Enseigner les stratégies de créacollage numérique pour éviter le plagiat au secondaire
Bibliographic record
Abstract
De nos jours, les eleves du secondaire ont de plus en plus recours au web lorsqu’ils ont besoin d’information pour leurs travaux scolaires. L’acces facile et rapide a cette information mene certains eleves au copier-coller. Afin de prevenir le plagiat, une serie de sept ateliers portant sur des strategies de creacollage numerique ont ete offerts a 63 eleves du secondaire. Les participants ont repondu a des questionnaires et participe a des entrevues. Les resultats montrent que les strategies de creacollage sont meconnues des eleves du secondaire et qu’elles gagneraient a y etre enseignees afin que ceux-ci prennent de bonnes habitudes de redaction et apprennent comment rediger sans plagier.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".