contextes externe et émergence des effets de contextes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".