Le corps enseignant face aux technologies de l’information et de la communication : un défi incontournable
Bibliographic record
Abstract
Cet article vise à illustrer empiriquement un modèle d’articulation des attitudes des enseignants face aux nouvelles technologies, inspiré de la théorie des représentations sociales. Tout d’abord, les auteurs présentent des éléments qui, au gré des époques et des approches théoriques, illustrent l’évidence des débats et des conflits qui ont accompagné l’introduction de toute nouvelle technologie dans les milieux scolaires. Ces éléments de débat constituent, à notre avis, des conditions favorables pour l’élaboration des représentations sociales chez un corps social, tel celui des enseignants. En deuxième partie, les chercheurs donnent une illustration empirique de la façon dont des enseignantes italiennes organisent leurs attitudes face aux nouvelles technologies de l’information et de la communication selon les prévisions de la théorie des représentations sociales.
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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 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".