Contextual Opportunities for Teacher Professional Learning: The Experience of One Science Department
Bibliographic record
Abstract
In this article we investigate the changing context for teacher professional learning potentially afforded by the conceptual change from professional development to professional learning. Using a narrative case study methodology, we utilize the Best Evidence Synthesis Iteration developed by Timperley, Wilson, Barrar and Fung (2007) to analyse the teachers’ responses to the changing context within their school. Our analysis reveals three important findings: the negligible impact of school policy on the work of the teachers, the willingness of teachers to utilize appropriate expertise, regardless of the source of that expertise, and the manner in which these teachers have developed a community in which teaching practices, both individual and corporate, can be discussed and critiqued. The clear implication of these findings is that it is teachers, working within the department and wider science education community, who were making the conceptual change from professional development to professional learning.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.019 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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".