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Appears in Collections:Faculty of Social Sciences Working Papers
Peer Review Status: Unrefereed
Title: Organizing algorithms, calculated publics in digitally-mediated education
Author(s): Williamson, Ben
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Citation: Williamson B (2014) Organizing algorithms, calculated publics in digitally-mediated education.
Keywords: algorithms
digital education
Big Data
Digital Media, Education
Issue Date: 4-Aug-2014
Date Deposited: 16-Feb-2015
Abstract: Recent news reports have begun to reveal how various analytics companies are now data mining millions of children. The learning analytics company Knewton, for example, claims that 4.1 million students are now using its proficiency-based adaptive learning platform, which has served 3.5 billion total recommendations between May 2013 and May 2014 alone. The role of these predictive analytics platforms and recommender systems in education is increasingly causing political and parental concerns, largely related to privacy. Less acknowledged, however, is the increasingly autonomous and automated capacity of the software algorithms working in the background of these platforms. Algorithms have become powerful devices in digitally-mediated education. They are present not only in the predictive analytics and recommender systems of adaptive learning platforms, but in the social networking sites where ‘networked publics’ hang out, in the information practices deployed in inquiry learning, in techniques of digital making, and in the ed-tech software promoted in classrooms. To put it bluntly, algorithms are now deeply embedded in the governance of education and learning—where governance means the techniques by which people’s actions, thoughts and ways of conducting themselves are evaluated, shaped and sculpted. So what do algorithms do, how much power do they have in the social ordering and governance of education, and how might they be influencing the lives of learners?
Type: Working Paper
Rights: Author retains copyright
Affiliation: Initial Teacher Education - LEGACY

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