The Community-based Institutional Administration Model to Promote Students’ Career Skills in Chiang Mai Education Sandbox, Thailand
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The research objectives were shown as follows: 1) to research the community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox, 2) to design the community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox, 3) to experiment the community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox, and 4) to develop the community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox by using research and development method. The samples of this study were 1) 9 basic education commissions, 2) 8 teachers and educational personnel, 3) 15 community leaders, monks, local wise men, and villagers, 4) 7 educational experts, and 5) 28 students, which in total were 67 people. The tools used in this study were as follows: 1) structured interview form, 2) community-based institutional administration model assessment form, 3) satisfaction assessment form, and 4) group discussion record form. Qualitative data were analyzed using Content Analysis and presented in a descriptive form (Descriptive Analysis), and quantitative data were analyzed using a statistical program to determine the mean and standard deviation. The result showed as follows:1) A community-based institutional administration model for promoting students’ career skills in the Chiang Mai education sandbox must be an educational management in an area with spatial diversity. School administrators and teachers must provide great cooperation and interest in participating in the development of the school by following the guidelines of the education sandbox. Furthermore, piloting basic learning activities that involved community areas and the area surrounding a community that is rich in natural resources and the environment was essential. This was the significant strength point that allowed us to develop a community-based institutional administration model more effectively.; 2) A community-based institutional administration model for promoting students’ career skills in the Chiang Mai education sandbox had an institution management strategy called the "4K Model," consisting of four strategies as follows: 1) Strategy 1 Knowingly: K1 Knowingly situations in the world, 2) Strategy 2 Keep Step: K2 Keep moving steps forward together, 3) Strategy 3 Knowledge: K3 Transferring knowledge from the community, and 4) Strategy 4 Kit out: K4 Sourcing support resources.; 3) Using the community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox, it was found that the overall level of satisfaction in both teachers and educational personnel, and students towards the use of this model was at the highest level.; 4) The community-based institutional administration model to promote students’ career skills in the Chiang Mai education sandbox that the researcher had developed to be more complete was under these five strategies as follows: 1) Strategy 1 Knowingly: K1 Knowingly situations in the world, 2) Strategy 2 Keep Step: K2 Keep moving steps forward together, 3) Strategy 3 Knowledge: K3 Transferring knowledge from the community, 4) Strategy 4 Kit out: K4 Sourcing support resources and 5) Strategy 5 Key success: K5 Key success. It was also found that there was a mechanism that supported this model, consisting of four mechanisms as follows: 1) policy mechanism, 2) academic cooperation building, 3) collaborative vision building, and 4) network party.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 découle