Development of Academic Leadership Competency Model of Elementary School Teachers in Rural Area in Hubei Province
Bibliographic record
Abstract
This study focused on elementary school teachers in rural area in Hubei Province, aiming to study the key components of academic leadership, to investigate the current state, ideal state, and the needs of academic leadership, to develop and verify the effectiveness of the model for enhancing academic leadership, and to investigate the results of implementing the model for enhancing academic leadership. The research was divided into four phases. The first phase examined key components of performance indicators of elementary school teachers in rural area in Hubei Province through a literature review and conducted semi-structured interviews with experts. The second phase investigated the current state, the ideal state, and the needs of academic leadership. The samples consisted of 320 teachers from elementary school in rural area in Hubei Province, selected through stratified random sampling. In the third phase, the model for enhancing academic leadership was developed through best practice interviews, and the manual was written. This model and manual were verified by nine experts in terms of possibility, appropriacy, accuracy, comprehensiveness, and usability. Moreover, the fourth phase implemented the model for enhancing academic leadership of elementary school teachers in rural area in Hubei Province with 30 teachers, selected through purposive sampling. The assessment of academic leadership of teachers was conducted using a pre-test and a post-test for assessing knowledge, and using evaluation forms for assessing the skill of the academic leadership and satisfaction. The results were as follows: 1) The results identified three key components of academic leadership which consisted of teaching leadership, charismatic leadership, and team leadership. 2) The overall current state was at a moderate level; the ideal state was at a high level. The needs analysis highlighted teaching leadership as the most needed, while the analysis indicated that charismatic leadership was the least needed. 3) The development of the model for enhancing academic leadership included five parts: Part 1 was the lead section; Part 2 was structural drafting; Part 3 was experimental implementation to compare implementation results; Part 4 was evaluation; and Part 5 was success conditions. The overall quality assessment of the model was at a high level. 4) The results of implementation of the model for enhancing academic leadership indicated that there was a statistically significant difference in terms of knowledge. A comparison of pre-test and post-test scores revealed a higher average score after the training. In terms of the skills of the academic leadership, teachers self-assessed their skills at a high level, while their administrator assessed the teachers’ skills at the highest level. Regarding satisfaction, teachers expressed the highest level of satisfaction towards the training.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".