The Making of a Champion Leader: Insights from the Diploma in Educational Leadership and Management Program in Uganda, West Nile Region
Bibliographic record
Abstract
Purpose: The purpose of this study was to examine the educational leadership development of 35 headteachers who participated in the Diploma in Educational Leadership and Management (DELM) program, a collaboration between Aga Khan University and Muni University under the Foundation for Learning (F4L) project. The study aimed to identify the professional development needs essential for enhancing leadership capacities in low-resource educational settings in Uganda. Methodology: We employed a mixed-methods approach using purposive sampling and transformational leadership theory as the framework. Quantitative data were collected through structured questionnaires capturing demographic characteristics, professional experiences, and participation in professional development. Qualitative data were obtained from semi-structured interviews, which were transcribed and thematically analyzed to explore the DELM program's impact on leadership practices. Findings: Findings revealed that DELM participants demonstrated significant alignment with transformational leadership principles, including improved communication skills, inclusive practices, and the ability to inspire professional development within their schools. The DELM program addressed critical gaps by equipping headteachers with practical skills in mentorship, gender sensitivity, and strategic succession planning. However, challenges such as resource limitations, resistance to change, and dual responsibilities highlighted the complexities of implementing these principles. Despite these hurdles, headteachers exhibited resilience and innovation, fostering collaborative, ethical leadership practices that promise lasting impact on school culture and student outcomes. Unique Contribution to Theory, Practice and Policy: Thus, we recommend for structured mentorship programs and succession planning to support the continued adoption of transformational leadership practices. Further, we recommend for continuous professional development opportunities tailored to the challenges of low-resource settings and policy interventions promoting leadership development. These measures will sustain and expand the impact of the DELM program, contributing to improved educational outcomes and broader leadership reforms in similar contexts.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".