The Needs of Evaluation in the Field of Early Childhood Development from the Early Learning and Childcare Educators' Perspective
Notice bibliographique
Résumé
Early childhood development (ECD) is an intersectoral and interdisciplinary field as it includes many sectors and programs that serve children from conception to six years of age. This life period is the foundation for human development. Therefore, positive early experiences set the path for adulthood in terms of education, economic stability, and health and wellbeing. In 2015, Canada committed to the United Nations’ 2030 agenda of Sustainable Development Goals (SDGs). The federal government is funding innovative initiatives that raise awareness around SDGs. Particularly, it is giving significant attention to enhancing early childhood experiences in Canada due to its importance in achieving the SDGs. However, there are still areas in this field that call for improvement. Evaluation is one way to identify those areas and learn how this field can be enhanced, but there are gaps in doing and using evaluation in this field. Therefore, it was important to understand the evaluation assets and needs in the ECD field. Understanding evaluation capacity assets and needs requires learning from stakeholders that are involved in this field. The Evaluation Capacity Network (ECN) conducted a study in 2021 to understand those needs and assets in ECD and to learn how it can effectively tailor its support in building the evaluation capacity of organizations and individuals. This thesis research builds on the ECN’s study to learn about the field’s capacity and context, and while this field is intersectoral, the thesis research focused on early learning and childcare (ELCC) as a subsection. ELCC is an important sector as it is where Canadian children spend most of their time when interacting with people other than the family. Among the diverse stakeholders in ELCC, this research focused on ELCC educators in Alberta, Canada. The research used qualitative methodology and drew on two data sources. Secondary data from five focus groups conducted by the ECN with ECD stakeholders in North America were used to reflect the field’s capacity at the organizational and system levels. This was followed by seven semi-structured interviews with ELCC educators in Alberta to reflect their individual capacity needs and assets to engage in evaluation. The findings revealed that educators have a unique evaluation capacity due to their natural evaluation practice with children that is embedded in their day-to-day work and interaction with children. Their natural evaluation practice makes the quality of their evaluation vary from one another based on their experiences. This research suggests that educators need evaluation capacity building at individual, organizational, and system levels. It is significant, however, to consider how educators define evaluation and the contexts in which they work to tailor evaluation capacity building opportunities more meaningfully. Improving educators’ evaluation capacity will ultimately enhance the collection of baseline data about children in the province that is currently lacking and ensure more coherent evaluation in the system to determine if significant funds and initiatives are making change.
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 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 | 0,001 |
| 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 | 0,000 | 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 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 ».