School Leadership in Times of Change: Analyzing Principals' Competencies in Implementing Vietnam’s 2018 General Education Curriculum
Bibliographic record
Abstract
Introduction: School principals are critical in leading educational change, yet research on their change management competencies in Vietnam remains limited. This study examines principals' abilities to implement the 2018 General Education Curriculum reform, identifying key competencies and challenges. Methods: A mixed-methods approach was employed, surveying 240 principals from primary, lower secondary, and upper secondary schools across four Vietnamese regions. Data were collected using the Educational Change Implementation Questionnaire (ECIQ) and analyzed using descriptive statistics in SPSS. Results: Principals exhibit strong awareness of external change drivers, such as policy mandates and socio-economic factors, but limited recognition of internal factors like innovation and technology integration. Strategic planning is underutilized, perceived mainly as time management rather than a transformative tool. While forecasting competencies are moderate, resource management and adaptive planning remain weak. Discussion: The study highlights a reactive approach to change, with principals prioritizing policy compliance over internal reform. Gaps in strategic planning and leadership suggest a need for targeted professional development in change management and resource allocation. Addressing these deficiencies is vital for effective reform implementation. Conclusion: Strengthening leadership training programs is essential to equip principals with skills for sustainable educational reform. Enhancing their change management competencies through structured professional development can improve long-term curriculum reform success.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".