Et si des situations d’enseignement-apprentissage différenciées et collaboratives pouvaient faire la différence ?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Il s'avre parfois complexe de planifier des situations d' enseignement et d'apprentissage (SEA) qui, comme le mentionne le Programme de formation de l' cole qubcoise (PFEQ), exploitent les champs d'intrt des lves, respectent les diffrents rythmes et prfrences d'apprentissage tout en s'appuyant sur leurs forces, les ressources disponibles et les acquis de chacun d' eux, et ce, tout en composant avec les diffrents contextes personnels, sociaux et familiaux. Cette chronique abordera un projet de collaboration entre chercheuses, conseillres pdagogiques et enseignants en classe spcialise provenant de trois coles d'un mme centre de services scolaire (CSS).
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it