Building, Supporting & Assuring Quality Professional Practice: A Research Study of Teacher Growth, Supervision, & Evaluation in Alberta
Notice bibliographique
Résumé
Alberta is considered among the world’s top performing education systems. Over the past two decades, the provincial education system has invested heavily in building teachers’ professional capital to ensure that the quality of teaching in Alberta is among the best in the world. A wealth of the educational reform research literature, at both international and provincial levels, suggests that continuous professional learning is key to building teachers’ professional capital. Within Alberta, the Teacher Growth, Supervision, and Evaluation Policy (TGSE) (Government of Alberta, 1998) guides that learning. In 2017, Alberta Education requested a comprehensive research study to inform an update to the existing policy, and to identify associated requirements for the growth, supervision, and evaluation of principals and superintendents. This research study provides an independent, objective examination of TGSE in Alberta school authorities and related policies at the school authority level. The purposes of the study were to provide education stakeholders and the Ministry with • an independent, objective review of the provincial TGSE Policy in Alberta and of related policies at the school authority level; • recommendations on how best to support implementation of any proposed changes to the TGSE policy; • recommendations on how the TGSE model should inform related policy on growth, supervision, and evaluation of principals; and • recommendations on how the TGSE model should inform related policy on growth, supervision, and evaluation of superintendents and school authority leaders. Research Design: The eight-member research team from the universities of Calgary, Lethbridge, and Alberta adopted a concurrent mixed methods research design to generate insights into educator experiences with and perspectives on teacher growth, supervision, and evaluation within the TGSE policy context. Our comprehensive analysis and merging of the study’s quantitative and qualitative data generated 14 merged findings and 10 recommendations. Quantitative data were generated from online surveys of 710 teachers, 131 principals, and 33 superintendents. Analysis of the survey data provided province-wide insights from a large population of educators in June and July of 2017. Qualitative data were gathered through multiple case study research during March to June of 2017. Members of the research team conducted individual and/or focus group interviews of teachers (n=64), principals (n=53), superintendents, and other system leaders (n=33) in seven randomly-selected school jurisdictions and selected charter and independent schools. Nine individual cases illustrated and illuminated practices through which teachers and leaders at the school and administrative levels engaged in teacher growth, supervision, and evaluation in their unique contexts. Our cross-case analysis identified 13 larger themes. Evidence was gathered in two additional ways: (a) through analysis of 30 randomly-selected school authority policies, and (b) through interviews of education partner organization leaders. The team also gathered evidence from documentary sources, artifacts, and field notes.
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 | 0,015 | 0,008 |
| 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 | 0,001 | 0,001 |
| 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) | 0,001 | 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 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 ».