ÉCHELLE DESCRIPTIVE D'APPRÉCIATION DU RENDEMENT DE L'ÉLÈVE: ACQUIS ET PROBLÉMATIQUES
Bibliographic record
Abstract
RESUME Sous l'influence du constructivisme et du cognitivisme, l'evaluation en salle de classe se degage progressivement de la notation quantitative et tente de mettre a profit des approches plutot qualitatives. Ce virage a suscite recemment de nombreux ecrits sur l'evaluation de la performance a partir d'une echelle descriptive d'appreciation. Le present article fait etat des acquis en matiere de notation qualitative et analyse les principaux aspects problematiques. DESCRIPTIVE RATING SCALE OF STUDENT PERFORMANCE: STATE OF THE ART ABSTRACT. Under the influence of constructivism and cognitivism, classroom assessment is gradually moving from quantitative to qualitative grading methods. This change of direction has given rise ta many papers on performance assessment using a descriptive rating scale such as the rubric. This article reports on the current trends in qualitative grading and analyzes the main problematic aspects.
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 | 0.034 | 0.135 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".