This handbook provides teachers with practical tips and advice on improving literacy skills for students with low vision. The book provides easy-to-understand explanations of vital topics such as interpreting eye reports, performing functional vision assessments, working with low vision service providers, and more. The valuable resource section, tables, sample reports and sidebars offer essential information on assessing low vision students and helping them use their vision effectively.

Looking for Learning: Provocations is a full-colour, practical guide to inspire child-led learning that's linked to current policy and the EYFS framework. As each child progresses through their learning journey, Early Years practitioners are expected to identify and understand what learning is taking place in every activity that a child is involved in. Laura England, creator of Little Miss Early Years, uses her wealth of experience as an Early Years teacher to explore the learning that takes place when a child's play has been inspired by a provocation, including mirrors to investigate symmetry, cardboard boxes to understand shapes, and sticks and pebbles to construct their own designs. Provocations invite learning, interest and creativity as they allow children to explore, think and use their imaginations. This dip-in-and-out book is linked to the Characteristics of Effective Learning and presents case studies, real-life images and practical pointers to explore their use. With tips for setting up the environment to the adult's role in this child-led play, Looking for Learning: Provocations is ideal for all Early Years practitioners searching for accessible ideas for using provocations in their settings. Looking for Learning books are the number one tool for identifying learning opportunities in child-led play. All four books are packed full of tried-and-tested ideas for indoor and outdoor activities, helpful hints and tips and full-colour photographs. Written by Laura England, known as Little Miss Early Years, these are a must-have for any nursery or pre-school.

Looking for Learning: Loose Parts won "Highly Commended" in the Creative Play Awards 2019 for Teaching Resources. Looks for Learning: Loose Parts is a full-colour, practical guide to inspire child-led learning that's linked to to current policy and the EYFS framework. As each child progresses through their learning journey, Early Years practitioners are expected to identify and understand what learning is taking place in every activity that a child is involved in. Laura England, creator of Little Miss Early Years, uses her wealth of experience as an Early Years teacher to explore the learning that takes place when a child is tinkering with loose parts, including tinker trays filled with nuts and bolts, pompoms and play dough to combine, construct and investigate with. Loose parts are natural or synthetic materials and resources that have no pre-planned use; they can be moved, combined with other resources, lined up, deconstructed and constructed again. They can capture a child's imagination, curiosity and creativity as they play with and manipulate them. This dip-in-and-out book is linked to the Characteristics of Effective Learning and presents case studies, real-life images and practical pointers to explore their use. With tips for setting up the environment to the adult's role in this child-led play, Looking For Learning: Loose Parts is ideal for all Early Years practitioners searching for accessible ideas for using loose parts in their settings. Looking for Learning books are the number one tool for identifying learning opportunities in child-led play. All four books are packed full of tried-and-tested ideas for indoor and outdoor activities, helpful hints and tips and full-colour photographs. Written by Laura England, known as Little Miss Early Years, these are a must-have for any nursery or pre-school.

Slow Looking provides a robust argument for the importance of slow looking in learning environments both general and specialized, formal and informal, and its connection to major concepts in teaching, learning, and knowledge. A museum-originated practice increasingly seen as holding wide educational benefits, slow looking contends that patient, immersive attention to content can produce active cognitive opportunities for meaning-making and critical thinking that may not be possible though high-speed means of information delivery. Addressing the multi-disciplinary applications of this purposeful behavioral practice, this book draws examples from the visual arts, literature, science, and everyday life, using original, real-world scenarios to illustrate the complexities and rewards of slow looking.

A bold, brain-based teaching approach to culturally responsive instruction To close the achievement gap, diverse classrooms need a proven framework for optimizing student engagement. Culturally responsive instruction has shown promise, but many teachers have struggled with its implementation—until now. In this book, Zaretta Hammond draws on cutting-edge neuroscience research to offer an innovative approach for designing and implementing brain-compatible culturally responsive instruction. The book includes: Information on how one’s culture programs the brain to process data and affects learning relationships Ten “key moves” to build students’ learner operating systems and prepare them to become independent learners Prompts for action and valuable self-reflection

Looking in Classrooms uses educational, psychological, and social science theories and classroom-based research to teach future classroom teachers about the complexities and demands of classroom instruction. While maintaining the core approach of the first ten editions, the book has been thoroughly revised and updated with new research-based content on teacher evaluation, self-assessment, and decision-making; special emphases on teaching students from diverse ethnic, cultural, class, and gender-identity contexts; and rich suggestions for integrating technology into classroom instruction. Widely considered to be the most comprehensive and authoritative source available on effective, successful teaching, Looking in Classrooms synthesizes the knowledge base on student motivation, classroom management, teacher expectations, teacher effectiveness, adaptive instruction for individual learners, and informative observational techniques for enhancing teaching. It addresses key topics in classroom instruction in an accessible fashion, promoting easy intepretation and transfer to practice, and articulates the roles of teacher-centered pedagogy, student-centered instruction, and project-based learning in today‘s classroom. Guided by durable historical knowledge as well as dynamic, emerging conceptions of teaching, this text is ideal for undergraduate teacher training programs and for masters-level courses for teachers, administrators, and superintendents.

Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. About the book Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you’ll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you’ll work with core algorithms, including deep Q-networks and policy gradients, along with industry-standard tools like PyTorch and OpenAI Gym. What's inside Building and training DRL networks The most popular DRL algorithms for learning and problem solving Evolutionary algorithms for curiosity and multi-agent learning All examples available as Jupyter Notebooks About the reader For readers with intermediate skills in Python and deep learning. About the author Alexander Zai is a machine learning engineer at Amazon AI. Brandon Brown is a machine learning and data analysis blogger. Table of Contents PART 1 - FOUNDATIONS 1. What is reinforcement learning? 2. Modeling reinforcement learning problems: Markov decision processes 3. Predicting the best states and actions: Deep Q-networks 4. Learning to pick the best policy: Policy gradient methods 5. Tackling more complex problems with actor-critic methods PART 2 - ABOVE AND BEYOND 6. Alternative optimization methods: Evolutionary algorithms 7. Distributional DQN: Getting the full story 8.Curiosity-driven exploration 9. Multi-agent reinforcement learning 10. Interpretable reinforcement learning: Attention and relational models 11. In conclusion: A review and roadmap