Et si la recherche collaborative participait au développement de pratiques évaluatives sommatives cohérentes ?
Bibliographic record
Abstract
De multiples études montrent que les pratiques évaluatives sommatives des enseignants manquent souvent de cohérence, tous contextes confondus. Cet article décrit comment six enseignants de français et de mathématiques suisses romands du secondaire ont amélioré cette cohérence en participant à une recherche collaborative 1 , dans laquelle l’activité réflexive a fait l’objet d’une attention particulière en prenant en compte leurs questions, leur contexte et leur discipline. Menée à l’aide de catégories conceptualisantes, l’analyse qualitative de leurs épreuves, d’entretiens compréhensifs, d’écrits de pratique et des échanges en séances de travail montre que six compétences évoluent positivement chez chacun d’entre eux dans une perspective dynamique, au service de leur développement professionnel, et que cette évolution est notamment permise par les contenus théoriques proposés au sein du dispositif.
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 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 | 0.148 | 0.187 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.028 | 0.038 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".