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A large and growing body of evidence identifies the types of reforms and programs that can improve foundational learning outcomes at scale.
But knowing what needs to be done is not enough. Systems need to learn how to make these changes, and how to make them in ways that diffuse down through to tens of thousands of schools to reach hundreds of thousands of teachers and millions of their students. Well designed plans are only the first step. Once administrators and teachers begin to put plans into action they can meet technical, resource, administrative and political constraints that throw them off course. Especially when done at scale, in low-capacity settings.
To succeed, education systems leaders must learn how to navigate, adapt, and iterate through these challenges so that programs lead to the changes we want to see in how systems operate – and ultimately to teacher-student interactions in classrooms.
In many cases these challenges inhibit large investments in foundational learning from achieving results. The Implementation Science for Education program (ISE), launched in mid-2024, embeds implementation science research in World Bank financed operations, and uses it to support delivery of learning reforms at scale. With support from the Foundational Learning Compact Multi- Donor Trust Fund and in partnership with the FCDO What Works Hub, the program awards grants and provides complementary technical support to embed implementation science research in these activities.
In this presentation we will share the ISE approach to embedding implementation research in government programs financed by World Bank operations. We will share examples of implementation challenges being investigated in our first cohort of projects. These include, leveraging coaches to improve uptake of differentiated learning in Ghana, deploying a remedial instruction curriculum in Rwanda, and using tablets to improve uptake of structured pedagogy in Nigeria. We will also discuss the types of measurement tools being deployed, and how the projects are leveraging insights from both quantitative and qualitative to iterate and improve.