Even though I had a really busy week at work and wasn’t able to participate in the Tweetorial, I monitored the tweets regularly and tried to visualise them. I wanted to illustrate the richness of the discussion so I chose to pull out the main terms from the various tweets.
Looking at the visualisation, key themes and issues become clear even for those who aren’t familiar with any of the literature on ‘governing’ with data.
As so often when data are involved, the terms ‘objective’ and ‘impartial’ appear. In the same breath, however, ‘bias’ and ‘subjectivity’ are mentioned, reminding us that data aren’t neutral. When it comes to data and governing, ‘accountability’ is a term that frequently arose in both tweets and literature. Big data and the associated notions of countability, numbering and statistical knowledge, give rise to new forms of ‘data-driven governance’ with an emphasis on ‘evidence-based policymaking’ (Williamson, 2017). This shift raises questions of whether bias is considered in policy making and which actors are involved.
An example of how powerful global policy actors have become is the OECD. Outcomes of their Programme for International Student Assessment (PISA) can result in countries changing their education policies in order to perform better in the assessment (Liss, 2013). Germany was one of the countries that performed badly in 2001 and the resulting ‘PISA shock’ led to steps being taken to improve test results. While this was achieved, the inequality gap in Germany has widened (Davoli and Entorf, 2018), reminding us of the potential issues of standardisation in education.
Davoli, M. & Entorf, H. (2018) ‘The PISA Shock, Socioeconomic Inequality, and School Reforms in Germany’, IZA Policy Papers 140, Institute of Labor Economics (IZA).
Liss, J. (2013) ‘Creative destruction and globalization: The rise of massive standardized education platforms’, Globalizations, Vol. 10, No. 4, pp. 557-570.
Williamson, B. (2017). Big Data in Education: The digital future of learning, policy and practice. Sage.