Q Tasks, 2nd Edition


Book Description

Questions and questioning are key skills in successful learning. The original Q Tasks was instrumental in showing teachers how to give students the tools they need to develop their own questions and build critical thinking and inquiry skills. This new, totally revised edition continues to nurture and advance these crucial skills, and also offers Q-task extensions that introduce digital components that facilitate collaboration and are designed to appeal to tech-savvy students. More than 100 practical, flexible exercises in this remarkable book provide a smorgasbord of choices for teachers to use to help students formulate good questions in an information-rich environment. They put the students at the centre of their own learning as they build the library and research skills that are essential to our information age. Teachers will find innovative ways to help students go beyond memorization and rote learning of facts to focus on personal understanding, and true ownership of the learning experience.




Ready, Set, Learn


Book Description

For the majority of students, the skills and work habits crucial to successful learning are not in place when they arrive at the school door. These skills must be explicitly taught by teachers who recognize the unique learning styles, preferences, and interests of their students. Ready, Set, Learn focuses on the importance of encouraging students to set their own learning goals and persevere to achieve them. It illustrates ways in which every lesson can be an opportunity for students to develop the skills and strategies they need in order to learn. Along with organizers, prompts, and specific activities, this timely book presents new ways to plan lessons that explicitly teach key learning skills, including organization, collaboration, communication, independence, memory, and initiative. This remarkable book shows how incorporating learning strategies into everyday work will improve students achievement, and create responsible, independent learners.




Take Me to Your Readers


Book Description

This thoughtful book is rooted in the belief that teachers can lead their students to develop their reading tastes and grow in their love of reading at the same time as supporting and stretching students in their meaning-making experiences. This practical resource highlights more than 50 instructional strategies that invite students to work inside and outside a book through reading, writing, talk, and arts experiences. It highlights the work of guest voices that include classroom teachers, occasional teachers, special education teachers, and librarians who share their best literacy practices. Take Me to Your Readers uses 5 essential areas to structure classroom experiences through children's literature: Motivation; Theme Connections; Genre Connections; Cross-Curricular Connections; and Response. Extensive booklists, teaching tips, a wide range of activities, and reproducible pages provide practical support. Ultimately, this book is designed to take teachers to their readers and start them on a lifelong journey through great books!




Deepening In-Class and Online Learning


Book Description

This timely book shows teachers how to make learning joyful as they translate successful classroom strategies to virtual learning. More than 60 step-by-step strategies encourage interaction, foster inclusion, and spark imagination. Each activity is presented in a consistent format, ready-to-use in-class and for online learning. Whether teaching virtually or adding digital activities to in-class instruction, this book explores effective ways for students to present, communicate, and collaborate. Innovative activities range from discussing hot topics and sharing personal stories to visual boards and digital storytelling. An up-to-date glossary of digital tools helps to make sense of the shifting landscape in today’s classrooms.




Guide To Temporal Networks, A (Second Edition)


Book Description

Network science offers a powerful language to represent and study complex systems composed of interacting elements — from the Internet to social and biological systems. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks and provides connections between the different areas of knowledge required to address this multi-disciplinary subject. After an introduction to key concepts on networks and stochastic dynamics, the authors guide the reader through a coherent selection of mathematical and computational tools for network dynamics. Perfect for students and professionals, this book is a gateway to an active field of research developing between the disciplines of applied mathematics, physics and computer science, with applications in others including social sciences, neuroscience and biology.This second edition extensively expands upon the coverage of the first edition as the authors expertly present recent theoretical and modelling progress in the emerging field of temporal networks, providing the keys to (and connections between) the different areas of knowledge required to address this multi-disciplinary problem.




Handbook of Mechanical Engineering, 2nd Edition


Book Description

Handbook of Mechanical Engineering is a comprehensive text for the students of B.E./B.Tech. and the candidates preparing for various competitive examination like IES/IFS/ GATE State Services and competitive tests conducted by public and private sector organization for selecting apprentice engineers.




Probability and Statistics for Computer Scientists, Second Edition


Book Description

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses. New to the Second Edition Axiomatic introduction of probability Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap More exercises at the end of each chapter Additional MATLAB® codes, particularly new commands of the Statistics Toolbox In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.




Contemporary Intellectual Assessment


Book Description

This leading practitioner reference and text--now in a revised and expanded fourth edition--provides the knowledge needed to use state-of-the-art cognitive tests with individuals of all ages, from preschoolers to adults. The volume examines major theories and tests of intelligence (in chapters written by the theorists and test developers themselves) and presents research-based approaches to test interpretation. Contributors address critical issues in evaluating culturally and linguistically diverse students, gifted students, and those with intellectual disability, sensory–motor impairments, traumatic brain injuries, and learning difficulties and disabilities. The fourth edition highlights the use of cognitive test results in planning school-based interventions. New to This Edition *Complete coverage of new or updated tests: WPPSI-IV, WISC-V, WISC-V Integrated, WJ IV, ECAD, CAS2, RIAS-2, KABC-II Normative Update, and UNIT2. *Chapters on cutting-edge approaches to identifying specific learning disabilities and reading disorders. *Chapters on brain imaging, neuropsychological intervention in schools, adult intellectual development, and DSM-5 criteria for learning disorders. *Updated chapters on theories of intelligence, their research base, and their clinical utility in guiding cognitive and neuropsychological assessment practice.




Classroom-Ready Rich Math Tasks, Grades 4-5


Book Description

Detailed plans for helping elementary students experience deep mathematical learning Do you work tirelessly to make your math lessons meaningful, challenging, accessible, and engaging? Do you spend hours you don’t have searching for, adapting, and creating tasks to provide rich experiences for your students that supplement your mathematics curriculum? Help has arrived! Classroom Ready-Rich Math Tasks for Grades 4-5 details more than 50 research- and standards-aligned, high-cognitive-demand tasks that will have your students doing deep-problem-based learning. These ready-to-implement, engaging tasks connect skills, concepts and practices, while encouraging students to reason, problem-solve, discuss, explore multiple solution pathways, connect multiple representations, and justify their thinking. They help students monitor their own thinking and connect the mathematics they know to new situations. In other words, these tasks allow students to truly do mathematics! Written with a strengths-based lens and an attentiveness to all students, this guide includes: • Complete task-based lessons, referencing mathematics standards and practices, vocabulary, and materials • Downloadable planning tools, student resource pages, and thoughtful questions, and formative assessment prompts • Guidance on preparing, launching, facilitating, and reflecting on each task • Notes on access and equity, focusing on students’ strengths, productive struggle, and distance or alternative learning environments. With concluding guidance on adapting or creating additional rich tasks for your students, this guide will help you give all of your students the deepest, most enriching and engaging mathematics learning experience possible.




Reinforcement Learning, second edition


Book Description

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.