Bibliographic record
Abstract
Cette étude de méthodologie mixte cherche à mieux comprendre le choix des nouveaux enseignants au Nouveau-Brunswick francophone d’intégrer l’ordinateur et d’autres technologies dès leur première année en pratique professionnelle. Les résultats de notre analyse de régression linéaire semblent confirmer les conclusions d’autres études en ce qui a trait à l’intégration pédagogique des TIC dans la pratique enseignante. Plus précisément, nous rapportons que la décision d’intégrer l’ordinateur et d’autres TIC à sa pratique enseignante peut être expliquée, en partie, par une combinaison des attitudes chez l’enseignant en formation et ses sentiments d’auto-efficacité envers les TIC comme outils pédagogiques. Enfin, un regard qualitatif sur l’intégration pédagogique des TIC chez quelques-uns de nos participants en première année d’enseignement révèle certains défis dans la pratique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.268 | 0.443 |
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".