Learning in Depth

Learning in Depth PDF

Author: Kieran Egan

Publisher: University of Chicago Press

Published: 2010

Total Pages: 231

ISBN-13: 0226190439

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Real education, Egan Explains, consists of both general knowledge and detailed understanding, and in Learning in Depth he outlines an ambitious, yet practical plan to incorporate deep knowledge into basic education. Under Egan's program, students will follow the usual curriculum, but with one crucial addition: beginning with their first days of school and continuing until graduation, they will each also study one topic-such as apples, birds, sacred buildings, mollusks, circuses, or stars-in depth. Over the years, with the help and guidance of their supervising teacher, students will expand their understanding of their one topic and build portfolios of knowledge that grow and change along with them. By the time they graduate each student will know as much about his or her topic as almost anyone on earth-and in the process will have learned important, even life-changing lessons about the meaning of expertise, the value of dedication, and the delight of knowing something in depth. --

Deconstructing Depth of Knowledge

Deconstructing Depth of Knowledge PDF

Author: Erik M. Francis

Publisher: Solution Tree Press

Published: 2021-11-05

Total Pages: 177

ISBN-13: 1951075161

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Depth of knowledge (DOK) has become a priority for many schools. But if your understanding of DOK is a little cloudy, you're not alone. This resource is your one-stop-shop for learning what it is, who it's for, and how to use and sustain it. Ultimately, you will discover how to plan and provide learning experiences that are academically rigorous, socially and emotionally supportive, and student responsive. Learn how DOK is a different, deeper way of approaching teaching and learning. Explore the different DOK levels and how they relate to instruction. Understand DOK's relationship with standards and assessment. Designate correct levels based on learning needs. Acquire strategies for helping students engage with DOK on a deeper level. Contents: Introduction: What Depth of Knowledge Is Not Chapter 1: What Exactly Is Depth of Knowledge? Chapter 2: What Are DOK Teaching and Learning Experiences? Chapter 3: How to Teach and Learn for Depth of Knowledge Chapter 4: How to Use Webb's DOK Levels as a Multi-Tiered System of Support Chapter 5: How to Deconstruct Learning Intentions for Depth of Knowledge Chapter 6: How to Designate the Depth of Knowledge Level Demanded Chapter 7: How to Construct DOK Learning Targets and Success Criteria Chapter 8: How to Ask and Address Good Questions for Depth of Knowledge Chapter 9: Let's Make a DOK! Conclusion References and Resources Index

Deep Active Learning

Deep Active Learning PDF

Author: Kayo Matsushita

Publisher: Springer

Published: 2017-09-12

Total Pages: 226

ISBN-13: 9811056609

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This is the first book to connect the concepts of active learning and deep learning, and to delineate theory and practice through collaboration between scholars in higher education from three countries (Japan, the United States, and Sweden) as well as different subject areas (education, psychology, learning science, teacher training, dentistry, and business).It is only since the beginning of the twenty-first century that active learning has become key to the shift from teaching to learning in Japanese higher education. However, “active learning” in Japan, as in many other countries, is just an umbrella term for teaching methods that promote students’ active participation, such as group work, discussions, presentations, and so on.What is needed for students is not just active learning but deep active learning. Deep learning focuses on content and quality of learning whereas active learning, especially in Japan, focuses on methods of learning. Deep active learning is placed at the intersection of active learning and deep learning, referring to learning that engages students with the world as an object of learning while interacting with others, and helps the students connect what they are learning with their previous knowledge and experiences as well as their future lives.What curricula, pedagogies, assessments and learning environments facilitate such deep active learning? This book attempts to respond to that question by linking theory with practice.

In Search of Deeper Learning

In Search of Deeper Learning PDF

Author: Jal Mehta

Publisher: Harvard University Press

Published: 2019-04-22

Total Pages: 465

ISBN-13: 0674988396

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"The best book on high school dynamics I have ever read."--Jay Mathews, Washington Post An award-winning professor and an accomplished educator take us beyond the hype of reform and inside some of America's most innovative classrooms to show what is working--and what isn't--in our schools. What would it take to transform industrial-era schools into modern organizations capable of supporting deep learning for all? Jal Mehta and Sarah Fine's quest to answer this question took them inside some of America's most innovative schools and classrooms--places where educators are rethinking both what and how students should learn. The story they tell is alternately discouraging and hopeful. Drawing on hundreds of hours of observations and interviews at thirty different schools, Mehta and Fine reveal that deeper learning is more often the exception than the rule. And yet they find pockets of powerful learning at almost every school, often in electives and extracurriculars as well as in a few mold-breaking academic courses. These spaces achieve depth, the authors argue, because they emphasize purpose and choice, cultivate community, and draw on powerful traditions of apprenticeship. These outliers suggest that it is difficult but possible for schools and classrooms to achieve the integrations that support deep learning: rigor with joy, precision with play, mastery with identity and creativity. This boldly humanistic book offers a rich account of what education can be. The first panoramic study of American public high schools since the 1980s, In Search of Deeper Learning lays out a new vision for American education--one that will set the agenda for schools of the future.

How We Think and Learn

How We Think and Learn PDF

Author: Jeanne Ellis Ormrod

Publisher: Cambridge University Press

Published: 2017-02-13

Total Pages: 239

ISBN-13: 1107165113

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This book introduces readers to principles and research findings about human learning and cognition in an engaging, conversational manner.

The Principles of Deep Learning Theory

The Principles of Deep Learning Theory PDF

Author: Daniel A. Roberts

Publisher: Cambridge University Press

Published: 2022-05-26

Total Pages: 473

ISBN-13: 1316519333

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This volume develops an effective theory approach to understanding deep neural networks of practical relevance.

The Art of Learning

The Art of Learning PDF

Author: Josh Waitzkin

Publisher: Simon and Schuster

Published: 2008-05-27

Total Pages: 291

ISBN-13: 0743277465

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An eight-time national chess champion and world champion martial artist shares the lessons he has learned from two very different competitive arenas, identifying key principles about learning and performance that readers can apply to their life goals. Reprint. 35,000 first printing.

An Imaginative Approach to Teaching

An Imaginative Approach to Teaching PDF

Author: Kieran Egan

Publisher: John Wiley & Sons

Published: 2005-02-04

Total Pages: 279

ISBN-13: 0470928484

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In this book, award-winning educator Kieran Egan shows how we can transform the experience of K-12 students and help them become more knowledgeable and more creative in their thinking. At the core of this transformative process is imagination which can become the heart of effective learning if it is tied to education's central tasks. An Imaginative Approach to Teaching is a groundbreaking book that offers an understanding of how students' imaginations work in learning and shows how the acquisition of cognitive tools drives students' educational development. This approach is unique in that it engages both the imagination and emotions. The author clearly demonstrates how knowledge comes to life in students' minds if it is introduced in the context of human hopes, fears, and passions. To facilitate this new educational approach, the book includes a wide variety of effective teaching tools - such as story, rhythm, play, opposition, agency, and meta-narrative understanding - that value and build upon the way children understand their experiences. Most important, Egan provides frameworks for lesson planning and more than a dozen sample lessons to show how teachers can use these tools to awaken intelligence and imagination in the classroom.

Learning and Understanding

Learning and Understanding PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2002-08-06

Total Pages: 588

ISBN-13: 030917080X

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This book takes a fresh look at programs for advanced studies for high school students in the United States, with a particular focus on the Advanced Placement and the International Baccalaureate programs, and asks how advanced studies can be significantly improved in general. It also examines two of the core issues surrounding these programs: they can have a profound impact on other components of the education system and participation in the programs has become key to admission at selective institutions of higher education. By looking at what could enhance the quality of high school advanced study programs as well as what precedes and comes after these programs, this report provides teachers, parents, curriculum developers, administrators, college science and mathematics faculty, and the educational research community with a detailed assessment that can be used to guide change within advanced study programs.

Learning from Data

Learning from Data PDF

Author: Vladimir Cherkassky

Publisher: John Wiley & Sons

Published: 2007-09-10

Total Pages: 560

ISBN-13: 9780470140512

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An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.