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. --

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

"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.

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

“All who are interested and concerned about educational reform and the improvement of schools will find this book a must read. It stimulates, it challenges, and it informs, such that the reader is most surely enriched by its plenitude.” Dr Shirley Hord, Scholar Emerita “At last we have a book of international cases to add to the literature on networks! Policymakers and practitioners alike will find the reasons why networks are fast becoming the reform organizations of choice. The book elevates network understanding to a new level.” Ann Lieberman, Senior Scholar at the Carnegie Foundationfor the Advancement of Teaching What is a professional learning community? What are the key challenges facing these communities and how might they be resolved? Is it time to extend our thinking about professional learning communities? There is great interest internationally in the potential of professional learning communities for enhancing educational reform efforts and sustaining improvement. This international collection expands perceptions and understanding of professional learning communities, as well as highlighting frequently neglected complexities and challenges. Drawing on research, each chapter offers a deeper understanding of topics such as distributed leadership, dialogue, organisational memory, trust, self-assessment and inquiry, and purpose linked to learning. The last section of the book focuses upon three of the most challenging dilemmas that face developing professional learning communities - developing professional learning communities in secondary school, building social capital, and sustaining professional learning communities. The authors provide pointers on why these challenges exist, offering rays of hope for ways forward. Professional Learning Communities is key international reading for education professionals, school practitioners, policymakers, academics and research students. It is a must-read for anyone interested in building capacity for sustainable learning and the ability to harness your community as a resource for change.

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.