The promises and premises of digital ‘dataism’

There are many good reasons to welcome the increased use of digital data in schools. While we might have reservations about the realities of how data-driven schooling is playing out ‘on the ground’, it is important not to lose sight of the benefits, improvements and other positive changes that might be possible.

Data-driven schooling is usually justified along a number of familiar lines. These all centre on the premise that digital data can provide a powerful basis for deciding what to do next. These decisions can range from what an individual student chooses to learn, through to schoolwide budget and resourcing allocations. Some decisions might be instantaneous and executed autonomously (e.g. whether a visitor is admitted through the school gates), whereas other decisions will require detailed analyses of many data-points with considerable human input (e.g. the timetabling of classes for the next school year)

Regardless of the type of decision, the basic premise is that digital data allows us to know more about a school. Crucially, the vast amount of digital data being generated within any school raises the possibility of having continuous ‘real-time’ information that can provide comprehensive insights into what is going on … and what should be done next. The promise of enhanced ‘knowing’ is certainly reflected in how education data is talked about – e.g. sentient schools, smart schools, precision education, adaptive teaching, personalised learning. Such phrases suggest an accuracy, efficiency and flexibility that many people might consider to have been lacking from the analogue schools of the past 100 years or so. Who wouldn’t want such qualities to now be infused throughout today’s schools?

Indeed, for some people, the logic of data-driven schooling is self-evident – requiring little justification or thought. The use of digital data in schools is an inherently ‘good thing’. Jose Van Dijk refers to this as the ideology of ‘dataism’. As she describes it:

the ideology of dataism shows characteristics of a widespread belief in the objective quantification and potential tracking of all kinds of human behaviour and sociality through online media technologies” (Van Dijk 2014, p.198)

This reference to ‘belief’ might be taken to infer a quasi-religious blind faith in the power of data. However, it is important not to dismiss such enthusiasms as an unthinking acceptance or naïve hope. Instead, there are a number of important assumptions at work here, especially with regards to the changing nature of social knowledge within a data-infused school environment. These include the assumptions that:

  • What goes on in school can be understood primarily as a continuous process of decision-making by individuals (either for themselves or on behalf of others). Improving what goes on in school can therefore be achieved by better informing (and thereby influencing) the ‘choices’ made by individuals. The mass of digital data being generated therefore offers a good basis for informing most (if not all) forms of decision-making that take place within a school.
  • A lot of what takes place in an organisation like a school involves decisions that do not really require repeated human involvement. Procedural and routine operations can be automated, using relevant data to execute pre-programmed sequences of logic. This can then ‘free up’ humans to engage with higher-level issues.
  • Digital data provide a comprehensive basis for basing decisions on. The scope of data being generated within a school vastly exceeds what any individual could hope to ‘know’ for themselves. In an ideal situation, the feedback that is offered by digital data analysis will be timely and drawn from a range of complementary sources. Digital data can represent what people have done as soon as they have done it – what can be termed ‘real-world’ data collected in ‘real-time’. As such, high-quality data analysis should be given more credence than people’s own observations, expectations and estimations.
  • Digital data provides a precise basis for making decisions. In contrast to the ‘messiness’ of most aspects of education, the discrete nature of data (as the cliché goes, ultimately in the form of ‘zeroes and ones’) offers definite and unambiguous responses. As Hintz puts it, the analysis of digital data provides “a seemingly ‘scientific’ method for tacking uncertainty” (Hintz et al. 2019, p.45).
  • Digital data provides an objective and unbiased basis for making decisions. As Hintz continues, digital data “may reduce political influences and subjective judgements and may therefore offer a more rational, impartial, reliable and legitimate way of decision-making” (Hintz et al. 2019, p.46).
  • Digital data can be analysed in ways that provide insights into otherwise imperceptible patterns and trends. The ongoing generation of data means that any analysis is longitudinal in nature. In contrast to ‘one-off’ measurements, digital data lend themselves to being analysed in terms of trends and trajectories – giving a sense of being able to identify how things have changed over time, as well as predicting how things might change in the future. As Hintz puts it, digital data is seen to give us a capacity for “understand[ing] previous occurrences, predicting future behaviour and facilitating possibilities for pre-emptive action” (Hintz et al. 2019, p.46).


These are all promises that our research needs to take seriously and not lose sight of. At the same time, it is also worth reflecting how these ‘data-ist’ assumptions also infer the rearrangement and reconstitution of schools in a number of specific ways. For example, from a ‘data-ist’ perspective it makes sense that school issues are framed in terms of successfully managing risks, pre-empting future trends, and giving individuals responsibility for their choices and for the outcomes of their choices. Based on the assumption that greater volumes of digital data come with greater potential benefits, it also makes sense that a speculative (rather than strategic) approach to data stewardship is adopted. Crucially, as Jose Van Dijk acknowledges, “dataism also involves trust in the (institutional) agents that collect, interpret, and share (meta)data culled from social media, internet “platforms, and other communication technologies” (Van Dijk 2014, p.198)

Regardless of how they are labelled, these ‘data-ist’ beliefs, presumptions, trusts and understandings certainly underpin this rise of digital data in education, and are therefore well worth testing and challenging. What alternative values and assumptions might we want to imbue digital data with? What alternate flavours of dataism might be worth exploring?


[notes from Hintz et al.  2019.   Digital Citizenship in a Datafied Society.]