DEVELOPMENT PROGRAM FOR SECONDARY SCHOOL HEADS
Bibliographic record
Abstract
School heads are the key leaders in the educational system, and they are responsible of carrying out the school’s vision and mission and play integral roles in making schools function smoothly. They are involved in all aspects of the school’s operation. This study developed and validated a development program for secondary school heads based on the competencies outlined in the seven domains of the National Competency-Based Standards for School Heads (NCBSSH). The research aimed to determine the extent of implementation of these competencies, explore the significant differences in evaluations by school heads and their teachers regarding the implementation, and assess the seriousness of problems related to the seven domains of NCBSSH. The Research and Development (R&D) method was employed to design the development program, which served as the study's output. Survey results indicated that the competencies under the seven domains were "sometimes" implemented by secondary school heads. Moreover, t-test results revealed a very significant difference between the self-evaluations of school heads and the evaluations made by key teachers. The Development Program was found to be acceptable in terms of its objectives, activities/strategies, persons involved, time frame, budgetary requirements, and success indicators. The study proposes the utilization and implementation of the development program to enhance the competencies of school heads.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".