The Learning Leadership of School Administrators to Enhance the Quality of Education in Ubon Ratchathani Primary Educational Service Area Office 3
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research examined learning leadership among school administrators for educational quality development in Ubon Ratchathani Primary Educational Service Area Office 3. The study aimed to: 1) assess learning leadership levels, 2) compare levels by position, work experience, and school size, and 3) identify development approaches. The sample included 323 administrators and teachers, with 6 participants selected for qualitative interviews through purposive sampling. A 5-point Likert scale questionnaire (reliability = .97) and structured interviews were used. Data analysis employed descriptive statistics, t-tests, F-tests, and Scheffe’s post-hoc tests. Findings indicated the learning leadership was at a high level overall. Significant differences (p < .01) were found across position, experience, and school size. Five development approaches were identified: 1) Team Learning—establishing shared objectives and promoting collaborative communication through technology; 2) Technology Utilization—developing technological skills and integrating technology in administration and learning management; 3) Creativity—fostering creative environments and supporting innovative teaching methods; 4) Learning-Conducive Environment—implementing participatory management, allocating resources, and developing safe learning spaces; and 5) Learning Innovation Development—promoting innovation application in learning processes and educational administration to enhance quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it