Teaching Approach and Teacher Self-Efficacy during Early Childhood Distance Learning
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Notice bibliographique
Résumé
Child Distance Learning (CDL) during the pandemic has led to an optimal development of children and effective teaching and learning processes in kindergartens. To overcome this, teachers need to apply a teaching approach in accordance with the principles of kindergarten education. In addition, teachers' self-efficacy of their ability to teach is also important for developing children's skills. This study aims to describe the teaching approach and the efficacy of kindergarten teachers during the CDL process and to identify the relationship between the two. The research method used is quantitative through document analysis as a source of data findings. A total of 116 Public Kindergarten (PK) teachers in DKI Jakarta participated in filling out the Classroom Management Scale and Teachers' Sense of Efficacy Scale online. All data were processed using descriptive statistics and correlation. Furthermore, there is a document analysis carried out on the Daily / Weekly Learning Program Design in PK Jakarta. The findings identified that the teaching approach of kindergarten teachers during CDL included only two principles of kindergarten education, namely thematic teaching and developing life skills. Furthermore, PK teachers in the Jakarta area showed low self-efficacy during CDL. The teaching approach and self-efficacy were caused by teachers' unpreparedness in facing challenges during CDL. In addition, other findings indicate that there is a relationship between teaching approaches and teacher self-efficacy. Another CDL model Interventions to increase teacher self-efficacy and the extent to which the relationship between the two variables can be studied further in future studies.
 Keywords: Early Childhood, Distance Learning, Teaching Approach, Teacher Self-Efficacy
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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 | 0,001 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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