Artificial Intelligence is at the top of the agenda for education leaders, scientists, technologists and policy makers in educating the next generation across the globe. Beyond applying AI in daily life applications and educational tools, understanding how to learn and teach AI is increasingly important. Despite these emerging technology breakthroughs, AI learning is still new to educators especially to K-16 teachers. There is a lack of evidence-based studies that inform them about AI learning, including design principles for building a set of curriculum content, and pedagogical approaches as well as technological tools. Teaching AI concepts and techniques from programming languages and developmentally appropriate learning tools (e.g., robotics, serious games, software, intelligent agents) across different education levels emerged in recent years. The primary purpose of this book is to respond to the need to conceptualize the emerging term “AI literacy” and investigate how to teach and learn AI in K-16 education settings.
This book examines different aspects of learning artefacts, pedagogies, content knowledge and assessment methods of AI literacy education, from theoretical discussions to practical recommendations for curriculum and instructional design. An exhaustive summary of current evidence with examples is illustrated in this book, as well as cutting-edge research that serves as an AI literacy model for different countries’ contexts. Part I, “Conceptualizing AI literacy”, provides a detailed discussion on the development of the concepts and frameworks on AI literacy education, discusses the differences and similarities between AI in education (AIED) and AI literacy education, and illustrates the reasons why K-16 students need to learn AI. These concepts are brought together in Part II, “K-16 AI literacy education” to further summarize the pedagogies, learning content, learning tools and assessment methods to inform K-16 educators how to design their AI instruction at each education level. After that, part III “AI literacy for instructional designers” explores how instructional designers (i.e., AI developers and teachers) prepare themselves to become ready to design developmentally appropriate tools, platforms, services and curricula to empower students with AI literacy skills.
Author(s): Davy Tsz Kit Ng, Jac Ka Lok Leung, Maggie Jiahong Su, Iris Heung Yue Yim, Maggie Shen Qiao, Samuel Kai Wah Chu
Publisher: Springer
Year: 2022
Language: English
Pages: 152
City: Cham
Foreword
Foreword 2
About the Book
Contents
Part I: Conceptualizing AI Literacy
Chapter 1: Introduction
1.1 Key Inquiry Questions
1.2 Organization
References
Chapter 2: AI Education and AI Literacy
2.1 A Historical Perspective
2.2 AI Education Versus AI Literacy
2.2.1 Artificial Intelligence in Education
2.2.2 Artificial Intelligence Literacy
2.2.3 Similarities and Differences Between AIED and AI Literacy
2.3 Conclusion
References
Chapter 3: AI Literacy for All
3.1 AI for Living, Workplace, Learning, and Societal Good
3.1.1 AI for Living
3.1.2 AI for Workplaces
3.1.3 AI for Learning
3.1.4 AI for Societal Good
3.2 Benefits of AI Literacy for Different Educational Levels
3.2.1 Kindergarteners
3.2.2 Primary and Secondary Education
3.2.3 Noncomputer Science University Students
3.3 Conclusion
References
Chapter 4: The Landscape of AI Literacy
4.1 AI Literacy as a Twenty-First Century Skill
4.2 Emerging Frameworks for AI Literacy Education
4.2.1 Competencies and Design Considerations
4.2.2 The Five “Big Ideas” About AI
4.2.3 Other Review Papers in AI Literacy Education
4.3 Rising Publications on AI Literacy Education
4.3.1 AI Literacy Education for K–12 Students
4.3.2 AI Literacy Education for Noncomputer Science University Students
4.4 New Education Policies on AI Literacy Across the Globe
4.5 Our Three Proposals of AI Literacy Educational Frameworks (Bloom’s, TPACK, P21)
4.5.1 AI Literacy and Bloom’s Taxonomy
4.5.2 AI Literacy and TPACK Framework
4.5.3 AI Literacy and P21’s Framework for the 21st Century Learning
4.6 Conclusion
References
Part II: K-16 AI Literacy Education
Chapter 5: AI Literacy Education in Early Childhood Education
5.1 Introduction
5.2 Methods
5.3 Results and Discussion
5.4 Conclusion
References
Chapter 6: AI Literacy Education in Primary Schools
6.1 Method
6.2 Results and Discussion
6.3 Conclusions
References
Chapter 7: AI Literacy Education in Secondary Schools
7.1 Method
7.2 Results and Discussion
7.3 Conclusions
References
Chapter 8: AI Literacy Education for Nonengineering Undergraduates
8.1 Methodology
8.1.1 Data Collection
8.1.2 Data Analysis
8.2 Results and Discussion
8.3 Conclusion
References
Part III: AI Literacy for Instructional Designers
Chapter 9: AI Literacy on Human-Centered Considerations
9.1 Overview
9.2 Needs of HCAI in Educational Fields
9.3 Key Elements of Human-Centered Considerations
9.3.1 Human Factor Designs and Values
9.3.2 Reflect Human Intelligence
9.3.3 Ethical and Responsible Design
9.3.4 AI Under Human Control and Under Human Conditions
9.4 Scaffolding Support
9.4.1 Knowing Learners’ Backgrounds
9.4.2 Knowing Learners’ Interests and Motivation
9.4.3 Knowing Students’ Learning Progress
9.4.4 Parental Involvement
References
Chapter 10: AI Literacy from Educators’ Perspectives
10.1 Understanding Teachers’ AI Digital Competencies
10.2 Essential AI Digital Competencies for Educators (P21)
10.3 Conclusion
References
Chapter 11: Summary and Conclusions
11.1 For Teachers
11.2 For Higher Education Faculty
11.3 For Policymakers
11.4 Parents
11.5 Researchers and Developers
11.6 What Is Next?
References
