Carnegie and SRI Education presented a webinar for networked improvement communities on improvement analytics, or learning from data to drive improvement, to select National Science Foundation (NSF) grantees. The webinar was offered by NSF INCLUDES, a comprehensive initiative to enhance U.S. leadership in science and engineering discovery and innovation by proactively seeking and effectively developing science, technology, engineering, and mathematics (STEM) talent from all sectors and groups in our society. By facilitating partnerships, communication, and cooperation, NSF aims to build on and scale up what works in broadening participation programs to reach underserved populations nationwide.

The webinar was the third in a series focused on a core set of closely related issues at the heart of any collective impact or networked improvement community effort. This webinar addresses the question: how can data be used to drive improvement? Answering this question can be complex, and as research on data-driven decision-making in education highlights, data don’t drive—people do. Using data for improvement purposes requires multiple enabling conditions, such as a common aim and a series of change ideas. This webinar presented examples of a family of measures developed in Carnegie’s and SRI’s various improvement efforts. Webinar participants were introduced to the process of developing a working theory for improvement, which in turn anchored a family of measures. The presenters also demonstrated how to develop practical measures that can be used as part of an INCLUDES project’s effort to make progress on high-leverage problems that orient the NIC. Watch the archived webinar here.