Components and Indicators of the Supervision Models for Developing Experiential Competency that Promote Life Skills for Early Childhood Teachers under the Office of the Basic Education Commission
Bibliographic record
Abstract
This research aimed to: 1) investigate the components and performance indicators for organizing experiential activities that foster life skills among early childhood students, particularly those taught by teachers under the Office of the Basic Education Commission of Thailand; 2) examine the current state, desired state, and the needs of supervision models for teachers to develop experiential competency that promotes life skills in early childhood students; and 3) enhance the supervision models for developing experiential competency, specifically focusing on promoting life skills among early childhood students taught by teachers under the Office of the Basic Education Commission of Thailand. The research is divided into 3 phrases. Phase 1: examine the components and indicators, targeting a qualified group of 9 experts selected through purposive sampling. This selection is based on the appropriateness assessment using the components and indicators evaluation form. Phase 2: investigate the needs of the supervision models. The sample group comprises 320 early childhood teachers, selected through multi-stage random sampling using a questionnaire with a 5-level Likert scale. Phase 3: developing the supervision models. Nine qualified experts selected through purposive sampling examined the appropriateness of the supervision models. The data were collected through questionnaires, interviews, assessments, and observations. Average, standard deviation and Priority Needs Index (PNImodified) were used to analyze the data. The findings of the study revealed the following: 1. The components and indicators of life skills serve as standards for teachers in organizing experiences that promote life skills for early childhood students. There are 5 components and 23 indicators, categorized as follows: 1) Decision-making with 5 indicators, 2) Problem-solving with 5 indicators, 3) Analytical thinking with 4 indicators, 4) Empathy with 4 indicators, and 5) Communication with 5 indicators. Overall, the proficiency level is rated as the highest. 2. The current state is rated as the highest, and the desired state is also at a high level. When assessing the needs of the supervision models, it is found that the component with the highest need is Component 3—Analytical Thinking. This is followed by Component 2—Problem-Solving, Component 4—Empathy, Component 1—Decision Making, and Component 5—Communication, with the lowest index of essential needs respectively. 3. The results of enhancing the supervision models for teachers to develop experiential competency that promotes life skills in early childhood students reveal that the supervision models encompasses five formats: 1) Preparation: Planning and development, 2) Strengthen Relationships and Increase Knowledge: Building relationships and expanding knowledge, 3) Knowledge into Practice: Applying knowledge into practice, 4) Reflection: Reflecting on outcomes for understanding, and 5) Evaluation: Quality measurement and assessment. These formats are deemed highly suitable, appropriate, and effective.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".