Download The Neural Teaching Guide full books in PDF, epub, and Kindle. Read online The Neural Teaching Guide ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
The Neural Teaching Guide showcases the innovative practices of K-12 teachers who are effectively applying findings from educational neuroscience into their classrooms. Educators today have remarkable opportunities to understand how the complex and often malleable functions of the brain affect learning, behavior, and social-emotional dynamics, but what practical strategies come out of this information? Authored by in-service teachers around the country, this book showcases a variety of brain-based approaches – cutting-edge yet intuitive, evidence-based yet accessibly translated – to helping children realize their potential at school. Both novice and veteran K-12 teachers alike will be reinvigorated to enhance students’ engagement and curiosity, nurture positive behaviors and self-regulation, support interest-based activities and inclusive interactions, identify biases and struggles, and more.
Book Synopsis The Neural Teaching Guide by : Kieran O'Mahony
Download or read book The Neural Teaching Guide written by Kieran O'Mahony and published by Taylor & Francis. This book was released on 2024-06-17 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Neural Teaching Guide showcases the innovative practices of K-12 teachers who are effectively applying findings from educational neuroscience into their classrooms. Educators today have remarkable opportunities to understand how the complex and often malleable functions of the brain affect learning, behavior, and social-emotional dynamics, but what practical strategies come out of this information? Authored by in-service teachers around the country, this book showcases a variety of brain-based approaches – cutting-edge yet intuitive, evidence-based yet accessibly translated – to helping children realize their potential at school. Both novice and veteran K-12 teachers alike will be reinvigorated to enhance students’ engagement and curiosity, nurture positive behaviors and self-regulation, support interest-based activities and inclusive interactions, identify biases and struggles, and more.
We are constantly learning, either we want or not. Learning is very natural to our brains, and it is (or it should be) enjoyable. What is the best way then to learn about effective learning? Making the process simple and fun. Cartoons are a very effective method because we learn with stories, we learn with observations and being part of a narrative. This is the idea of the authors, Harvard Professor and neuroscientist Felipe Fregni and Federal University of Sao Paulo Professor of Systems Thinking Joao Arantes, when they got together to write this cartoon book about learning and how to use this knowledge in teaching practices.This book follows the book of Critical Thinking in Teaching and Learning (Felipe Fregni, 2019) and in 191 cartoons the authors show using funny and simple illustrations the basic neural principles of learning (including the basic principles of neuroplasticity, how we encode new information, the attentional system and learning, memory and learning, the critical importance of our motivation system and how to activate that in educational programs, how stress affect (or help) learning and the use of social interaction in educational programs) and how to apply these principles for teaching (including teaching methods (student-centered vs. teacher-centered methods), online teaching, teaching critical thinking and assessments).We all need to become better learners, especially in a society when fact memorization is no longer important. This book is, therefore, an essential guide to every student and teacher looking to improving their own and their students learning experience.
Book Synopsis The Cartoon Guide to Effective Teaching and Learning by : João Arantes
Download or read book The Cartoon Guide to Effective Teaching and Learning written by João Arantes and published by . This book was released on 2020-06-04 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are constantly learning, either we want or not. Learning is very natural to our brains, and it is (or it should be) enjoyable. What is the best way then to learn about effective learning? Making the process simple and fun. Cartoons are a very effective method because we learn with stories, we learn with observations and being part of a narrative. This is the idea of the authors, Harvard Professor and neuroscientist Felipe Fregni and Federal University of Sao Paulo Professor of Systems Thinking Joao Arantes, when they got together to write this cartoon book about learning and how to use this knowledge in teaching practices.This book follows the book of Critical Thinking in Teaching and Learning (Felipe Fregni, 2019) and in 191 cartoons the authors show using funny and simple illustrations the basic neural principles of learning (including the basic principles of neuroplasticity, how we encode new information, the attentional system and learning, memory and learning, the critical importance of our motivation system and how to activate that in educational programs, how stress affect (or help) learning and the use of social interaction in educational programs) and how to apply these principles for teaching (including teaching methods (student-centered vs. teacher-centered methods), online teaching, teaching critical thinking and assessments).We all need to become better learners, especially in a society when fact memorization is no longer important. This book is, therefore, an essential guide to every student and teacher looking to improving their own and their students learning experience.
This book is designed to enable the reader to design and run a neural network-based project. It presents everything the reader will need to know to ensure the success of such a project. The book contains a free disk with C and C++ programs, which implement many of the techniques discussed in the book.
Book Synopsis Applying Neural Networks by : Kevin Swingler
Download or read book Applying Neural Networks written by Kevin Swingler and published by Morgan Kaufmann. This book was released on 1996 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to enable the reader to design and run a neural network-based project. It presents everything the reader will need to know to ensure the success of such a project. The book contains a free disk with C and C++ programs, which implement many of the techniques discussed in the book.
Download or read book The Brain in Space written by and published by . This book was released on 1998 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
A step-by-step guide for teachers to the benefits of visual note-taking and how to incorporate it in their classrooms. We've come a long way from teachers admonishing students to put away their drawings and take traditional long-form notes. Let's be honest: note-taking is boring and it isn't always the most effective way to retain information. This book is a guide for teachers about getting your students drawing and sketching to learn visually. Whether in elementary school or high school, neuroscience has shown that visual learning is a very effective way to retain information. The techniques in this book will help you work with your students in novel ways to retain information. Visual note-taking can be used with diverse learners; all ages; and those who have no drawing experience. Teachers are provided with a library of images and concepts to steal, tweak, and use in any way in their classrooms. The book is liberally illustrated with student examples from elementary and high school students alike.
Book Synopsis Visual Note-Taking for Educators: A Teacher's Guide to Student Creativity by : Wendi Pillars
Download or read book Visual Note-Taking for Educators: A Teacher's Guide to Student Creativity written by Wendi Pillars and published by W. W. Norton & Company. This book was released on 2015-11-30 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide for teachers to the benefits of visual note-taking and how to incorporate it in their classrooms. We've come a long way from teachers admonishing students to put away their drawings and take traditional long-form notes. Let's be honest: note-taking is boring and it isn't always the most effective way to retain information. This book is a guide for teachers about getting your students drawing and sketching to learn visually. Whether in elementary school or high school, neuroscience has shown that visual learning is a very effective way to retain information. The techniques in this book will help you work with your students in novel ways to retain information. Visual note-taking can be used with diverse learners; all ages; and those who have no drawing experience. Teachers are provided with a library of images and concepts to steal, tweak, and use in any way in their classrooms. The book is liberally illustrated with student examples from elementary and high school students alike.
Dr Shore has produced a well-informed, highly readable book that has potential for substantially influencing a number of critical educational issues.
Book Synopsis Baby Teacher by : Rebecca Shore
Download or read book Baby Teacher written by Rebecca Shore and published by R&L Education. This book was released on 2002-05 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr Shore has produced a well-informed, highly readable book that has potential for substantially influencing a number of critical educational issues.
Discusses biological and artificial neural networks, neural network learning and instructional practice.
Book Synopsis A Neural Network Guide to Teaching by : Justine C. Baker
Download or read book A Neural Network Guide to Teaching written by Justine C. Baker and published by . This book was released on 1998 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discusses biological and artificial neural networks, neural network learning and instructional practice.
Compatible with other professional development programs, this model shows how to apply relevant research from educational and cognitive neuroscience to classroom settings through a pedagogical framework. The model's six components are: 1) Establish the emotional connection to learning; 2) Develop the physical learning environment; 3) Design the learning experience; 4) Teach for the mastery of content, skills, and concepts; 5) Teach for the extension and application of knowledge; 6) Evaluate learning. --Book cover.
Book Synopsis The Brain-Targeted Teaching Model for 21st-Century Schools by : Mariale M. Hardiman
Download or read book The Brain-Targeted Teaching Model for 21st-Century Schools written by Mariale M. Hardiman and published by Corwin Press. This book was released on 2012-02-15 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compatible with other professional development programs, this model shows how to apply relevant research from educational and cognitive neuroscience to classroom settings through a pedagogical framework. The model's six components are: 1) Establish the emotional connection to learning; 2) Develop the physical learning environment; 3) Design the learning experience; 4) Teach for the mastery of content, skills, and concepts; 5) Teach for the extension and application of knowledge; 6) Evaluate learning. --Book cover.
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
Book Synopsis Neural Networks and Deep Learning by : Charu C. Aggarwal
Download or read book Neural Networks and Deep Learning written by Charu C. Aggarwal and published by Springer. This book was released on 2018-08-25 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
Download or read book The Brain in Space written by and published by . This book was released on 1998 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
