Achieving Learning Regulation Support: How a Socially Shared Approach Fits, Functions, and Thrives
Notice bibliographique
Résumé
Across three studies, the purpose of this dissertation was to explore how socially shared learning regulation (SSLR) “fits” as a suitable solution to the lack of learning regulation support in Ontario, “functions” to support teachers’ professional learning and students’ independence, and best “thrives” among teacher implementers who face a range of constraints. Three different research methodologies were used with the overall goal of providing guidance to educators and researchers regarding the use of socially shared learning regulation as a classroom teaching approach. In Study 1, data gathered from 50 key Ontario Ministry of Education (MOE) documents were analysed to measure the alignment between SSLR and the practices and mandates that are prescribed as guidance for educators in Ontario; considerable “fit” between the MOE publications and the central tenants of SSLR was discovered. Especially within these areas of fit, a lack of pedagogical specificity for educators was both apparent and remarked upon by the documents themselves. These seem as though they could be addressed, at least partly, through the use of SSLR. In Study 2, a qualitative interview method was used to explore the way an SSLR pedagogy may “function” to support teachers’ pedagogical learning, personal learning regulation development, and student independence. A second researcher was heavily involved in the recruiting, interviewing, transcribing, and coding for this study to supply greater objectivity and place the first researcher at an arms-length from a topic in which she had a vested interest. In this study, a wide range of pedagogical learning resulting from teachers’ use of SSLR was revealed, as well as an epistemological shift in the way teachers viewed their students as learners. In Study 3, a mixed methods approach was used to gather descriptive information about the types of enablers and constraints faced by teachers as they attempted to engage in SSLR – a brand new pedagogical approach for most. Survey and short answer data was collected over 3 months and 3 timepoints from 81 kindergarten to Grade 8 teachers who were genuinely dissatisfied by their status quo practices, ready for change, and largely eager to implement the novel teaching approach presented to them. Building on established theories of planned change implementation, the findings of this study indicated a minimal effect of teachers' approval of the intervention on implementation. Rather, specific drivers to the implementation of complex, communal pedagogical interventions included the support of high-status supervisors and peers, while constraints to implementation included fears regarding management of student behavior.
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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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».