I’ve found this final block particularly interesting, possibly because it links most closely to the aspect of education that I’m involved in working in.
The centrality of knowledge and information (linked to neoliberal influences in education) incurred a change from traditional construction of knowledge in segments to a more interdisciplinary, problem solving approach which often includes data (Grek & Ozga, 2010 in Ozga, 2016). With the notion of improvement often connected with data in education, policy problems and solutions can be derived from the same data (Ozga, 2016). Although a collection of similar hot and cold data; animal noises or indeed screen time from different people could be comparable, there would be limitations to the decisions made from the information. Through a centralised approach to reviewing this data, it is likely it would be presented and considered as a problem to be solved as part of improvement or reform. This is not a critique to say that there is not a problem to be solved, rather that wider examination and shared understanding is required amongst the education system and the wider public about the direction in which our education should and can move – that’s fair to all learners’ opportunities. This involves careful inspection of the tensions between outputs and outcomes relating to the data (Anagnostopoulos et al, 2013). Data and data visualisation could be a powerful tool in the decision-making processes, not least for the perceived accessibility of the information, or the ability for it data and their visualisation to ‘sell’ progress (Williamson, 2017; Sobe, 2013).
If these types of data at a local level were compared at national level, then for it to be perceived as objective it could be desirable to achieve a detachment context eg from the dog loving bias in my final visualisation (Ozga, 2016). This means that the data could show that dogs are appearing in substantial numbers where I live, as opposed to cats, which may not be true. I’m fairly certain that I probably neglected to notice a couple of cats! By the time these data were compared nationally, the context and my biases might not be considered with the decisions that the data was contributing to.
Part of the centralisation (to public and private organisations rather than local institution level) of education governance and data is supplemented by the wider public knowledge and the media. Data have a “popular and official currency” (Pattoria, 2017, p. 8 in Ozga, 2016). Education is both influenced and is influenced by public life and social policy (eg American civil rights examples in Fontaine, 2016; equalities acts including UNCRC incorporation into Scottish Law). Therefore, data visualisations (such as my bar graph, dots and hs and cs) in the media holds potential influence over society’s understanding of educational data, trends in education and perceived educational success (Prinsloo, 2020). The centralisation of education governance allows for a briefer (and oversimplified) representation of educational data.
In this block, the potential intrinsic power of data (what Anagnostopoulos et al (2013) describe in the rise of informatic power) was evident. It is imperative that all involved in education – including the learners – understand the influence that their data have on governance decisions. Perhaps data visualisation is both a problem and a solution in that regard?
Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. 2013. Conclusion: The Infrastructure of Accountability: Tensions, Implications and Concluding Thoughts. In, Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. (Eds) The Infrastructure of Accountability: Data use and the transformation of American education.
Fontaine, C. 2016. The Myth of Accountability: How Data (Mis)Use is Reinforcing the Problems of Public Education, Data and Society Working Paper 08.08.2016
Ozga, J. 2016. Trust in numbers? Digital Education Governance and the inspection process. European Educational Research Journal, 15(1) pp.69-81
Prinsloo, P. 2020. Data frontiers and frontiers of power in (higher) education: a view of/from the Global South. Teaching in Higher Education, 25(4) pp.366-383
Sobe, N. (2013) Educational data at late ninteeth- and early twentieth-century international expositions: ‘accomplished results’ and ‘instruments and apparatuses’ in Lawn, M. (ed), The Rise of Data in Education Systems: collection, visualization and use. Oxford: Symposium. Pp. 41-56.
Williamson, B. (2017) Digital Education Governance: political analytics, performativity and accountability. Chapter 4 in Big Data in Education: The digital future of learning, policy and practice. Sage.