Digital technologies are a key part of how data is generated, stored, processed and circulated throughout schools. Even the smallest of schools is now home to myriad forms of data-work – from the accumulation of data ‘traces’ resulting from each use of a digital system and application, through to more direct forms of data profiling, ‘data mining’ and dataveillance. These data processes increasingly are taking algorithmic form, where raw data feeds into complex calculations and modelling processes designed to predict and inform future action. These forms of data work are often anticipatory in nature, concerned with managing future consequences rather than understanding existing causes of social problems (Lyon 2014).
Such uses of data can be justified as supporting efficient modes of governance and management. Rob Kitchin (2014) points to the role of data in enhancing organizational preparedness and response, cross border planning and/or whole institution management. However, a range of attendant concerns also require consideration. These include issues of reductionism and the privileging of an ‘instrumental rationality’ that presumes that complex social and cultural situations can be dissembled into discrete, neatly modelled problems that are addressable through calculation and computation. (Mattern 2013). Further questions need to be asked regarding the potential for data-based calculations and judgments to exacerbate unequal social relations between powerful and non-powerful groups. Scott Lash (2007), for example, warns of new power-laden regimes of ‘facticity’ which marginalize the agentic opportunities available to disadvantaged ‘smaller’ actors’.
In many ways, the increasingly data-driven nature of how schools are organized and governed is to be expected. Jean-François Lyotard wrote presciently at the beginning of the 1980s of the production of performative knowledge in French universities through databases and data systems. These themes were expanded in Mark Poster’s writing during the early 1990s on the database as a society-wide means of subjectivication and control. Subsequently, Michael Hardt and Antonio Negri observed the reframing of modern institutions as ‘inspection regimes’ built around the recording, monitoring, gathering and storage of data. Now – decades later – it is of little surprise that these warnings have come to be realized in mundane organizational settings such as the school.
Against this background, sustained attention needs to be paid to the actual (rather than imagined) experiences and enactments of digital data within the realities of schools. In particular, the critical debates outlined above need to be substantiated by empirical studies of “the everyday use of data and analytics from a social perspective” (Couldry 2015). In this spirit, our study needs to investigates the ways in which digital data is implicated in the day-to-day school experience. As such we need to consider research questions such as …
- What data exist in schools? How are schools and other educational organisations gathering data? What areas of schooling do these data relate to (i.e. teaching and learning, organization and administration, leadership and management, change and innovation)? In what forms do these data exist and in what forms are these data accessible (e.g. open/closed access, raw/value-added)? Are these data created intentionally or ‘naturally-occurring’? What are the quality, scope, inter-operability and compatibility of these data? What is assembled – included/excluded, present/absent, inside/outside of these data? How has this assembling of data varied and changed over time?
- What are the ‘primary’ uses of these data?g. measurement, monitoring, formative or summative assessment? Where in education systems are these data being used, e.g. individual classrooms, departments, schools, regions, states/provinces, or (inter)national? How are these data being used and by whom – i.e. data work by internal and external actors, data work for auditing and assessing, or decision-making and planning?
- What – if any – are the ‘secondary’ uses of these data? For what purposes are these data being re-used and by whom? How are these data being used for prediction; analysing trends and patterns; modeling; distillation of data for human judgment? How do these data inform ‘rules of thumb’, informal models and implicit practices of understanding and making sense? What is the ‘social life’ of these data – i.e. how are these data being aggregated, segregated and reconstituted? What innovative data practices can be identified within school settings?
- What are the consequences of these uses of data? Are these data uses leading to improved outcomes, efficiencies, self-regulation and/or relationships? How are data uses related to alter social relations within schools – i.e. in terms of relations of power and control, conditions of performativity and/or surveillance? How do these consequences differ between students, teachers, administrators, school leaders and managers? How are digital technologies supporting the connection, aggregation and use of data in ways not before possible?
- What organizational cultures have formed around the use of data within school settings, and with what outcomes? Where does data work mirror existing institutional structures and hierarchies? Where is data disrupting, changing or leading to new arrangements, relationships and understandings? Where is data leading to a refocusing in practice/understandings towards to measurable and ‘visible’? What ethical, legal, managerial and organizational issues are shaping the use of data within schools?
- How might data-work be more efficiently and equitably arranged in schools? How might authorities ensure ‘beneficial’ collective use of the total data that is available to those who currently have data ‘done to’ them, rather than having the availability ‘to do’ data? Conversely, how might data access and use be more democratically arranged across all elements of school communities? In both these senses, what types and forms of data and data accessibility are desirable? How might quality data sets (in terms of scope, interoperability and compatibility) and sources be developed? What data tools and technologies are required?
Couldry, N. 2015. A necessary disenchantment: myth, agency and injustice in a digital world. The Sociological Review, [ahead of print]
Lyon, D. (2014). Surveillance, Snowden, and big data: capacities, consequences, critique. Big Data & Society, 1(2):1-13
Kitchin, R. 2014. The Data Revolution. London
Lash, S. 2007. Power after hegemony. Theory, Culture & Society, 24(3), 55–78.
Mattern, S. 2013. Methodolatry and the art of measure. Design Observer: Places, 5. [https://placesjournal.org/article/methodolatry-and-the-art-of-measure/]