This block we explored the topic of ‘Governing with data’, the interdependence between government and knowledge (production and use), as well as different ways of digital governance and practice. According to Ozga (2016), there has been a drastic shift in terms of how human activity is understood and measured, and the ease by which vast amount of data can be collected and process sin all aspects of human activity. The rise of ‘data-led’ practices where ‘actionable data’ is privileged, pose the risk of reducing ‘creative thinking’ and limit the possibility of understanding the ‘fundamental problems and possibilities’ of human activity. In term of digital governance in education, data-led government policies have lead to a more flexible and fast responding approach to educational policy.
The term ‘educational governance’ is embedded in highly- coded educational practices with the ‘values, worldviews and aspirations’ of many actors, from programmers to algorithm designers to educational analysts and government representatives. (Williamson, 2017) There is a clear trend towards a form of ‘digital education governance’ that demands a constant flow of data to create ‘digital trails and timestreams’ to govern.
The role of ‘big data’ in education is more prominent every day, particularly in times like these where there is a greater demand than ever for digital tools and more effective ways of teaching online. The impact of ‘big data’ in education can be seen in different forms, from the ‘normalisation of digital data work within education/schooling’ (Ozga, 2016) to the data mining of student information at a transnational, national and institutional level in an attempt to solve all educational problems.
The implicit bias in the data collection process is visible in the creation of the algorithms from a particular perspective, to the questions asked, or the choice of what is considered valuable to measure. Test-based accountability as a way of information collection and decision making, also represents a power problem. ‘Determining what kind of information about the nation’s students, teachers, and schools is collected and how tit is processed, disseminate, and used, by whom, in what form, and for what purposes involve questions of power.’ (Anagnostopoulos and Jacobsen)
This block ‘Governing with data’ helped me explore the concept of ‘code’ from a different perspective. Ozga (2016), defines code as a ‘system of regulation that shames conduct and transmits messages about what counts as knowledge’. This way of understanding ‘code’ in an educational context, shifts the emphasis towards the ‘automagical’ properties of software, and the ‘structured and structuring’ power of code. Coding practices and inspection frames and activities, also have the power being disciplined and disciplining others. This seems to be a never-ending cycle where one system feeds form another, in a continuous flow of information that structures and shapes human interactions and behaviour. Governments often rely on ‘experts’ or other people who are able to interpret and transform this vast amount of information generated into ‘actionable data’. (Ozga, 2016)
In conclusion, the power of data in educational governance is very significant in terms of the impact in can have in educational practices, inspection processes and government educational policy. Overall, according to the authors read in this block, a more ‘critical assessment’ of the implications of governing with data is required.
Anagnostopoulos, D., Rutledge, S.A. and Jacobsen, R. ‘Introduction: Mapping the Information Infrastructure of Accountability’, in Anagnostopoulos, D.R.S.A. and Jacobsen, R. (eds.) The Infrastructure of Accountability: Data use and the transformation of American education., pp. 1-20.
Ozga, J. (2016) ‘Trust in numbers? Digital Education Governance and the inspection process’, European Educational Research Journal, 15(1), pp. 69-81.
Williamson, B. (2017) Big data in education : the digital future of learning, policy and practice. Los Angeles: SAGE.