La crise sanitaire : une occasion de penser des pratiques d’évaluation dans le cadre d’un enseignement à distance
Bibliographic record
Abstract
La crise sanitaire a imposé aux structures d’enseignement supérieur la mise en place d’un enseignement à distance. Dans ce cadre, l’évaluation des apprentissages s’est avérée difficile. Notre article propose de présenter différentes stratégies d’évaluation mises en place par des équipes pédagogiques lors des semestres en distanciel, de discuter de leurs limites et de mettre en lumière les questionnements et les prises de conscience des enseignants. Afin de nourrir ce bilan, le ressenti des étudiants quant à ces évaluations est aussi présenté. Au-delà de l’utilisation d’exemples dans les pratiques et de la littérature existante sur le sujet, nous souhaitons prendre un recul critique afin de voir dans quelle mesure cela pourrait également s’appliquer dans une perspective d’enseignement en présentiel.
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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 | 0.083 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.053 |
| Scholarly communication | 0.028 | 0.024 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.008 | 0.016 |
| 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".