La parole aux milieux collégial et universitaire: réflexions et résultats d'enquêtes sur l’IA générative
Bibliographic record
Abstract
Le présent document propose un bilan de la Journée de réflexion sur l'IA générative en enseignement supérieur du 18 juin 2025, organisée par l'Obvia en collaboration avec le Pôle interordres de Montréal (PIM). Au total, 89 personnes provenant de 24 établissements d’enseignement supérieur (14 universités et 10 cégeps) ainsi que de 7 organisations œuvrant dans le milieu (associations étudiantes, syndicats, organismes publics, etc.) ont participé à l'événement. Reprenant la structure de la journée, le document est principalement divisé autour de deux éléments suivants : 1- Les faits saillants et résultats des 5 initiatives et projets de recherche présentés lors de l'événement, portant sur les perceptions, l'utilisation et l'intégration de l'IAg dans les cégeps et les universités. 2- La synthèse de l'atelier de discussions auquel ont pris part les participantes et participants issus des milieux collégial et 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 | 0.023 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".