Developing Teachers as the Learning Profession: Findings from the State of Educators’ Professional Learning in Canada Study
Bibliographic record
Abstract
Teachers’ professional development and learning is of high interest in educational reform internationally. We present findings from the State of Educators’ Professional Learning in Canada study. We identify ten features proposed for effective professional learning: evidence-informed; subject-specific and pedagogical content knowledge; a focus on student outcomes; a balance of teacher voice and system coherence; active and variable learning; collaborative learning experiences; job-embedded learning; ongoing in duration; resources; and supportive and engaged leadership. Our findings indicate that these features are present in current professional learning experiences within Canada. However, we also found important differences in the details of professional learning within and across Canada. We suggest it is important to research, value and understand the diversity of professional learning needs, activities, experiences and outcomes within and across countries. We discuss potential considerations for the study of teachers’ professional learning in Scotland to contribute to improvements locally and to inform global debates.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.015 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".