A Framework for Embedding Learning in Systems Change - Bertermann, Kecia; Coffman, Julia (Center for Evaluation Innovation, 2024)
This five-step framework, developed and tested by a foundation, embeds learning in emergent systems change strategies. It prioritizes the testing of hypotheses and assumptions, uses learning questions, and calls for examining both confirming and disconfirming evidence. — A framework for embedding learning in systems change strategies and for testing strategic uncertainties. Learning and evaluation approaches that accompany systems change efforts need to fit with and support the emergent nature of this work. Systems change efforts call for examining, with evidence, the hypotheses and assumptions that undergird the work and regularly adapting in response to what is learned. They require staff to be highly engaged in testing their ideas by gathering evidence, interpreting it, and then acting on its implications. This brief presents a learning approach—referred to here as the Learning Framework—developed and tested by a foundation to support its systems change strategies. It is intended for other practitioners working on approaches for integrating learning with systems change efforts. Because a wealth of conceptual work exists about why learning is critical to systems change but practical advice about how to do it is much less available, we describe the approach we took and how the Framework’s core elements fit together in practice. The primary purpose of this approach is to interrogate our strategic uncertainties. This approach to learning is different from the dominant approach to learning and evaluation in philanthropy that primarily looks for evidence (often static metrics) that expected outcomes have been achieved (an approach that is more suitable for linear and predictable change strategies). This Learning Framework is driven by, and organized around, hypotheses and assumptions. This is especially important for systems change efforts where the path forward cannot be determined with complete certainty, but where robust evidence collection and regular sensemaking can increase our confidence in chosen directions and ultimately increase our chances of success.

Developing, representing, and using theories of change for interventions in complex systems - Rogers, Patricia (Theories of Change in Reality, 2024)
Theories of change for interventions in complex systems present a challenge for usual approaches to developing, representing, and using theories of change. Interventions in complex systems operate under conditions of ongoing uncertainty, not because of a lack of information but because of three features that contribute to this uncertainty: (1) numerous, diverse, and interacting components; (2) nonlinear relationships; and (3) changes brought about through self-organisation, agency, adaptation, and learning. In such situations, a different approach is needed to theories of change. Their primary intended use needs to be supporting ongoing single-loop and double-loop learning and adaptation by the various actors involved, rather than monitoring compliance with an initial plan. The underlying change theories need to be appropriate for managing complex systems—for example, focusing on developing an effective network of actors, creating an enabling environment, and supporting iterations of learning and adaptation rather than planning tightly prescribed implementation of ‘what works’.
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