Approaches to scaling innovations across schools: an analysis of key theories and models

Greany, Toby

Abstract

The question of how to scale up successful innovations remains a key challenge for policy and practice in education (Hall, 2013). This article outlines three established ‘schools of thought’ around how to scale up successful innovations. The first approach – eco-systems - is informed by complexity theory and tends to focus on generating and scaling innovations through diverse lateral networks which allow multiple stakeholders to collaborate (OECD, 2015). The second approach – ‘what works?’ – is interested in identifying effective practices through rigorous, scientific research and in replicating these proven practices across multiple schools with high degrees of fidelity. The third approach – Improvement Science - emphasises the importance of practitioner judgement and learning for interpreting and applying evidence across different contexts, but also recognises the importance of school-level cultures and wider factors, and so seeks to generate systematic forms of innovation, evaluation and improvement at scale (Bryk, 2015; Resnick, 2010). This article concludes by discussing the respective contributions of these models and the implications for policy, practice and research.

Citation

Greany, T. (2019). Approaches to scaling innovations across schools: an analysis of key theories and models. In R. Heraud, & M. A. Peters (Eds.), Encyclopaedia of Educational Innovation. Springer. https://doi.org/10.1007/978-981-13-2262-4_68-1

• Acceptance Date: Apr 6, 2019
• Online Publication Date: Sep 12, 2019
• Publication Date: 2019
• Deposit Date: Apr 8, 2019
• Publicly Available Date: Sep 13, 2021
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Book Title: Encyclopaedia of Educational Innovation
• DOI: https://doi.org/10.1007/978-981-13-2262-4_68-1
• Keywords: educational innovation; scaling up; educational improvement; educational change; schools
• Public URL: https://nottingham-repository.worktribe.com/output/1760533
• Publisher URL: https://link.springer.com/referenceworkentry/10.1007/978-981-13-2262-4_68-1
• Related Public URLs: https://meteor.springer.com/project/dashboard.jsf?id=813&tab=About&mode=ReadPage&entity=6074