Blinding Data

My research will take place in a social and political climate in which a proliferation of digital devices, global online platforms, sensors and closed-circuit cameras has enabled the capture of vast amounts information, earning it the appellation "Big Data" and epigrammatic depiction as the "new oil" (Economist, 2017).
In school, data is harvested from systems monitoring attendance, from pupils' interaction with apps and learning environments and from baseline and summative testing and examination. There is a burgeoning interest in behavioural and social and emotional information derived from facial recognition technology, wearable devices and data-loggers.
Education technology systems harvest student data for modelling aptitude and behaviours in order to predict achievement and personalise learning. Using Artificial Intelligence (AI) and Machine Learning (ML) techniques, they articulate a "child-by-numbers" in a society in which numbers are hard to challenge yet remain amenable to inscrutable algorithmic intervention.
My research will explore how these technologies both represent and constitute a powerful mode of "authorised seeing" and governance (Jasanoff, 2015) by the ways in which they construct, measure and control teachers and pupils, raising pressing questions about learning and knowledge in the educational domain. The work will introduce much-needed interdisciplinary perspectives to understand the social and ethical impact of intensive data processing on new generations of students.
Whilst there is a growing body of critical work focusing on datafication in Higher Education, my research will address a gap by examining the impact of an unrelenting data-emphasis in secondary schools in the Edinburgh region.
Methodology
My ontological position is summarised by the belief that nothing is known distinct from the way in which it is known and given value. This belief is important for tracing the complex sociomaterial networks that constitute big data and its claims for supremacy.
My position calls for a methodology that troubles notions of discrete and objective data and I will employ a postqualitative approach because of its commitment to rethink traditional research methods, data and analysis. I will draw inspiration from the work of Donna Haraway, Karen Barad and Elizabeth St Pierre among others.
I will collaborate with teachers and pupils in three secondary schools in the Edinburgh area on experimental and participatory projects akin to Ruppert's "para-sites" which "combine research, reflection and reporting and a mix of participants" (2018, p.25) using three bespoke methods: "A life in the day of data", "iVersify" and "Wicked!".
Postqualitative methods emerge in responsive and responsible ways from the research experience. Their hallmarks include ethnographic sensibilities and being alert to doubt, difficulty, assumption and surprise. I will attend to breakdowns in understanding to avoid a fixed framing of the research material and remain sensitive to the affective and embodied as constituting valid and important data. A postqualitative methodology aims to surface that which is elided and marginalised and to creatively engender new possibilities.
References
Economist (2017). The world's most valuable resource is no longer oil, but data. Economist [Website]. Available at: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data
Jasanoff, S. (2015). Future imperfect: Science, technology, and the imaginations of modernity. In S. Jasanoff & S.-H. Kim (Eds.), Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power, (pp. 1-35). Chicago, IL: University of Chicago Press.
Ruppert, E. (2018). 'Sociotechnical imaginaries of Different Data Futures: An experiment in citizen data'. Dutch and Flemish Sociological Association Conference and the Third Van Doorn Lecture. Rotterdam, Netherlands. June 2018.