Do Strategic Leadership and Self Efficacy Among School Leaders Make a Difference?
Bibliographic record
Abstract
The main purpose of the study is to investigate if there is any significant relationship between Strategic Leadership Characteristics of Maldivian school leaders and their Leadership Self-efficacy. The study employed a survey approach and the data were collected using an adapted seven point Likert scale survey questionnaire. Data were collected from 23 schools in the capital city Male’, Republic of Maldives. A total of 200 school leaders (45 males and 155 females) participated in the study. The data were analyzed using descriptive statistics, Pearson product-moment correlation and Structural Equation Modeling. The findings of the study revealed that the school leaders in Male’ possessed all nine characteristics of strategic leadership. It also indicated that school leaders’ in Male’ have quite a bit of control in their roles as school leaders, revealing a high perception level of self-efficacy. Moreover, the results of the correlation analysis and examination of path analysis indicated that there was statistically significant and positive relationship between Strategic Leadership Characteristics of Maldivian school leaders and their Leadership Self-efficacy. The present study provides a starting-point for further exploring the strategic leadership qualities and self-efficacy of school leaders which are vital to bring a positive reform in schools. This study highlights that executing strategic leadership is essential to deal with both the need for sustainable change. It further indicates that both self-efficacy and strategic leadership are important to school leaders’ as they affect performance of the leaders through different mechanisms. Keywords: Strategic leadership; leadership self efficacy; Maldives school leaders; structural equation modeling.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".