Giving Compass' Take:

• Brookings' Million Learning Real-time Scaling Labs project examines how education initiatives around the world are progressing and applies "improvement science," a form of adaptive learning, to do so.

• Starting with the assumption that scaling any ambitious project will not be easy, those in the education space should look at how the researchers for the scaling labs went about their work: They had to go deep into data and combat "solutionitis" (the urge to draw conclusions based on small sample sizes).

• Here are some platforms for scalable learning in the social sector.

A three-legged stool can be tough to balance if the legs are uneven. We’ve been thinking a lot about how to do just that with the launch of the Millions Learning Real-time Scaling Labs starting in Brazil, Jordan, Tanzania, Côte d’Ivoire, and the U.S. city of Philadelphia. How do we balance and give equal weight to our three primary objectives: learn from, document, and support education interventions in the process of scaling? We think that drawing from principles behind adaptive and iterative learning methodologies, such as improvement science, can help.

Our starting point with the scaling labs is to learn more about how effective education interventions expand and deepen their impact — what we refer to as scale — especially among some of the world’s most marginalized communities. The global education community is learning a lot about how best to scale, some of which is seen in our 2016 report Millions Learning: Scaling Up Quality Education in Developing Countries. But there is certainly a lot more to learn, particularly around the core drivers behind adapting an evidenced-based initiative to a new context as well as about the enabling conditions in the environment that allow for good ideas to take root and spread. Through the lab process, we hope to learn even more about this scaling as it unfolds in real-time.

Secondly, we hope to document this process so that we gain deeper insight into the scaling journey, not only to understand what outcomes are achieved but, just as importantly, to understand how they are achieved, and to be able to “tell the story of what happened” so that other decisionmakers can learn from it.

Read the full article about how improvement science helps assess education research by Jenny Perlman Robinson at Brookings.