Educational systems have long had trouble ensuring that all students experience ambitious instructional approaches characterized by problem-solving, critical thinking, and student-directed learning. Existing scholarship has helped us understand the challenges of scaling ambitious instruction, conceptualize scale, and see how deeper learning can be promoted under the right conditions. However, existing research has had limited practical utility for educators. In work funded by the William & Flora Hewlett Foundation, the Carnegie Foundation for the Advancement of Teaching, a collection of 10 research-practice partnerships (RPPs), and a group of expert scholars are seeking to address this gap by developing and scaling interventions that foster deeper learning in schools and districts. To this end, we have produced a set of frameworks designed to assist educational leaders in making concrete improvements that advance deeper learning instruction at scale.
These three papers arise out of the work in which the Carnegie Foundation convened three study teams consisting of members of the RPPs and external experts with relevant expertise. The study teams each pursued one of three key questions at the core of advancing deeper learning through RPPs:
- What are key design considerations for interventions aimed at fostering deeper learning instruction equitably?
- How can RPPs be productively organized to support such practice improvements?
- Through which processes can deeper learning practices scale?
To pursue these questions, the study teams drew on extant scholarship and materials about each RPP developed by the Carnegie Foundation, including briefs on original grant proposals and qualitative portraits of each RPP based upon 10–12 interviews and RPP documents. Between 2019–21, each study teams met twice annually to exchange drafts and receive feedback. They also had repeated opportunities to listen and learn from RPP presentations and cross-partnership consultancies during twice annual convenings of the 10 partnerships.
Existing research on scaling ambitious instruction has had limited value for practitioners. The field of quality improvement from healthcare and industry is instructive in this regard because it has created many frameworks that are explicitly designed to support improved decision-making among practitioners. Drawing inspiration from such practically oriented frameworks, these papers are squarely targeted at informing concrete improvements in educational practice. They also speak to the scope of the ambition and the depth of the challenge of bringing about deeper learning equitably at scale in schools and districts whose practices are generally far from it.
Three Frameworks to Guide Action
Paper #1: Designing for Deeper Learning: Challenges in Schools and School Districts Serving Communities Disadvantaged by the Educational System
Imagine a team of designers who want to advance deeper learning in districts and schools serving communities disadvantaged by the educational system. To achieve this, the design team needs to decide which design features (e.g., activities, materials, programs, artifacts) to include in their intended intervention.
This paper aims to map the depth of such a design challenge by illuminating the spectrum of tasks to be addressed and identifying trade-offs to wrestle with. The design task matrix facilitates a view of the systemic complexity of advancing deeper learning. For research partners, the paper reveals important conceptual terrain beyond their areas of specialization and how to translate research ideas into more concrete design tasks. For practitioners or development partners, the paper offers research-based knowledge that can deepen thinking and reveal design tasks that they may have overlooked.
Paper #2: Partnering to Scale Instructional Improvement: A Framework for Organizing Research-Practice Partnerships
Research-Practice Partnerships are a promising strategy for bringing together diverse expertise to tackle the complexity involved in developing interventions and relevant know-how to accomplish large-scale change. However, forming long-term, trusting collaborations presents unique challenges, and there are few guides available to help navigate these challenges.
In this paper, the authors present a framework for partnerships seeking to improve instruction at scale. Our aim with this framework is to guide researchers and funders of RPPs, as well as those seeking to engage in trusting and productive partnerships, as they learn their way into better solutions.
Paper #3: A Framework for Scaling for Equity
For decades, researchers, educators, and the philanthropic community have wrestled with how to scale up promising pockets of reform. Today, in the wake of a national reckoning with race-based injustice, ideas about what it means to be at scale and how to get there continue to evolve. There is a growing recognition that our education system perpetuates inequity by design. For those interested in scale, this reckoning means moving beyond the idea that scaling work is, ipso facto, equity work simply because there is a goal to reach every student. Centering equity in scaling means prioritizing students who have historically been farthest from powerful learning opportunities.
Drawing on information from the 10 RPPs, this paper specifies a practice-derived framework for scaling for equity. In addition to advancing a scholarly understanding of scale, the Framework—complete with a six-tool Navigator—helps teams see what adaptations are needed to the innovation or scaling strategies, as well as to the system in question in order to achieve outcomes equitably and reliably at scale.
May 17, 2022
Carnegie Board Chair Diane Tavenner and President Tim Knowles discuss how technology and personal relationships can be combined to create a resilient learning community and why the Carnegie Unit must be reconsidered to stay effective and relevant.
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This series of blog posts presents resources for educators from the 2021 Summit on Improvement in Education (and elsewhere). This is the first blog post focusing on leadership.