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How to Use Theory of Change for Adaptive Monitoring, Evaluation and Learning
In my previous post on designing and implementing adaptive MEL frameworks , I discussed the importance of a program’s Theory of Change (TOC) in facilitating understanding among your team and your stakeholders on what change looks like. The biggest challenge facing most programs, however, is that TOC is often mistaken for another form or version of a results chain/log frame/results framework. While they are not mutually exclusive, they are not the same. The important distinction is that the TOC needs to iterate the theory behind the change you are seeking to enable, not just the process. The process is iterated in a results chain that specifies the tangible results you are pursuing driven by the theory. In an adaptive program, your results chain (i.e.: activities and outputs) can change depending on the initial results you are observing and the reflections that are being undertaken about what should happen next. The ‘what comes next’ reflections need to be based on something, and
Implementing an Adaptive Monitoring Framework: Principles and Good Practice
*This is an adapted version of an article I drafted for the SIAP SIAGA program, which can be found here . In 2019, I began working on a program that set itself the challenge of implementing a systems change, adaptive approach in order to leverage the results of previous programs in that sector, as well as to take into account the increasing complexity of development programming in a middle-income country. This type of program required a different type of monitoring framework – one that could capture changes in the system based on the results of the program, as well as be adaptive to the adjustments in program implementation over time. With adaptive monitoring still in its infancy (in practice, despite the plethora of theoretical information available on line), there were few practical experiences and good practices to draw on to facilitate the design of the monitoring, evaluation and learning (MEL) framework. There were more resources on monitoring systems change, but as with any pr
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