This session, recorded at the Carnegie Summit in 2021, introduces the Evidence for Improvement Framework. The Framework illustrates how improvement networks can be conceptualized and measured using a three-level nested model composed of (1) a working theory of improvement towards achieving their aim, (2) an improvement enterprise that functions as a scientific learning community, and (3) environmental contexts that may constrain or enable improvement efforts.
Improvement networks, by design, are focused on developing and testing changes based upon theories of improvement (and providing for the spread of those changes that demonstrate merit and potential). All this is based upon practical evidence brought forth from rigorous disciplined inquiry. To succeed, networks must learn quickly by continuously adapting to changing circumstances within their organizations and the broader environment. In this workshop, participants are introduced to the Evidence for Improvement framework, an integrated approach to analytic support for improvement networks in education. Drawing on several evaluative practices, the EFI framework represents the complexity of network learning through a three-level nested model that illustrates work related to a network’s working theory of improvement, improvement enterprise, and environmental contexts. Participants learn how to use the EFI framework to align evaluative expertise to advance productive learning.
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