Liens entre le modèle CBAM et l’approche d’enseignement dans le contexte de l’adoption d’une classe d’apprentissage actif par des enseignants au postsecondaire | Relationships between the CBAM Model and the Approach to Teaching Inventory in the Adoption of the Active Learning Classrooms by Postsecondary Teachers
Bibliographic record
Abstract
Although research shows that the use of active learning clasrooms, specially designed for the use of technologies and active pedagogies, has positive impacts on learning (Beichner et al., 2007), the process by which teachers come to adopt this type of class setup has yet to be explored in depth. This multi-case study uses the Concern-Based Adoption Model (CBAM) and Approaches to Teaching Inventory (ATI) theoretical models to describe the cases of 15 teachers who use this class setup, which is still quite new in the Quebec cégep network. The results reveal CBAM stage of concern (SoC) profiles that are sometimes surprising, especially with regard to new users who display characteristics typical of advanced user profiles. A correlation of the SoC profiles with the teaching approach adopted could account for this profile distribution. Finally, as collaboration is shown to be a dominant factor in the teachers’ interests, its links with the CBAM levels of use (LoU) are discussed.Des recherches montrent que l’utilisation de classes d’apprentissage actif (CLAAC) a des impacts positifs sur l’apprentissage, spécialement dans les classes aménagées pour une utilisation de la pédagogie active et des technologies (Beichner et al., 2007). Cependant, le processus par lequel les enseignants en viennent à adopter ce type de classe semble inexploré. Cette étude fait appel aux modèles CBAM (Concern-Based Adoption Model) et ATI (Approaches to Teaching Inventory) pour décrire 15 cas d’enseignants qui utilisent ce type d’aménagement encore récent pour le réseau collégial québécois. Les résultats montrent des profils d’intérêt et de préoccupation parfois surprenants, en particulier chez les nouveaux utilisateurs qui affichent un profil d’utilisateur avancé. Une corrélation des profils d’intérêts avec l’approche d’enseignement pourrait expliquer cette distribution de profils. Enfin, la collaboration est un élément dominant dans les intérêts des enseignants et ses liens avec les niveaux d’utilisation sont exposés.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".