La construction du sens autour de la notion de compétence dans des dispositifs universitaires en alternance
Bibliographic record
Abstract
Lorsque l’on se propose d’étudier le développement de compétences dans des formations de l’enseignement supérieur, il nous semble important d’analyser les « éléments de preuve » que les étudiants peuvent apporter pour démontrer leur acquisition. Les productions en contexte professionnel et en situation scolaire peuvent servir de bases d’évaluation et orienter la démarche d’accompagnement des formateurs. Dans cette recherche, nous allons nous intéresser aux preuves de l’acquisition de compétences chez des étudiants de premier cycle universitaire en éducation sociale, travail social, éducation préscolaire et primaire d’une université espagnole lors de leur stage pratique. Le but est de proposer un modèle d’interprétation de la construction de compétences transversales dans les formations universitaires.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".