Understanding Applied Learning


Book Description

Understanding Applied Learning enables teachers, lecturers and educators to facilitate applied learning effectively with learners in schools, colleges and universities. It introduces teachers to the concept of applied learning in practice, cutting across any vocational and academic divide to show how this approach supports high-quality and effective outcomes for learners. Applied learning prepares and equips learners for life in the twenty-first century and lifelong learning. Offering practical guidance on why and how to adopt applied learning in all post-primary settings, this practical resource introduces and explores the core concepts, practices and benefits of using this approach. Illustrated with real-life scenarios, it examines why applied learning is relevant today, how it enables learners to connect knowledge with new situations, how to navigate and solve intellectual and skills-based problems and how to work collaboratively and develop higher-level thinking skills. Key topics covered include: A range of applied learning theories and strategies Relevant, Engaging, Active Learning (REAL) for successful knowledge and skills development The relevance of applied learning to employers Overcoming issues in embedding applied learning approaches How to embed creativity into learning experiences. Understanding Applied Learning is an authoritative, down-to-earth guide to facilitate applied learning effectively and successfully with students in secondary schools, colleges and universities. It is a source of support and inspiration for all those committed to high-quality and effective outcomes for learners.




Getting Smart


Book Description

A comprehensive look at the promise and potential of online learning In our digital age, students have dramatically new learning needs and must be prepared for the idea economy of the future. In Getting Smart, well-known global education expert Tom Vander Ark examines the facets of educational innovation in the United States and abroad. Vander Ark makes a convincing case for a blend of online and onsite learning, shares inspiring stories of schools and programs that effectively offer "personal digital learning" opportunities, and discusses what we need to do to remake our schools into "smart schools." Examines the innovation-driven world, discusses how to combine online and onsite learning, and reviews "smart tools" for learning Investigates the lives of learning professionals, outlines the new employment bargain, examines online universities and "smart schools" Makes the case for smart capital, advocates for policies that create better learning, studies smart cultures




Handbook of Research on Applied Learning Theory and Design in Modern Education


Book Description

The field of education is in constant flux as new theories and practices emerge to engage students and improve the learning experience. Research advances help to make these improvements happen and are essential to the continued improvement of education. The Handbook of Research on Applied Learning Theory and Design in Modern Education provides international perspectives from education professors and researchers, cyberneticists, psychologists, and instructional designers on the processes and mechanisms of the global learning environment. Highlighting a compendium of trends, strategies, methodologies, technologies, and models of applied learning theory and design, this publication is well-suited to meet the research and practical needs of academics, researchers, teachers, and graduate students as well as curriculum and instructional design professionals.




How People Learn


Book Description

First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from the original book can translate into actions and practice, now making a real connection between classroom activities and learning behavior. This edition includes far-reaching suggestions for research that could increase the impact that classroom teaching has on actual learning. Like the original edition, this book offers exciting new research about the mind and the brain that provides answers to a number of compelling questions. When do infants begin to learn? How do experts learn and how is this different from non-experts? What can teachers and schools do-with curricula, classroom settings, and teaching methodsâ€"to help children learn most effectively? New evidence from many branches of science has significantly added to our understanding of what it means to know, from the neural processes that occur during learning to the influence of culture on what people see and absorb. How People Learn examines these findings and their implications for what we teach, how we teach it, and how we assess what our children learn. The book uses exemplary teaching to illustrate how approaches based on what we now know result in in-depth learning. This new knowledge calls into question concepts and practices firmly entrenched in our current education system. Topics include: How learning actually changes the physical structure of the brain. How existing knowledge affects what people notice and how they learn. What the thought processes of experts tell us about how to teach. The amazing learning potential of infants. The relationship of classroom learning and everyday settings of community and workplace. Learning needs and opportunities for teachers. A realistic look at the role of technology in education.




Applied Data Science


Book Description

This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.




Applied Machine Learning


Book Description

Machine learning methods are now an important tool for scientists, researchers, engineers and students in a wide range of areas. This book is written for people who want to adopt and use the main tools of machine learning, but aren’t necessarily going to want to be machine learning researchers. Intended for students in final year undergraduate or first year graduate computer science programs in machine learning, this textbook is a machine learning toolkit. Applied Machine Learning covers many topics for people who want to use machine learning processes to get things done, with a strong emphasis on using existing tools and packages, rather than writing one’s own code. A companion to the author's Probability and Statistics for Computer Science, this book picks up where the earlier book left off (but also supplies a summary of probability that the reader can use). Emphasizing the usefulness of standard machinery from applied statistics, this textbook gives an overview of the major applied areas in learning, including coverage of:• classification using standard machinery (naive bayes; nearest neighbor; SVM)• clustering and vector quantization (largely as in PSCS)• PCA (largely as in PSCS)• variants of PCA (NIPALS; latent semantic analysis; canonical correlation analysis)• linear regression (largely as in PSCS)• generalized linear models including logistic regression• model selection with Lasso, elasticnet• robustness and m-estimators• Markov chains and HMM’s (largely as in PSCS)• EM in fairly gory detail; long experience teaching this suggests one detailed example is required, which students hate; but once they’ve been through that, the next one is easy• simple graphical models (in the variational inference section)• classification with neural networks, with a particular emphasis onimage classification• autoencoding with neural networks• structure learning




How Learning Works


Book Description

Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning




Applied Machine Learning


Book Description

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical style, the book covers a broad array of machine learning topics with special emphasis on methods that have been profitably employed. Coverage includes: •Supervised learning•Statistical learning•Learning with support vector machines (SVM)•Learning with neural networks (NN)•Fuzzy inference systems•Data clustering•Data transformations•Decision tree learning•Business intelligence•Data mining•And much more




Strategies in Learning and Using a Second Language


Book Description

Strategies in Learning and Using a Second Language examines what it takes to achieve long-term success in languages beyond the first language. Distinguishing language learning from language-use strategies, Andrew D. Cohen disentangles a morass of terminology to help the reader see what language strategies are and how they can enhance performance. Particular areas of research examined in the book include: - links between the use of task-specific strategies and language performance - how multilinguals verbalise their thoughts during language learning and use strategies that learners use in test-taking contexts In this fully revised and substantially rewritten second edition, every chapter has been reworked, with material either updated or replaced. Entirely new material has also been developed based on examples of specific strategies supplied by actual learners, mostly drawn from a website featuring these strategies in the learning of Spanish grammar.Strategies in Learning and Using a Second language will be an invaluable resource for language teachers and researchers, as well as for administrators of second language programmes and for students of applied linguistics.




Motivation for Learning and Performance


Book Description

Designed for educators, researchers, practitioners, or anyone interested in maximizing human potential, Motivation for Learning and Performance outlines 50 key motivation principles based on the latest scientific evidence from the disciplines of psychology, education, business, athletics, and neurology. Using a highly applied and conversational style, the book is designed to inform the reader about how to diagnosis, analyze, and mediate learning and performance challenges influenced by motivation. The book features chapters on the biopsychology of motivation, how motivation changes across the lifespan, and the important influence of culture on motivated behavior. Three chapters are devoted to practical strategies and the implementation of motivational change. Special sections are included on enhancing motivation at work, in the classroom, in competitive environments, and during online education. Hoffman employs the innovative approach of using his interviews with "real" people including many notable personalities across diverse cultures and disciplines to illustrate motivated behavior. For example, readers will learn what motivated the colossal investment fraud masterminded by Bernie Madoff, the intimate thoughts of former NFL superstar Nick Lowery when he missed a field goal, and the joys and tribulations of Emmy-nominated "Curb your Enthusiasm" actress Cheryl Hines. The book provides a practical, applied, and multi-disciplinary resource for anyone interested in motivation and performance, but especially for university students at the graduate or undergraduate level studying education, psychology, business, leadership, hospitality, sports management, or military science. Additionally, the writing style and eclectic nature of the text will appeal to readers of non-fiction who can use the book to gain self-awareness to enhance performance of themselves or others. Considers motivation for both learning and performance Identifies 50 foundational principles relating to motivation Provides research evidence supporting the foundational principles Includes interviews from famous individuals, identifying what motivated them and why Includes research from psychology, education, neuroscience, business, and sports