Data-driven Educational Practices: On Access, Transparency, and the Value-creation of Data

By setting the spotlight on the intricate relationship between form, content, and outcomes in data-driven educational practices, this chapter explores the nuanced dimensions of value creation in such practices. A series of illustrative examples that deal with the use of data-driven tools to perform and deliver certain tasks are used to discuss the negotiation of standards during instructional interaction, as well as the cultural boundaries between epistemic and non-epistemic knowledge. More specifically, examples from driving simulator-based instruction in a Natural Resource Program show the complex alignment with set standards in practices of assessment and feedback. This chapter critically examines various dimensions, incorporating both political and ethical aspects of data value creation. It emphasizes the necessity for a meta-perspective that addresses the sensitive issues of access and transparency in educational practices. This serves as an ethical measure to make students aware of algorithmic control. Furthermore, the chapter argues for processes of data creation and evaluation that stay close to its users in space and time. By keeping the value of data bound to its context, we avoid the pitfalls of tools’ market-orientation, and we create the conditions for the understanding and theorization of data-driven educational practices.