Developing Non-Positional Teacher Leadership of Formative Assessment Practices: Findings from the Teacher-Led Learning Circles Project
Bibliographic record
Abstract
This article examines the development of teacher leadership through the Teacher-Led Learning Circles project, a professional learning and research initiative across seven countries: Brazil, Côte d’Ivoire, Ghana, Malaysia, South Korea, Switzerland, and Uruguay. Through targeted professional development over one academic year, the project advanced non-positional teacher leadership and confidence in four core formative assessment strategies as well as the embedded use of these strategies by teachers. Data were collected through multiple sources, including a teacher pre-survey (n = 171), a teacher post-survey (n = 121), a teacher codification framework questionnaire (n = 113), a local facilitator questionnaire (n = 27), a local union representative questionnaire (n = 10), a national researcher questionnaire (n = 7), and seven country profiles. Findings show that when teachers are supported, their influence grows, and formative assessment practices become more embedded and confident, highlighting the potential of teacher-led professional development for sustainable educational improvement.
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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 | 0.035 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".