Introducing the Learning Sciences : Insights and Implications for Teaching

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Introducing the Learning Sciences : Insights and Implications for Teaching

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  • 製本 Hardcover:ハードカバー版/ページ数 258 p.
  • 言語 ENG
  • 商品コード 9781032029481

Full Description

Learning Sciences is a cutting-edge interdisciplinary field that investigates how people learn and applies these insights to improve educational practices. This essential textbook introduces the field with a focus on classroom teaching, making complex theories accessible and relevant to educators at all levels. By blending principled understanding with room for teachers' creativity and cultural adaptation, the book empowers educators to design learning experiences that engage and inspire students.

The book explores core aspects of learning - cognitive, constructive, socio-cultural, emotional and motivational, and representational - through a unique metaphor: teaching as architecture. Like architects, educators must balance evidence-based principles with their professional vision and adapt to diverse contexts and needs. Each chapter delves into foundational theories and evidence, drawing evidence from multiple methods and practices, before illustrating practical applications through metaphors and stories. It provides practical insights grounded in research, helping readers understand why their teaching works and offering a framework to refine their practice. The final chapter examines emerging trends, including critical perspectives and the impact of AI on education, offering a forward-looking view of the field.

This book is an invaluable resource for educators, teacher trainers, and students of education or Learning Sciences. Whether you are new to teaching or a seasoned professional, it will inspire you to design learning experiences that educate, captivate, and empower your students to reach their full potential.

Contents

1. Learning Sciences: An Introduction 2. Foundations of Cognition 3. Constructive Perspectives 4. Social and Cultural Essentials 5. Emotional and Motivational Learning 6. Representational Approaches 7. Conclusion

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