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maig 16 2014

Very new Big Data and very old Positivism: uses of knowledge for education policy-making

The recent debate on the OCDE Programme for International Student Assessment in The Guardian retrieves a number of deep questions about the use of knowledge in education policy-making. In fact, although it is obvious that such policy deals with knowledge as far as the curriculum is concerned, it should also be noticed that research produces telling evidence on  policy designs and evaluation reports. Advocates of Big Data insist on the possible contribution of the huge amounts of information produced by satellites, social networks and geographic information systems for many dimensions of human development. Recently, an officer working for the World Bank Group argued that this source of evidence could be extremely helpful for designing innovative teaching methods tailored for poor students.

The proposal of using these new technical services to tackle poverty raises a number of questions about the involvement of Public-Private Partnerships in their procurement. To the extent that a variety of providers is entering the sector, such a policy may transform the rules of the game that schools are playing. Particularly, Big Data could reinforce the role of large corporations that run for-profit schools in poor communities and make a short-term profit by availing of the alleged economies of scale produced by this new mode of knowledge management. Potential harms for equity are also at stake.

However, two further implications affecting the scope of selected knowledge should be also taken into account. First, if complex algorithms that analyse Big Data are used to lead effective teaching, the resulting guidelines will very likely neglect the role of professional knowledge in the very activity of teaching. Besides short sets of explicit instructions, an exhaustive map of knowledge should be aware of both simple and complex explicit knowldge as well as of relational, somatic and collective tacit knowledge. All these components are crucial for teaching and learning. Notably, many of the arguments posited to invest in Big Data are locked in one of the old myths taken for granted by Positivism in the nineteenth century, namely: that data are the only component of knowledge.

Second, these algoriths can only provide sound recommendations to teachers depending on specific research questions. Findings do not come out from a mathematical pattern that fits data, but from a theoretical understanding of this match between data and a model. This is a basic principle of epistemology and methodology whose consequences have been widely discussed. Do we need these amounts of data for answering to the main questions of educational research? Do these data account for all the aspects involved in teaching and learning? Can we really extrapolate the conclusions of classroom data collected in a given setting to a large variety of schools? Another myth of that old Positivism precisely consisted of overlooking this type of questions.


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