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Over the past two decades, the role of data in international development has expanded rapidly. Policymakers, implementers, funders, and researchers are increasingly using data to make important decisions around resources and priorities. This coincides with the shift from a focus on outputs, such as Millennium Development Goal 2 of universal education attendance, to outcomes, such as Sustainable Development Goal (SDG) 4’s emphasis on the importance of learning. This focus on outcomes, coupled with increases in data literacy, is bringing a renewed focus to demonstrating and measuring the achievement of positive outcomes for the beneficiaries of social programs around the world.
At the Center for Universal Education (CUE), we have identified four types of data necessary for achieving outcomes, including data on the cost of action and inaction, final results data, and data along the way—or real-time performance data. If we are to achieve meaningful progress toward SDG 4 on education, real-time data are essential, and we must build systems of continuous measurement to ensure systematic collection, scrutiny, and usage of data. What are real-time data and how are they different?
The randomized controlled trial (RCT) movement, which gained momentum in the early 2000s, pushed for an increase in rigorous final […]