Needs for Teacher Development of the Special Education Bureau Group 1 Based on the Concept of Facilitation Skills
Bibliographic record
Abstract
This research aims to study the needs for teacher development of the Special Education Bureau Group 1 based on the concept of facilitation skills. This is descriptive research. The research population included a group of Special Education Centers subsidiary to the Special Education Bureau. The information source Group 1 included 11 school directors and 16 school deputy directors, 27 in total, with purposive sampling used in the process. This also included 173 teachers with stratified sampling used. The total number of the population was 200. The research instrument used was a questionnaire on current conditions, desirable conditions, and the needs for teacher development of the Special Education Bureau Group 1 based on the concept of facilitation skills. Statistics used in data analysis were frequency, percentage, arithmetic mean, and standard deviation. According to the results, it was found that the needs for teacher development of the Special Education Bureau Group 1 based on the concept of facilitation skills were, in general, at a moderate level (M = 3.413, SD = 0.798). When considering each aspect of the needs for teacher development of the Special Education Bureau Group 1 based on the concept of facilitation skills, it was found that empowerment skills were most essential (PNIModified =0.376), followed by communication and conflict resolution skills (PNIModified =0.371), management skills (PNIModified =0.360), skills to create and sustain a participatory environment (PNIModified =0.344), and interpersonal skills (PNIModified =0.333).
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".