Beyond data extraction: alternative models for the governance of educational data

This paper discusses data governance models for educational platforms that could better protect students’ and teachers’ privacy and reduce data management burdens for teachers and administrators. Within an ethnographic study involving four Swedish secondary schools and municipal- and national-level administrators working with educational technology, we conduct qualitative interviews informed by educational data-tracing activities done with the help of computational methods from infrastructure studies. We highlight the extractive nature of the current data governance model, and demonstrate the power imbalances inherent to it, the uncertainties surrounding big tech companies’ data management practices, the burdens placed on teachers and administrators, and the fragmentation of the data/platform ecosystem. This allows us to engage in conceptual analysis of the desirability and feasibility of three alternative data governance schemes as applied to education: personal information management systems (which enable individuals to make data-related decisions), data trusts (expert bodies handling data governance in a fiduciary way) and data cooperatives (which steward data in a decentralised fashion through participatory and democratic decision-making). We conclude that data trusts offer the best response to the concerns identified through our infrastructural and ethnographic study, while also being the most feasible to implement in a variety of school systems.