Un nouveau regard sur les profils des enseignants à l’égard de l’intégration des TIC
Bibliographic record
Abstract
Cette étude de cas trace le profil des enseignants d’une école élémentaire francophone de l’Ontario à partir de trois modèles : les représentations des enseignants face à leurs compétences avec les TIC (Desjardins, 2005), les catégories d’adoptants à partir des traits de personnalité (Rogers, 1995) ainsi que l’évolution des préoccupations et de l’utilisation de l’innovation (Hall & Hord, 1987). Elle met en évidence six regroupements : les initiateurs, les collaborateurs, les observateurs, les apprentis, les hésitants et les réfractaires. Ces profils constituent un moyen pour mieux comprendre les enseignants face au changement qu’ils vivent en regard de l’intégration des TIC et ainsi permettre aux décideurs de mieux intervenir. (A new perspective on teacher profiles with regards to their integration of ICTs) This case study highlights the profiles of teachers in a francophone elementary school of Ontario using three models: the representations of the teachers’ competencies in regards to ICT’s (Desjardins, 2005), the categories of adopters based on personality traits (Rogers, 1995) as well as the evolution of preoccupations and use of innovation (Hall & Hord, 1987). This study focuses on six profiles: the initiators, the collaborators, the observers, the apprentices, the hesitant and the refractory. These profiles constitute a way of better understanding teachers’ adjustment as a result of the changes they are currently facing regarding the integration of ICT’s and thus allows school administrators to better intervene.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".