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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».