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Produktbild: Quantum Learning

Quantum Learning Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

85,99 €

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Beschreibung

Produktdetails

ISBN

978-1-04-127226-7

Erscheinungsdatum

30.05.2026

Einband

Taschenbuch

Herausgeber

Ahmad A. Elngar + weitere

Verlag

Taylor & Francis

Seitenzahl

216

Maße (L/B)

28/21 cm

Sprache

Englisch

Beschreibung

Produktdetails

ISBN

978-1-04-127226-7

Erscheinungsdatum

30.05.2026

Einband

Taschenbuch

Herausgeber

Verlag

Taylor & Francis

Seitenzahl

216

Maße (L/B)

28/21 cm

Sprache

Englisch

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Quantum Learning

  • Chapter 1: Introduction
    1.1 The Evolution of Educational Technology
    1.2 Defining Quantum Learning
    1.3 The Need for a New Paradigm in Education
    1.4 Overview of Key Technologies: AI, Quantum Computing, and Data Science
    1.5 How to Use This Book
    Part I: Quantum Computing in Education
    Chapter 2: Understanding Quantum Computing
    2.1 The Basics of Quantum Computing: Qubits, Superposition, and Entanglement
    2.2 Classical vs. Quantum Computing: A Comparative Overview
    2.3 Potential Applications of Quantum Computing in Education
    2.4 Quantum Algorithms for Educational Data Processing
    2.5 Challenges and Opportunities in Quantum Education
    Chapter 3: Quantum Simulations in the Classroom
    3.1 Enhancing Science Education with Quantum Simulations
    3.2 Quantum Modeling for Complex Problem Solving
    3.3 Case Studies: Quantum Computing Projects in Schools and Universities
    Chapter 4: Preparing for the Quantum Future
    4.1 Curriculum Development for Quantum Computing Education
    4.2 Integrating Quantum Concepts into K-12 and Higher Education
    4.3 Teacher Training and Professional Development
    4.4 Quantum Literacy: Preparing Students for the Quantum Age
    Part II: Artificial Intelligence in Education
    Chapter 5: AI-Powered Personalized Learning
    5.1 The Role of AI in Personalizing Education
    5.2 Adaptive Learning Systems: Tailoring Education to Individual Needs
    5.3 AI in Learning Analytics: Monitoring and Enhancing Student Performance
    5.4 Implementing AI in Diverse Educational Settings
    Chapter 6: Intelligent Tutoring Systems and Virtual Classrooms
    6.1 The Rise of Intelligent Tutoring Systems
    6.2 AI in Virtual and Augmented Reality for Education
    6.3 Enhancing Student Engagement through AI-Powered Interactions
    6.4 Case Studies: AI-Driven Virtual Classrooms in Practice
    Chapter 7: Automation and Efficiency in Education
    7.1 Automating Administrative Tasks with AI
    7.2 AI in Grading and Assessment: Reducing Educator Workload
    7.3 Ethical Considerations in AI-Driven Educational Decisions
    7.4 The Future of AI in Educational Management
    Part III: Data Science and Educational Transformation
    Chapter 8: Data-Driven Decision Making in Education
    8.1 The Power of Data Science in Education
    8.2 Collecting and Analyzing Educational Data
    8.3 Predictive Analytics: Identifying At-Risk Students
    8.4 Data-Driven Curriculum Design and Evaluation
    Chapter 9: Enhancing Institutional Efficiency with Data Science
    9.1 Resource Optimization through Data Insights
    9.2 Data Science in Student Support Services
    9.3 Case Studies: Data-Driven Improvements in Educational Institutions
    9.4 Challenges in Implementing Data-Driven Approaches
    Chapter 10: Ethical Data Practices in Education
    10.1 Privacy Concerns and Data Security in Education
    10.2 Addressing Bias in Data-Driven Educational Tools
    10.3 Ensuring Transparency and Accountability in Educational Data Use
    10.4 Developing Ethical Guidelines for Data Science in Education
    Part IV: Interdisciplinary Approaches and Future Directions
    Chapter 11: Designing Interdisciplinary Curricula
    11.1 Integrating Quantum Computing, AI, and Data Science in Education
    11.2 Fostering Interdisciplinary Skills for the Future Workforce
    11.3 Collaborative Learning Platforms and Interdisciplinary Projects
    11.4 Preparing Students for Emerging Career Paths
    Chapter 12: Case Studies and Practical Applications
    12.1 Real-World Examples of Quantum Learning in Action
    12.2 Success Stories from Educational Institutions
    12.3 Lessons Learned: Challenges and Triumphs
    12.4 Insights for Future Implementation
    Chapter 13: Ethical Considerations and the Role of Educators
    13.1 Navigating the Ethical Landscape of Emerging Technologies
    13.2 The Educator's Role in Shaping Ethical Tech Use
    13.3 Preparing Students for Responsible Technology Use
    13.4 Building an Ethical Framework for Quantum Learning
    Chapter 14: The Future of Education in the Quantum Age
    14.1 Visioning the Future: Quantum Learning in 2030 and Beyond
    14.2 Emerging Trends and Technologies
    14.3 Global Impacts of Quantum Learning
    14.4 Preparing for Continuous Change in Education
    Conclusion
    15.1 Summarizing the Quantum Learning Framework
    15.2 The Road Ahead: Continuous Innovation in Education
    15.3 Final Thoughts and Call to Action
    Appendix