Types conatifs et interventions pédagogiques différenciées en milieu universitaire
Bibliographic record
Abstract
L’objectif principal de cette étude visait à vérifier la pertinence d’utiliser le Kolbe A Index dans une classe différenciée. Trente sujets âgés de 22 à 35 ans fréquentant le Campus Saint-Jean de l’Université de l’Alberta ont été recrutés à cette fin. Les étudiants avaient le choix de faire deux travaux de session en ayant recours à un des quatre styles de production (document écrit, schéma, présentation orale et production manuelle). Les résultats de l’étude vont partiellement dans le sens des données recueillies par Kolbe (2004) dans le milieu de l’entreprise. En fait, plusieurs des sujets ont choisi une forme de production qui correspond à leurs types conatifs. Les auteurs font ressortir, en conclusion, les limites et l’intérêt d’avoir recours au Kolbe A Index dans une classe différenciée en milieu universitaire.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".