Preparation and training of Hungarian school directors
Bibliographic record
Abstract
Our fast-paced and seemingly ever-changing world is reflected in the transformations that are occurring in our school systems. Meeting the dynamic needs of all stakeholders in a school building’s ecosystem falls on the shoulders of the school principals. Employing capable leaders in this role is vital yet many countries do not require candidates for the position to have special qualifications. In addition, training programs that do exist have been subject to much criticism. Recently, suggestions for reform have been implemented and this study explored a newly mandated school leader training program to assess its perceived effectiveness. This qualitative research study contributes a missing link to current research into educational leadership training programs world-wide which tends to focus on educational reforms in Canada, the United States and Australia. Twelve Hungarian school principals, or directors as they are termed in their native land, were interviewed for this research and asked to share their personal formal and informal pre-service preparation and training experiences. The directors were also asked to provide their opinions regarding the relative value of different components of their compulsory School Leaders’ Training program. Findings support the theories presented in existing literature regarding effective school leader training programs using methods specifically targeted toward adult learners and add to the call for mandatory school administrator training and preparation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".