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Record W4379231625 · doi:10.1080/13664530.2023.2216663

What are primary teachers’ experiences of policy on shaping a context of sustainable mathematics professional development?

2023· article· en· W4379231625 on OpenAlexaff
Evelyn Penfold

Bibliographic record

VenueTeacher Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsUniversity of Alberta
FundersUniversity of Roehampton
KeywordsNumeracyProfessional developmentNational curriculumCurriculumContext (archaeology)Mathematics educationFaculty developmentSustainable developmentCognitively Guided InstructionNational PolicyPedagogyCurriculum developmentSociologyPolitical sciencePsychologyLiteracyGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.033
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0210.023
Scholarly communication0.0230.010
Open science0.0020.012
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.083
GPT teacher head0.377
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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