Computational Thinking Education 1st edition by Siu-Cheung Kong, Harold Abelson ISBN 981136527X  978-9811365270

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ISBN 10: 981136527X
ISBN 13:  978-9811365270
Author: Siu-Cheung Kong, Harold Abelson

This This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.

Computational Thinking Education 1st Table of contents:

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Part I: Understanding Computational Thinking

Chapter 1: What is Computational Thinking?

• Definition and origins of computational thinking

• Key concepts: Algorithms, Decomposition, Pattern Recognition, Abstraction, and Evaluation

• The role of computational thinking in problem solving

Chapter 2: Computational Thinking and the Curriculum

• Incorporating computational thinking into K-12 education

• Cross-disciplinary applications of computational thinking

• Benefits of computational thinking for students and educators

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Part II: Teaching Computational Thinking

Chapter 3: Tools and Techniques for Teaching Computational Thinking

• Programming languages and environments for teaching (e.g., Scratch, Python)

• Visual programming tools for beginners

• Robotics, game design, and simulations

Chapter 4: Pedagogical Approaches

• Active learning and inquiry-based learning

• Project-based learning for computational thinking

• Collaborative and interdisciplinary teaching

Chapter 5: Designing Curriculum for Computational Thinking

• Curriculum models and frameworks

• Assessing computational thinking in students

• Adapting lessons for various age groups and skill levels

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Part III: Applications of Computational Thinking

Chapter 6: Computational Thinking in STEM Education

• Integrating computational thinking into science, technology, engineering, and mathematics (STEM)

• Problem-solving with computational thinking in scientific research

• Computational thinking in data science and engineering

Chapter 7: Computational Thinking in the Arts and Humanities

• Using computational thinking for creativity and design

• Applications in literature, music, and visual arts

• Digital humanities and computational methods in the humanities

Chapter 8: Computational Thinking for Real-World Problems

• Case studies of computational thinking in solving social issues

• Projects focused on healthcare, environmental sustainability, and economics

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Part IV: Challenges and Future Directions

Chapter 9: Overcoming Challenges in Teaching Computational Thinking

• Addressing barriers in diverse educational settings

• Managing access to technology and resources

• Encouraging students from underrepresented groups

Chapter 10: The Future of Computational Thinking Education

• Emerging trends in computational thinking

• The role of artificial intelligence, machine learning, and data analytics

• Preparing students for careers in technology and beyond

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Appendices

• A. Glossary of Terms

• B. Recommended Resources and Tools for Educators

• C. Further Reading

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