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Strengthening school leadership towards improved school resiliency: final technical report

2023· other· en· W7071588118 sur OpenAlexfundno aff

Notice bibliographique

RevueOpen Research Online (The Open University) · 2023
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesInternational Development Research Centre
Mots-clésQuality (philosophy)CurriculumEducational leadershipMultidisciplinary approachQuality managementSet (abstract data type)Exploratory researchNarrative
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

''Strengthening School Leadership Towards Improving School Resiliency” was a two-year interdisciplinary multi- country development research project exploring how the quality of school leadership could be strengthened as a means of improving education quality in under-resourced environments. The primary objective of the project was to understand whether use of a specific continuous improvement approach, Improvement Science (IS), supports sustainable change in the practices of school leaders. School leaders are acknowledged to have a critical role in improving the quality of teaching and learning within schools. Continuous improvement methods such as IS offer a set of ideas, tools, and practices which empower practitioners such as school leaders to take an active role in improvement, crafting a narrative which explains the improvement initiative and helping to remove obstacles and blockages in the improvement initiative, and other actions which move the institution towards its goals.
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\nThis exploratory multi-country research adopted a realistic evaluation (RE) framework to explore the use of IS with groups of school leaders in three contrasting contexts. The multidisciplinary research team collaborated with in-country partners across three continents: Chile – SUMMA (Laboratory of Education Research and Innovation for Latin America and the Caribbean); Kenya – Worldreader; the Philippines – FIT-ED (Foundation for Information Technology Education and Development). Despite the constraints of the COVID-19 pandemic in each setting, school leaders were recruited and improvement communities were established and guided to engage with the IS methodology through carrying out “Plan-Do-Study-Act” (PDSA) cycles on local challenges. Data was gathered on the experiences of the school leaders through their improvement science journeys using a range of qualitative research instruments including records of the PDSA activities.
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\nThe project offers a contribution to knowledge by offering emerging findings on how an amended IS methodology might be effectively utilized by school leaders working in under-resourced contexts. To date, there has been little utilization of the Improvement Science approach in low- or medium-income contexts; relevant prior research has all been undertaken in high-income contexts. Our analysis revealed that there can be clear benefits for schools when school leaders engage with the IS approach: changes in institutional practices, attitudes, and relationships are noted when conditions are favorable. The findings draw attention to the importance of the school leader improvement communities. They enable school leaders to develop a broader vision on their work and strengthen potential for further collaborations towards common goals. These are values and behaviors which support implementation of a continuous improvement approach.
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\nOur recommendations identify a number of issues for consideration in further research and implementation of the IS approach. Specifically, it is important to encourage school leaders to embrace continuous improvement as a core part of their leadership role. This may require changes in how school leaders enact their role. Practices such as team working, more consideration of different forms of data, and active experimentation are required for successful use of the IS approach. In addition, the IS approach will only be useful with particular kinds of problems. It needs to be used for small-scale change and improvements; it is not appropriate for tackling large or complex problems. From a development perspective, the use of IS methodology in education appears to offer the potential to shift towards more equitable dialogue between education partners when problem solving. It supports movement away from implementation of external “what works” solutions in schools and towards a legitimizing of the use of locally-driven small changes or adaptations that respond to highly specific local conditions and capabilities. It moves discussion from “this isn’t being implemented properly or with sufficient intensity” to “is this the most appropriate change for my institution?” The sharing of these local improvements with peers and other actors starts to point towards ways in which school leader collaboration could be harnessed for improvements in the quality of local education provision, in particular pedagogic change.
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\nThis research was undertaken in the highly fluid and dynamic environments of the pandemic; when rules and expectations were constantly shifting, and project partners (development practitioners, school leaders, and researchers) were experiencing the impact of COVID-19 in different ways. This led to a number of challenges and consequent changes in ways of working. For example, local authority stakeholders had reduced capacity to engage with the project, organizing meetings with the school leaders was difficult at times, and the IS approach required multiple team members to move outside their usual roles to become more enabling and less solution-focused.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,009
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies, Communication savante, Science ouverte, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesScience ouverte, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0120,009
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0040,011
Études des sciences et des technologies0,0020,002
Communication savante0,0030,002
Science ouverte0,0270,026
Intégrité de la recherche0,0010,007
Charge utile insuffisante (le modèle a refusé de juger)0,0180,016

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.

Tête enseignante Opus0,324
Tête enseignante GPT0,431
Écart entre enseignants0,107 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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