Evaluating the individual and combined impact of national leadership programmes in England: perceptions and practices
Bibliographic record
Abstract
The National College for School Leadership (NCSL) was launched in 2000 with a remit to supervise and further enhance educational leadership development initiatives in England and Wales. Its corporate plan for 2003–07 set out a series of key objectives, which include a commitment to demonstrate the impact of the NCSL on school leadership. Some empirical evidence is beginning to emerge regarding the efficacy and impact of programmes delivered under the aegis of the NCSL but systematic studies of the ways in which school effectiveness is enhanced in schools that have been subject to multiple interventions in leadership development are less visible in the literature. This article reports on a study that included both a questionnaire survey and case studies of 10 schools which required school leaders, at all levels from middle managers to headteachers, to reflect on the impact that national programmes, both individually and cumulatively, were having on their personal professional development and on their schools as a whole. Findings of the study suggest that there is evidence that national leadership programmes are impacting positively on leadership in schools although the level of impact appears to be variable across programmes. The paper is offered as one contribution to the International Study of the Preparation of Principals (ISPP) project based at the University of Calgary.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".