Exploring case studies of data infrastructures, facial recognition, and the use of data science in education, Algorithms of Education maps the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond debates that separate humans and machines to develop new strategies for, and a new politics of, education.
- rightsThe University of Minnesota Press gratefully acknowledges support for the open-access edition of this book from the University of Sydney, the Australian Research Council, and the Social Sciences and Humanities Research Council (SSHRC) of Canada.
A different version of chapter 2 was previously published as Sam Sellar, “Acceleration, Automation, and Pedagogy: How the Prospect of Technological Unemployment Creates New Conditions for Educational Thought,” in Education and Technological Unemployment, ed. M. A. Peters, P. Jandric, and A. J. Means, 131–44 (Dordrecht: Springer, 2019). A different version of chapter 4 was previously published as Kalervo N. Gulson and Sam Sellar, “Emerging Data Infrastructures and the New Topologies of Education Policy,” Environment and Planning D: Society and Space 37, no. 2 (2019): 350–66; and as Sam Sellar and Kalervo N. Gulson, “Dispositions and Situations of Education Governance: The Example of Data Infrastructure in Australian Schooling,” in Education Governance and Social Theory: Interdisciplinary Approaches to Research, ed. A. Wilkins and A. Olmedo, 63–79 (London: Bloomsbury Academic, 2018); Bloomsbury Academic is an imprint of Bloomsbury Publishing PLC. A different version of chapter 6 was published as Sam Sellar and Kalervo N. Gulson, “Becoming Information Centric: The Emergence of New Cognitive Infrastructures in Education Policy,” Journal of Education Policy 36, no. 3 (2021): 309–26, available at https://www.tandfonline.com.
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