Educational systems generate huge quantities of digital data. Digital educational data is captured and used at all points -- from classrooms and schools, to the level of educational departments. As growing trends in ‘data-driven instruction’ suggest, all these data have great potential to support student, teacher and leadership practices, help guide work and learning decisions, and inform policy development. Moreover, an increasing focus is being placed on the development of artificial intelligence to automate and improve how data are used. Yet, stakeholder data practices remain invisible and little understood, which complicates how artificial intelligence can be embedded in this context. In this paper, we introduce an educational data journeys framework to frame dynamics of data power, data work, identities and literacies. This approach is employed to explore educational policy revealing data flows and frictions in school improvement and implications for the development of artificial intelligence in education.
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