The Analysis of Content and Operational Components of Public School Teachers’ Continuing Professional Development in Great Britain, Canada and the USA
Bibliographic record
Abstract
Abstract In the article the content and operational components of continuing professional development of public school teachers in Great Britain, Canada, the USA have been characterized. The main objectives are defined as the theoretical analysis of scientific-pedagogical literature, which highlights different aspects of the problem under research; identification of the common features of the content, models, forms and methods of continuing professional development of public school teachers. The legislative and normative framework of teachers’ CPD in Great Britain, Canada and the USA, which determines the CPD content, has been highlighted; teachers’ knowledge, skills, professional values and attitudes have been characterised; the key models, forms and methods of teachers’ CPD have been defined. The teachers’ CPD has been studied by foreign and Ukrainian scientists: models, forms and methods of teachers’ CPD (L. Chance, A. Hollingsworth, D. Ross, E. Villegas-Reimers), non-formal teachers’ CPD (J. Scheerens), continuing professional education (Ya. Belmaz, T. Desyatov), postgraduate education (A. Kuzminskyy, V. Russol), professional education (R. Hurevych, N. Nychkalo), teacher training (T. Koshmanova, Ye. Yevtukh), teachers’ professional development (N. Klokar, V. Oliynyk). The research methodology comprises theoretical (logical, induction and deduction, comparison and compatibility, structural and systematic, analysis and synthesis) and applied (observations, questioning and interviewing) methods. The research results have been presented.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".