As many as one in 20 children struggles with sensory issues. To address these needs in the classroom, sensory integration has become a staple in early education. This book is sure to be every teacher's bible of sensory activities.

Digital Learning in Motion provides a theoretical analysis of learning and related learning media in society. The book explores how changing media affects learning environments, which changes the learning itself, showing that learning is always in motion. This book expounds upon the concept of learning, reconstructing how learning unfolds and analyzing the discourse around pedagogy and Bildung in the age of new digital media. It further discusses in detail the threefold relationship between learning and motion, considering how learning is based on motion, generated by new experiences and changes with the environment and through its own mediatization. The book presents a normative model that outlines how learning can be structured on the basis of society’s values and self-understanding discourses in the digital age. This book will be of great interest for academics, postgraduate students, and researchers in the fields of digital learning and inclusion, education research, educational theory, communication and cultural studies.

Knowledge in Motion brings together archaeologists, historians, and cultural anthropologists to examine communities from around the globe as they engage in a range of practices constituting situated learned and knowledge transmission. The contributors lay the groundwork to forge productive theories and methodologies for exploring situated learning and its broad-ranging outcomes.

Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

Scientists have found that moving the body maximizes brainpower and that even simple movements can bring about improvement in a child's memory and concentration levels. This packet is a compilation of games that get students up and moving in the classroom; all of which can be adapted to current curriculum and used for most subject areas.

Engage students in grade K while connecting physical activity, good health, and learning using Learning in Motion. Teach basic language arts and math skills with more than 40 activities that help students build physical and mental muscle. These age-appropriate activities cover reading, writing, speaking, listening, and math. The activities focus on concepts of print, syllables, rhyming words, vowels, sight words, capitalization, punctuation, following directions, counting, measurement, sorting, and patterns. These activities support NCTE and NCTM standards while developing flexibility, strength, and endurance. This 80-page book aligns with state, national, and Canadian provincial standards and includes a parent letter and instructions for creating easy-to-use, low-cost activity equipment.

An eminent psychologist offers a major new theory of human cognition: movement, not language, is the foundation of thought When we try to think about how we think, we can't help but think of words. Indeed, some have called language the stuff of thought. But pictures are remembered far better than words, and describing faces, scenes, and events defies words. Anytime you take a shortcut or play chess or basketball or rearrange your furniture in your mind, you've done something remarkable: abstract thinking without words. In Mind in Motion, psychologist Barbara Tversky shows that spatial cognition isn't just a peripheral aspect of thought, but its very foundation, enabling us to draw meaning from our bodies and their actions in the world. Our actions in real space get turned into mental actions on thought, often spouting spontaneously from our bodies as gestures. Spatial thinking underlies creating and using maps, assembling furniture, devising football strategies, designing airports, understanding the flow of people, traffic, water, and ideas. Spatial thinking even underlies the structure and meaning of language: why we say we push ideas forward or tear them apart, why we're feeling up or have grown far apart. Like Thinking, Fast and Slow before it, Mind in Motion gives us a new way to think about how--and where--thinking takes place.