Educational Development Websites: What Do They Tell Us About How Canadian Centres Support the Scholarship of Teaching and Learning?
Bibliographic record
Abstract
The study investigates how university educational development centres in Canada currently support faculty in developing the skills and knowledge to engage in the scholarship of teaching and learning. Content analysis of centre websites was used to identify strategies used to support SoTL. The main strategies identified were providing information and grants. Recommendations include increasing the visibility of SoTL on centre websites and integrating it with other centre activities. The data question the viability of a national strategy to improve teaching through SoTL. L’étude porte sur la façon dont les centres universitaires d’appui à la formation au Canada soutiennent actuellement les membres du corps enseignant dans le perfectionnement de leurs compétences et de leurs connaissances pour participer à l’avancement des connaissances en enseignement et en apprentissage. L’analyse du contenu des sites Web des centres a été utilisée pour déterminer les stratégies employées pour soutenir cet avancement. Les principales stratégies consistent à fournir de l’information et des bourses. Les recommandations portent sur l’augmentation de la visibilité de l’avancement de ces connaissances et sur son intégration aux activités du centre. Les données remettent en cause la viabilité d’une stratégie nationale visant à améliorer l’enseignement grâce à l’avancement des connaissances en enseignement et en apprentissage.
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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 | 0.078 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.032 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.019 |
| 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; both teacher heads agree on what is shown here.
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".