Informal Teacher Leaders: Secondary School Teachers’ Perceptions of How They Collaboratively Construct and Implement Classroom Assessment Policy and Practice
Bibliographic record
Abstract
Secondary school teachers enact informal teacher leadership to move their instructional and assessment practices forward by leveraging existing structures and navigating micropolitical contexts. Leadership cannot be oversimplified as the work of an individual because of the complex and interwoven nature of schools and the current political climate of educational settings. Informal teacher leaders (ITLs) co-create roles based on needs that focus on supporting learning for students, for colleagues, and for themselves. This study used a constructivist lens and inquiry methodology to explore perceptions of informal secondary school teacher leaders as they collaboratively construct and implement classroom assessment policy and practice. The study highlights the perceived purpose and nature of informal teacher leadership; organizational factors and conditions that ITLs face when working collaboratively to improve assessment practices; and strategies that these teachers leverage to navigate changes in assessment practice and policy. (Note: a provincial review of assessment was conducted during completion of this dissertation.) This qualitative study explored informal teacher leadership and assessment practice and policy through semi-structured interviews, focus groups, document analysis, and memoing. The research encompassed 28 participants, 11 of whom are ITLs in a suburban school district in Ontario. Findings reveal how ITLs structure their roles to be responsive, reciprocal, reflective, and results oriented. Recommendations are provided to inform educators and policy developers at the provincial, district, and school level for both supporting informal teacher leadership and developing assessment literacy.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 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".