"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"--
"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"--Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Kalervo N. Gulson is professor in education policy at the University of Sydney. He is author of Education Policy, Space, and the City: Markets and the (In)visibility of Race and coauthor of Education Policy and Racial Biopolitics in Multicultural Cities. Sam Sellar is professor in education policy at the University of South Australia. Most recently he coedited the World Yearbook of Education 2019: Comparative Methodology in the Era of Big Data and Global Networks. P. Taylor Webb is associate professor in the Department of Educational Studies at the University of British Columbia. He is coauthor of, among others, Education Policy and Racial Biopolitics in Multicultural Cities.
Inhaltsangabe
Introduction. Synthetic Governance: Algorithms in Education 1. Governing: Networks Artificial Intelligence and Anticipation 2. Thought: Acceleration Automated Thinking and Uncertainty 3. Problems: Concept Work Ethnography and Policy Mobility 4. Infrastructure: Interoperability Datafication and Extrastatecraft 5. Patterns: Facial Recognition and the Human in the Loop 6. Automation: Data Science Optimization and New Values 7. Synthetic Politics: Responding to Algorithms in Education Acknowledgments Notes Index
Introduction. Synthetic Governance: Algorithms in Education 1. Governing: Networks Artificial Intelligence and Anticipation 2. Thought: Acceleration Automated Thinking and Uncertainty 3. Problems: Concept Work Ethnography and Policy Mobility 4. Infrastructure: Interoperability Datafication and Extrastatecraft 5. Patterns: Facial Recognition and the Human in the Loop 6. Automation: Data Science Optimization and New Values 7. Synthetic Politics: Responding to Algorithms in Education Acknowledgments Notes Index
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