Download or read book Learning in Depth written by Kieran Egan and published by University of Chicago Press. This book was released on 2010 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. --
Download or read book Deconstructing Depth of Knowledge written by Erik M. Francis and published by Solution Tree Press. This book was released on 2021-11-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book In Search of Deeper Learning written by Jal Mehta and published by Harvard University Press. This book was released on 2019-04-22 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Download or read book Imaginative Education written by Kieran Egan and published by . This book was released on 2010 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Professional Learning Communities written by Louise Stoll and published by McGraw-Hill Education (UK). This book was released on 2007-03-16 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: “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.
Download or read book Deep Active Learning written by Kayo Matsushita and published by Springer. This book was released on 2017-09-12 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Principles of Deep Learning Theory written by Daniel A. Roberts and published by Cambridge University Press. This book was released on 2022-05-26 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Download or read book Swift in Depth written by Tjeerd in 't Veen and published by Simon and Schuster. This book was released on 2018-12-10 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Now updated for Swift 5! Swift is more than just a fun language to build iOS applications with. It features a host of powerful tools that, if effectively used, can help you create even better apps with clean, crystal-clear code and awesome features. Swift in Depth is designed to help you unlock these tools and quirks and get developing next-gen apps, web services, and more! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology It's fun to create your first toy iOS or Mac app in Swift. Writing secure, reliable, professional-grade software is a different animal altogether. The Swift language includes an amazing set of high-powered features, and it supports a wide range of programming styles and techniques. You just have to roll up your sleeves and learn Swift in depth. About the Book Swift in Depth guides you concept by concept through the skills you need to build professional software for Apple platforms, such as iOS and Mac; also on the server with Linux. By following the numerous concrete examples, enlightening explanations, and engaging exercises, you'll finally grok powerful techniques like generics, efficient error handling, protocol-oriented programming, and advanced Swift patterns. Author Tjeerd in 't Veen reveals the high-value, difficult-to-discover Swift techniques he's learned through his own hard-won experience. What's inside Covers Swift 5 Writing reusable code with generics Iterators, sequences, and collections Protocol-oriented programming Understanding map, flatMap, and compactMap Asynchronous error handling with ResultBest practices in Swift About the Reader Written for advanced-beginner and intermediate-level Swift programmers. About the Author Tjeerd in 't Veen is a senior software engineer and architect in the mobile division of a large international banking firm. Table of Contents Introducing Swift in depth Modeling data with enums Writing cleaner properties Making optionals second nature Demystifying initializers Effortless error handling Generics Putting the pro in protocol-oriented programming Iterators, sequences, and collections Understanding map, flatMap, and compactMap Asynchronous error handling with Result Protocol extensions Swift patterns Delivering quality Swift code Where to Swift from here
Download or read book The Art of Learning written by Josh Waitzkin and published by Simon and Schuster. This book was released on 2008-05-27 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Learning How to Learn written by Barbara Oakley, PhD and published by Penguin. This book was released on 2018-08-07 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
Download or read book How We Think and Learn written by Jeanne Ellis Ormrod and published by Cambridge University Press. This book was released on 2017-02-13 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to principles and research findings about human learning and cognition in an engaging, conversational manner.
Download or read book A Walking Curriculum written by Gillian Judson and published by . This book was released on 2018 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book What the Best College Teachers Do written by Ken Bain and published by Harvard University Press. This book was released on 2011-09-01 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: What makes a great teacher great? Who are the professors students remember long after graduation? This book, the conclusion of a fifteen-year study of nearly one hundred college teachers in a wide variety of fields and universities, offers valuable answers for all educators. The short answer is—it’s not what teachers do, it’s what they understand. Lesson plans and lecture notes matter less than the special way teachers comprehend the subject and value human learning. Whether historians or physicists, in El Paso or St. Paul, the best teachers know their subjects inside and out—but they also know how to engage and challenge students and to provoke impassioned responses. Most of all, they believe two things fervently: that teaching matters and that students can learn. In stories both humorous and touching, Ken Bain describes examples of ingenuity and compassion, of students’ discoveries of new ideas and the depth of their own potential. What the Best College Teachers Do is a treasure trove of insight and inspiration for first-year teachers and seasoned educators.
Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Download or read book Whole Class Mathematics Discussions written by Teruni Lamberg and published by Allyn & Bacon. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filled with research-based ideas, practical strategies and tools, this book and the accompanying website supports teachers in facilitating effective whole class discussions to enhance K-8 students' mathematical understanding.
