Apprivoiser l’IA en enseignement postsecondaire : perspectives croisées des apprenants et apprenantes et du personnel enseignant au Nouveau-Brunswick
Bibliographic record
Abstract
Cette tude explore les perceptions et les pratiques lies l'intelligence artificielle gnrative (IAg) dans l'enseignement postsecondaire au Nouveau-Brunswick (Canada).Base sur une approche mixte, elle analyse les rponses de 281 participantes et participants issus de deux tablissements d'enseignement.Les rsultats montrent que l'adoption de l'IAg varie selon les profils, influenant les perceptions de son utilit et de ses implications thiques.Tandis que les tudiants et tudiantes peroivent l'IA comme un outil pdagogique, les enseignants et enseignantes expriment des proccupations sur son impact.Ces divergences soulignent la ncessit d'une formation systmatique pour dvelopper une littratie de l'IA adapte aux besoins du 21 e sicle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".