Teacher-Driven Professional Learning as a Vehicle for Teacher Leadership: A Qualitative Study of Participant Leadership roles in Ontario’s Teacher Learning and Leadership Program
Bibliographic record
Abstract
Over the past 20 years, a host of formalized teacher leadership programs have emerged in response to numerous calls for the re-culturing (Fullan, 2001) and re-professionalization (Hargreaves, 2000) of teaching. That being said, very little research has explored the manner in which such programs have facilitated real change in the leadership capacity of teachers. As such, the purpose of this study was to explore the nature and sustainability of leadership roles experienced by three participants in the Teacher Learning and Leadership Program (TLLP), a one-year program in Ontario, Canada, where teachers ‘take the lead’ in developing context specific professional learning opportunities with the aim of impacting both student and teacher learning. Results indicate that the TLLP provided participants with an avenue for the development and enactment of various teacher leadership opportunities both in and beyond their own school. However, extending that leadership beyond the timeframe of their TLLP projects proved to be a difficult endeavour. Understanding the impact of cultural norms, top-down hierarchies, and historical views of the teacher as implementer on the sustainability of teacher leadership is of particular relevance to planning committees who organize and develop such programs as well as progressive school boards who are genuinely interested in promoting authentic change in school leadership development.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".