Our projects and partnerships span five phases. These phases were developed and tested through an iterative, design-based approach that combined insights from multiple research-practice partnerships. These partnerships have all aimed to develop data products and change ideas that support more equitable and effective learning environments. In working to achieve this aim, we identified the importance of four interrelated conditions: (1) trust and shared values among partners, (2) use of an explicit improvement method, (3) learning events that facilitate knowledge- and trust-building, and (4) data sharing infrastructure that promote joint interpretation of data products in a secure and ethical manner. The figure, below, illustrates our theory for how these conditions can be thought to support achieving the aim of using data intensive research techniques to improve learning environments. This theory is tentative, and we are working everyday to improve our understanding of how to engage in data intensive research with practitioners. Please contact us with ideas or suggestions.
Each one of the above primary drivers runs throughout the five phases of a CDIR project:Phase I: Prepare
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