Centre for Excellence and Development Impact and Learning
The Centre of Excellence for Development Impact and Learning (CEDIL) was established in 2017 through funding from UK’s Foreign, Commonwealth & Development Office. Its primary objectives are to:
- Develop and test innovative methods for evaluation and evidence synthesis in international development contexts
- Build the evidence base on research uptake and use in decision-making
To deliver these goals, CEDIL is commissioning a £10 million research portfolio of primary evaluations, secondary data analysis, evidence synthesis and exploratory projects. These projects will focus on three thematic areas:
- Evaluating complex interventions: The Centre seeks to strengthen methods to evaluate complex, multi-component interventions and improve theoretical understanding of causal chains that explain how and why combinations of activities work.
- Enhancing evidence transferability: The Centre will develop and test middle-range theories to explain how programmes work in a plurality of contexts and how interventions can be designed and adapted to novel contexts.
- Increasing evidence use: The Centre aims to rigorously assess three areas of research uptake – stakeholder engagement, making sense of evidence and communication methods – and will develop guidelines for policymakers on using evidence from multiple sources.
In addition, the Centre’s Directorate will undertake evidence synthesis and outreach activities to maximise learning from its research and ensure uptake.
New CEDIL methods working paper and brief on middle-level theory
CEDIL’s new methods working paper, Making predictions of programme success more reliable, provides an account of a type of detailed theory of change called a ‘causal–process–tracing theory of change’ that can be very helpful for programme prediction, planning and evaluation. A new CEDIL brief based on this paper takes a practical, how-to approach in outlining ten steps for building a middle-level theory of change.
View the methods working paper: Making predictions of programme success more reliable
View the methods brief: Using mid-level theory to improve programme and evaluation design