Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education

Abstract

The emergence of digitized health and physical education, or ‘eHPE’, embeds software algorithms in the organization of health and physical education pedagogies. Particularly with the emergence of wearable and mobile activity trackers, biosensors and personal analytics apps, algorithmic processes have an increasingly powerful part to play in how people learn about their own bodies and health. This article specifically considers the ways in which algorithms are converging with eHPE through the emergence of new health-tracking and biophysical data technologies designed for use in educational settings. The first half of the article provides a conceptual account of how algorithms ‘do things’ in the social world, and considers how algorithms are interwoven with practices of health tracking. In the second half, three key issues are articulated for further exploration: (1) health tracking as a ‘biopedagogy’ of bodily optimization based on data-led and algorithmically mediated understandings of the body; (2) health tracking as a form of pleasurable self-surveillance utilizing data analytics technologies to predict future bodily probabilities and (3) the ways that health-tracking produces a body encased in an ‘algorithmic skin’, connected to a wider ‘networked cognitive system’. These developments and issues suggest the need for greater attention to how algorithmic systems are embedded in emerging eHPE technologies and pedagogies.