What are primary teachers’ experiences of policy on shaping a context of sustainable mathematics professional development?
Bibliographic record
Abstract
The author explored the extent to which policy could be a source of sustainable professional development for elementary teachers’ mathematical knowledge for teaching. The study involved three policies in England: the National Numeracy Strategy and the Primary National Strategy, introduced in response to concerns regarding mathematics teaching and student attainment, and a new National Curriculum. Professional development was offered to support teachers in the processes of changing their practice. This article focuses on the responses of eight teachers who suggest that the National Numeracy Strategy and the Primary National Strategy were useful sources of mathematical knowledge for teaching. However, the 2013 National Curriculum, along with the teaching for mastery policy, show how the teachers’ professional development had been rooted in policy enactments and was temporal. The author discusses the need for sustainable professional development to facilitate teachers’ continuous enhancement of their mathematical knowledge for teaching within a changing policy landscape.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".