An Innovative Leadership Model for School Administrators to Enhance Instructional Quality in Secondary Educational Service Area Offices in Northeast Thailand
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 aimed to develop an innovative leadership model for school administrators to enhance the quality of instructional management among teachers within Secondary Educational Service Area Offices in Northeast Thailand. The study employed a research and development (R&D) methodology conducted in two phases. Phase 1 investigated current conditions and components of innovative leadership for enhancing instructional management quality. Research instruments included a five-point Likert scale questionnaire and semi-structured interviews. The sample consisted of 478 school administrators and teachers selected through stratified random sampling, based on Krejcie and Morgan’s (1970) sample size determination table. Additionally, three school administrators recognized for exemplary practices were selected through purposive sampling for in-depth interviews. Data were analyzed using descriptive statistics (mean, percentage, and standard deviation), Exploratory Factor Analysis (EFA), and content analysis. Results showed that overall, innovative leadership was at a moderate level. EFA identified four components with initial eigenvalues greater than 1, explaining 79.67% of cumulative variance: (1) Creating an Innovative Vision, (2) Developing Leadership and Innovative Culture, (3) Creative Innovation Thinking, and (4) Utilizing Digital Technology for Innovative Instructional Management. Phase 2 involved developing the innovative leadership model to enhance instructional quality. Twelve experts validated the model through a peer review process. The model consisted of five key elements: principles, objectives, implementation methods (covering four dimensions: innovative vision, innovative organizational culture, creative innovation thinking, and digital technology utilization), model evaluation guidelines, and conditions for success. Overall suitability and feasibility of the model were rated at the highest level.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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