The epistemic machinery of educational platforms

This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack these platforms’ epistemic arrays of data extraction, interfaces, justifications, and representations and the knowledge arrangements they aim to constitute in schools. Borrowing Knorr-Cetina’s notion of ‘epistemic machineries,’ which entails the material and discursive apparatuses of knowledge production in specific ‘epistemic cultures,’ we analyse the platforms’ empirical apparatuses, ontological assumptions, and referential constructions. This exploration unearths two different digital epistemes: a gamified, engagement-based recognition system; and a bureaucratic-scientific framework that aims to produce actionable data for educators and schools. We explore the ramifications of these different human-machine entanglements and question how these bring to bare on pertaining to school life, such as human agency, knowledge practices, and educational decision-making.