Algorithms of Education How Datafication and Artificial Intelligence Shape Policy
A critique of what lies behind the use of data in contemporary education policy While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming educat...
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| Format: | eBook Book |
| Language: | English |
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Minneapolis
University of Minnesota Press
17.05.2022
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| Edition: | 1 |
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| ISBN: | 1517910250, 9781517910259 |
| Online Access: | Get full text |
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| Abstract | A critique of what lies behind the use of data in
contemporary education policy
While the science fiction tales of artificial intelligence
eclipsing humanity are still very much fantasies, in Algorithms
of Education the authors tell real stories of how algorithms
and machines are transforming education governance, providing a
fascinating discussion and critique of data and its role in
education policy.
Algorithms of Education explores how, for policy
makers, today's ever-growing amount of data creates the illusion of
greater control over the educational futures of students and the
work of school leaders and teachers. In fact, the increased
datafication of education, the authors argue, offers less and less
control, as algorithms and artificial intelligence further abstract
the educational experience and distance policy makers from teaching
and learning. Focusing on the changing conditions for education
policy and governance, Algorithms of Education proposes
that schools and governments are increasingly turning to "synthetic
governance"-a governance where what is human and machine becomes
less clear-as a strategy for optimizing education.
Exploring case studies of data infrastructures, facial
recognition, and the growing use of data science in education,
Algorithms of Education draws on a wide variety of
fields-from critical theory and media studies to science and
technology studies and education policy studies-mapping the
political and methodological directions for engaging with
datafication and artificial intelligence in education governance.
According to the authors, we must go beyond the debates that
separate humans and machines in order to develop new strategies
for, and a new politics of, education. |
|---|---|
| AbstractList | A critique of what lies behind the use of data in
contemporary education policy
While the science fiction tales of artificial intelligence
eclipsing humanity are still very much fantasies, in Algorithms
of Education the authors tell real stories of how algorithms
and machines are transforming education governance, providing a
fascinating discussion and critique of data and its role in
education policy.
Algorithms of Education explores how, for policy
makers, today's ever-growing amount of data creates the illusion of
greater control over the educational futures of students and the
work of school leaders and teachers. In fact, the increased
datafication of education, the authors argue, offers less and less
control, as algorithms and artificial intelligence further abstract
the educational experience and distance policy makers from teaching
and learning. Focusing on the changing conditions for education
policy and governance, Algorithms of Education proposes
that schools and governments are increasingly turning to "synthetic
governance"-a governance where what is human and machine becomes
less clear-as a strategy for optimizing education.
Exploring case studies of data infrastructures, facial
recognition, and the growing use of data science in education,
Algorithms of Education draws on a wide variety of
fields-from critical theory and media studies to science and
technology studies and education policy studies-mapping the
political and methodological directions for engaging with
datafication and artificial intelligence in education governance.
According to the authors, we must go beyond the debates that
separate humans and machines in order to develop new strategies
for, and a new politics of, education. |
| Author | Kalervo N. Gulson P. Taylor Webb Sam Sellar |
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| BackLink | https://cir.nii.ac.jp/crid/1130578348765432327$$DView record in CiNii |
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| Copyright | 2022 the Regents of the University of Minnesota |
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| DOI | 10.5749/j.ctv2fzkpxp |
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| Discipline | Education |
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| Notes | Includes bibliographical references and index |
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| Snippet | A critique of what lies behind the use of data in
contemporary education policy
While the science fiction tales of artificial intelligence
eclipsing humanity... |
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| SubjectTerms | Artificial intelligence -- Educational applications Education Education -- Data processing Education -- Mathematical models Education -- Mathematical models -- Data processing |
| Subtitle | How Datafication and Artificial Intelligence Shape Policy |
| TableOfContents | Front Matter
Table of Contents
INTRODUCTION.
CHAPTER ONE: Governing:
CHAPTER TWO: Thought:
CHAPTER THREE: Problems:
CHAPTER FOUR: Infrastructure:
CHAPTER FIVE: Patterns:
CHAPTER SIX: Automation:
CHAPTER SEVEN: Synthetic Politics:
ACKNOWLEDGMENTS
NOTES
INDEX
Back Matter Cover Page -- Title Page -- Copyright Page -- Contents -- Introduction: Synthetic Governance: Algorithms of Education -- Chapter 1: Governing: Networks, Artificial Intelligence, and Anticipation -- Chapter 2: Thought: Acceleration, Automated Thinking, and Uncertainty -- Chapter 3: Problems: Concept Work, Ethnography, and Policy Mobility -- Chapter 4: Infrastructure: Interoperability, Datafication, and Extrastatecraft -- Chapter 5: Patterns: Facial Recognition and the Human in the Loop -- Chapter 6: Automation: Data Science, Optimization, and New Values -- Chapter 7: Synthetic Politics: Responding to Algorithms of Education -- Acknowledgments -- Notes -- Index -- About the Author |
| Title | Algorithms of Education |
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