Educational Intelligent Economy

Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
 
 
Emerald Publishing Limited; International Perspectives on Education and Society
  • erschienen am 25. November 2019
  • |
  • 304 Seiten
 
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
978-1-78754-854-1 (ISBN)
 
Access to big data, the &quote;new commodity&quote; for the 21st century economies, and its uses and potential abuses, has both conceptual and methodological impacts for the field of comparative and international education. This book examines, from a comparative perspective, the impact of the movement from the so-called knowledge-based economy towards the Intelligent Economy, which is premised upon the application of knowledge. Knowledge, the central component of the knowledge-based economy, is becoming less important in an era that is projected to be dominated and defined by the integration of complex technologies under the banner of the fourth industrial revolution. In this new era that blends the physical with the cyber-physical, the rise of education intelligence means that clients including countries, organizations, and other stakeholders are equipped with cutting-edge data in the form of predicative analytics, and knowledge about global educational predictions of future outcomes and trends. In this sense, this timely volume links the advent of this new technological revolution to the world of governance and policy formulation in education in order to open a broader discussion about the systemic and human implications for education of the emerging intelligent economy.By providing a unique comparative perspective on the Educational Intelligent economy, this book will prove invaluable for researchers and scholars in the areas of comparative education, artificial intelligence and educational policy.
  • Englisch
  • Bingley
  • |
  • Großbritannien
Emerald Publishing Limited
  • 1,45 MB
978-1-78754-854-1 (9781787548541)
weitere Ausgaben werden ermittelt
  • Intro
  • FM
  • Half Title Page: THE EDUCATIONAL INTELLIGENT ECONOMY
  • Series Page
  • Title Page: The Educational Intelligent Economy: BIG DATA, Artificial Intelligence, Machine Learning and the Internet of Things in Education
  • Copy Right
  • Deducation Page
  • Contents
  • About the Contributors
  • FOREWORD
  • References
  • Introduction: The Educational Intelligent Economy, Educational Intelligence, and Big Data
  • Chapter Overviews
  • References
  • Chapter 1: Big "G" and Small "g": The Variable Geometries of Educational Governance in an Era of Big Data
  • Introduction
  • History of Data Collection and Governance in Comparative and INTERNATIONAL EDUCATION
  • Data Collection and the International Evaluation of Educational Achievement (IEA)
  • Data Collection and the Organisation for Economic Co-operation and Development (OECD)
  • Data Collection and UNESCO Reports
  • Governance in an Era of Data Servitization
  • Blitzscaling: Toward Educational Big Data Governance as a Complex Assemblage
  • References
  • Chapter 2: The Educational Intelligent Economy and Big Data in Comparative and International Education Research: A Decolonial Vision
  • Introduction
  • What is at Stake?
  • Big Data: Origins and Definitions
  • From Electronic Colonialism to Digital Frontierism
  • Data Sharing
  • Neoliberal Scientism, Control of Data, and the NSF
  • Way Forward
  • References
  • Chapter 3: The Perceptron: A Partial History of Models and Minds in Data-Driven Educational Systems
  • Introduction
  • Methodological Notes
  • Models, Minds, and Social Physics
  • What's "New" about Big Data and Learning Analytics?
  • American Cybernetics and Structural Objectivity
  • Cognitive and "Non-cognitive" Universalizations
  • Of Perceptrons and Change
  • Concluding Remarks
  • References
  • Chapter 4: Best Practices from Best Methods? Big Data and the Limitations of Impact Evaluation in the Global Governance of Education
  • Introduction
  • Methodological Limitations of Impact Evaluation
  • Regression Analysis
  • Randomized Control Trials
  • Group Differences
  • Unbiasedness and Impact
  • Variance of Treatment Effects
  • Lack of Generalizability
  • Discussion and Conclusion
  • References
  • Chapter 5: What if Compulsory Schooling was a 21st Century Invention?
  • Introduction
  • Definition of Terms
  • Learning Versus Schooling (Pedagogy)
  • Framework for Analysis and Limitations
  • Results and Discussion: Scenarios for Compulsory Schooling within an Educational Intelligent Economy Future
  • Remodel One: Role of Learner and Teacher
  • Remodel Two: Design of a School
  • Remodel Three: Purpose of Compulsory Schooling
  • Comparative Content Analysis
  • General Documents About Ethos
  • Analysis of School Websites
  • Organizational Forgetting
  • Change of Routines and Addition of "Slack Resources"
  • Conclusion
  • References
  • Chapter 6: The Educational Intelligent Economy - Lifelong Learning - A vision for the future
  • Introduction
  • Vision for the Future
  • What We Need to Do to Achieve That Future
  • Digital Competency, Literacy and the Educational Intelligent Economy
  • Technology and the Educational Intelligent Economy
  • Opportunities and Challenges of Big Data and Artificial Intelligence in Education (AIED)
  • Data Ownership
  • Data Privacy
  • Digital Exclusion Due to Algorithmic Biases
  • Opportunities and Challenges of Blockchain in Education
  • Government Policies
  • Conclusion
  • References
  • Chapter 7: Humanistic, Innovative Solutionism: What Role do Data Analytics Play in Developing a More Responsive and More Intelligent Adult and Workforce Education Policy?
  • Introduction
  • Responding to the Fourth Industrial Revolution
  • Governing Rationalities
  • Methods, Trends, and Creating Data Analysts
  • Possible Critiques to be Addressed
  • Concluding Thoughts
  • References
  • Chapter 8: Data Mining and Predictive Analytics in Digital Education: Lessons We can Learn from Big Data that are Often Discarded
  • Introduction
  • Economic Security and Educational Intelligence
  • Data Mining, Machine Learning, and Artificial Intelligence
  • ML+AI in Educational Technology
  • Technology and Data in Education
  • Machine Learning and Artificial Intelligence: Student Focus
  • Data Mining and Digital Education: Lessons to Learn
  • DATA MINING, MACHINE LEARNING, AND COMPARATIVE PERSPECTIVE
  • Data Mining, Educational Intelligence, and Comparative Analysis
  • Conclusion
  • Looking Ahead
  • References
  • Chapter 9: The Intricate Web of Educational Governance: The Cyborg Dialectic and Commodification of Knowledge
  • Introduction
  • Theoretical Framework
  • Methodology
  • The Web of Battelle
  • Origin Points
  • Battelle Memorial Institute
  • Battelle
  • Battelle Education
  • Battelle for Kids
  • Destination Points
  • Battelle Center for Science, Engineering, and Public Policy at Ohio State University (OSU)
  • Metro Early College High School (MECHS)
  • Ohio STEM Learning Network (OSLN)
  • STEM Learning Networks across the US
  • The Student Experience Survey
  • Formative Instructional Practices (FIP)
  • Global Education Study: Six Drivers of Student Success: A Look Inside of the World's Highest Performing School Systems
  • Summary
  • Conclusion
  • References
  • Chapter 10: Engineering the Mechanism/Repairing the Robot: Artificial Intelligence at the Intersection of Education and Industry
  • Artificial Intelligence across Education and Industry
  • Reimagining Two Occupations in the Automobile Industry
  • Automotive Engineers
  • Automotive Service Technicians and Mechanics
  • Artificial Intelligence: Governance, Challenges, and Responses
  • Conclusion
  • References
  • Chapter 11: Policy Development for an Educational Intelligent Economy in the European Union: An Illusory Prospect?
  • A Policy Riposte to Unrestrained Data Flows
  • The European Union as a Case for Comparison in the Era of Big Data
  • An Emerging European Policy Space for Data Regulation with Global Implications
  • Competing Policy Narratives: Fragmentation Versus Coherence
  • EU Policy Challenges in the Educational Intelligent Economy
  • Further Research Directions
  • References
  • Chapter 12: Haunted Data: The Colonial Residues of Transnational School Reforms in Kenya*
  • Ungrounding Data's Colonial Residues
  • Making up "the African:" School Reforms and Colonial Difference
  • Data as Infra-spectral and the Algorithmic Governance of Difference
  • The Haunted Data of an "Educational Intelligent Economy"
  • The Colonial Residues of Data-Driven Reforms
  • References
  • Chapter 13: Brave New World(s): Governing Clouds, Smart Schools, and the Rise of AIED
  • Introduction
  • Education 2030: Smart Governance Under Benevolent AI Clouds
  • On Bright Lights and Dark Shadows
  • Smarter Global Governance: Education after the Data Revolution
  • The "Chinese Dream": Smart Cities, Social Credit, and Smart Schools
  • Changing Winds: Toward the Chinese Dream
  • Smart Cities
  • Social Credit
  • Smart Schools
  • Discussion: Interwoven Worlds of Educational Intelligence
  • References
  • Chapter 14: Learning Analytics for Student Success at University: Trends and Dilemmas
  • Introduction
  • Defining Learning Analytics
  • Learning Analytics in Practice
  • Drivers of Learning Analytics Development
  • A community of Research and Practice
  • Higher Education Managers and Administrators
  • The Commercialization and Commodification of Learning Analytics
  • Charitable Foundations, Technology Networks, and Governments
  • Implications of Learning Analytics for Students, Educators, and Administrators
  • Conclusions and Future Directions
  • References
  • Index

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