Critique of Research Methodologies and Methods in Educational Leadership
Bibliographic record
Abstract
The purpose of this exploratory study was to document aspects of research methodology in educational leadership directed at emerging school leaders and the academic community that supports them. The intricacy of educational challenges highlights the necessity for a thorough investigation, the results of which will inform suitable reforms. Scholars have long argued about which of the qualitative and quantitative approaches is more rigorous in its contribution to the development of education. Some academics contend that since education focuses primarily on human behaviour, which is value-laden, research in this area should take a qualitative approach. Results indicate that while qualitative methods were more common in the arts, quantitative methods dominated research in education and the sciences. However, the social sciences frequently used a blend of qualitative and mixed approaches. The findings' implications for improving research methodology skills and the integrity of educational research are examined.
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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 | 0.725 | 0.750 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.011 | 0.090 |
| Scholarly communication | 0.030 | 0.021 |
| Open science | 0.012 | 0.015 |
| Research integrity | 0.011 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".