Implementation as distributed sensemaking and adaptation: Understanding how an interest-driven STEAM learning environment maintains integrity across diverse contexts

Background Much of learning sciences research focuses on the design of learning innovations. However, curricula developed by learning scientists are seldomly widely adopted. One reason is that scaling programs beyond local, carefully tended contexts is difficult and is often unsuccessful. This problem suggests a need for research aimed at understanding how learning innovations scale beyond initial implementations.Methods We take a distributed sensemaking approach to analyzing the micro-level processes through which actors make sense of and align themselves with new programs. We examine one learning innovation, FUSE Studios, an integrated suite of STEAM (science, technology, engineering, arts, and math) learning activities, which has spread from two afterschool implementations to over 250, primarily in-school implementations. We present an analysis of classroom video and interviews with students and teachers from 17 focal schools, including a detailed case analysis of one school.Findings Our findings demonstrate how distributed sensemaking and adaptation among networks of humans and non-humans shaped local implementations and how, despite local adaptations, the program was able to maintain integrity of implementation, delivering similar experiences to students across contexts.Contribution These findings improve our understanding of how learning innovations scale and demonstrate the value of a distributed sensemaking perspective on implementation processes.