Research on the interplay between preschool teachers’ dispositions, practice and children’s learning in block play
Notice bibliographique
Résumé
Previous research has shown the importance of early science, technology, engineering, and math education for children’s knowledge, as it establishes a groundwork for their later learning and academic achievement. However, the engagement of preschool teachers especially in science learning activities is infrequent, and some teachers still pronounce the belief that science education is inappropriate for the early childhood years. Furthermore, there is a lack of clarity regarding the connections between teachers' attitudes (including their knowledge, beliefs, and willingness) towards teaching early science and their actual teaching practice, as well as the subsequent effects of teacher practice on children's learning outcomes. This dissertation primarily aims to clarify these associations. Block play offers the possibility to link scientific concepts (e.g., stability) to children’s everyday activities and thus represents an age-appropriate way to examine young children’s STEM-learning. The present dissertation encompasses three research articles, focusing specifically on the interplay between preschool teachers’ dispositions and practice in block play and 4- to 6-year old children’s knowledge. The first article focused on the validation of a self-developed instrument to assess preschool teachers’ willingness to engage in science teaching and examined the predictive power of teachers’ willingness for teachers’ practice. Results suggested that the instrument measured teachers’ willingness reliably and validly, however, teachers’ willingness did not predict their practice in block play. The second article examined the relationship between the preschool teachers’ instructional quality during block play and various aspects of children's knowledge. Specifically, the study explored how instructional quality in block play influenced children's knowledge in stability, math, and spatial language. Additionally, children’s academic self-concept and cognitive aspects (i.e., intelligence, working memory) were considered. Results implied that preschool teachers’ scaffolding activities were related to children’s stability knowledge in block play. Moreover, teachers’ instructional quality was positively correlated with children’s academic self-concept in block play. The primary focus of the third article was on implementing a block play curriculum. Therefore, study 3 employed a longitudinal design to assess the effectiveness of a teacher training on teachers’ practice with the curriculum, which included both, guided and free play. Teachers were randomly assigned to either a control group or an experimental group. The experimental groups received training with the block play curriculum, while the control group did not receive any training. Results showed no change in teachers’ knowledge before and after training. Nonetheless, teachers in the experimental group applied more scaffolding after the training. Furthermore, preschool teachers applied more scaffolding during guided than during free play. Children’s math score in the experimental group, but not in the control group, significantly improved from pre- to post-test. In the general discussion, the findings of the three articles are reflected in the light of the interplay between teachers’ dispositions and their teaching practice as well as the impact of teacher practice on children’s knowledge. Besides, the discussion reflects on methodological difficulties of empirical studies in early childcare settings, providing a prospective view on multimethod approaches for future research. Taken together, the present dissertation contributes to a more profound understanding of how teacher practices and children's knowledge interact. Further, the research holds great relevance for practical application as it illustrates the differential effects of teacher training on preschool teachers’ knowledge and their teaching practice.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».