The Study of Components Technology Leadership of Teachers in Public Art Education Management Take Nanning, Guangxi
Bibliographic record
Abstract
The objectives of this article were: 1) to investigate the components and indicators of Technology Leadership of Teachers in Public Art Education Management in Nanning; 2) to examine the current conditions, desired conditions, and the necessity for developing Technology Leadership of Teachers in Public Art Education Management in Nanning; and 3) to explore guidelines for fostering Technology Leadership of Teachers in Public Art Education Management in Nanning, Guangxi. The research sample comprised 7 participants. The study was divided into three steps: Step 1 involved examining the components and indicators, with qualified individuals evaluating their suitability. Step 2 entailed investigating the current situation using a multi-stage sampling method, with a sample group of 263 individuals. Step 3 focused on exploring guidelines for developing technology leadership among teachers, utilizing data from 6 individuals. Research tools included questionnaires, interviews, and assessments. Statistical analysis methods such as mean, standard deviation, and the analysis of necessary conditions (PNI modified) were employed for data interpretation. The research findings revealed that: 1) the components and indicators of technology leadership among teachers in educational management comprised 4 components and 40 indicators, namely: Technological vision with 10 indicators, Technological competence with 10 indicators, Technology professional development with 10 indicators, and Technology integration with 10 indicators, rated as highly appropriate overall. 2) The necessary requirements for developing technology leadership among teachers in educational management suggested the need for development across all components. 3) The guidelines for fostering technology leadership among teachers in educational management encompassed a total of 13 development strategies. The assessment of these strategies indicated a high level of appropriateness and feasibility.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".