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The article focuses on the problem of human capital gap between young, employed and high-qualified adults, and the unemployed and low-qualified, all of whom are participants of lifelong learning process. It also considers net partnership as a tool for bridging the gap.
This book analyses and elaborates on learning processes within work environments and explores professional learning. It presents research indicating general characteristics of the work environment that support learning, as well as barriers to workplace learning. Themes of professional development, lifelong learning and business organisation emerge through the chapters and contributions explore theoretical and empirical analyses on the boundary between working and learning in various contexts and with various methodological approaches. Readers will discover how current workplace learning approaches can emphasise the learning potential of the work environment and how workplaces can combine the application of competence that is working, with its acquisition or learning. Through these chapters, we learn about the educational challenge to design workplaces as environments of rich learning potential without neglecting business demands. Expert authors explore how learning and working are both to be considered as two common aspects of an individual’s activity. Complexity, significance, integrity and variety of assigned work tasks as well as scope of action, interaction and feedback within its processing, turn out to be crucial work characteristics, amongst others revealed in these chapters. Part of the Professional and Practice-based Learning series, this book will appeal to anyone with an interest in workplaces as learning environments: those within government, community or business agencies and within the research communities in education, psychology, sociology and business management will find it of great interest.
As more is discovered about the powerful impact of lifelong learning on adults, educators are changing their views about how, when and where we learn. Learning is no longer defined only in the context of formal educational settings but in social context as well – including families, the workplace, and religious and political groups. This book explores how learning is our lifetime quest to understand personal identity, purpose and meaning while conforming and adapting to the perceived and real confines of our paradoxical society. The author examines the complex social experience of learning, revealing how culture, gender, race and other societal factors shape an individual’s identity and ability to function in relationships – the basis of all learning. He also discusses the difficult paradox of cultivating creative thinking and reflective action in a society that values the acquisition of degrees, certificates and titles over actual learning and growth.
In Why Knowledge Matters, E. D. Hirsch, Jr., presents evidence from cognitive science, sociology, and education history to further the argument for a knowledge-based elementary curriculum. Influential scholar Hirsch, author of The Knowledge Deficit, asserts that a carefully planned curriculum that imparts communal knowledge is essential in achieving one of the most fundamental aims and objectives of education: preparing students for lifelong success. Hirsch examines historical and contemporary evidence from the United States and other nations, including France, and affirms that a knowledge-based approach has improved both achievement and equity in schools where it has been instituted. In contrast, educational change of the past several decades in the United States has endorsed a skills-based approach, founded on, Hirsch points out, many incorrect assumptions about child development and how children learn. He recommends new policies that are better aligned with our current understanding of neuroscience, developmental psychology, and social science. The book focuses on six persistent problems that merit the attention of contemporary education reform: the over-testing of students in the name of educational accountability; the scapegoating of teachers; the fadeout of preschool gains; the narrowing of the curriculum to crowd out history, geography, science, literature, and the arts; the achievement gap between demographic groups; and the reliance on standards, such as the Common Core State Standards, that are not linked to a rigorous curriculum. Why Knowledge Matters makes a clear case for educational innovation and introduces a new generation of American educators to Hirsch’s astute and passionate analysis.
From ancient times, philosophers, theologians, and artists have attempted to describe and categorize the defining virtues of civilization. In Truth, Beauty, and Goodness Reframed, renowned education authority Howard Gardner explores the meaning of the title's three virtues in an age when vast technological advancement and relativistic attitudes toward human nature have deeply shaken our moral worldview. His incisive examination reveals that although these concepts are changing faster than ever before, they are -- and will remain, with our stewardship -- cornerstones of our society. Designed to appeal to a wide readership, Truth, Beauty, and Goodness Reframed is an approachable primer on the foundations of ethics in the modern age.
"Sleep is one of the most important but least understood aspects of our life, wellness, and longevity ... An explosion of scientific discoveries in the last twenty years has shed new light on this fundamental aspect of our lives. Now ... neuroscientist and sleep expert Matthew Walker gives us a new understanding of the vital importance of sleep and dreaming"--Amazon.com.
Comparing Special Education unites in-depth comparative and historical studies with analyses of global trends to uncover similarities and differences found in special education systems around the world.
The Foundational Handbook on Improvement Research in Education is a pathbreaking effort to build a field of research committed to producing the practical knowledge needed to advance educational access, quality, and equity. This is research distinguished by the use of inclusive, iterative approaches to analysis, design, implementation, and evaluation to understand and address educational opportunities, needs, and problems grounded deeply in school and community contexts. Designed for researchers, students, and educators, the handbook elaborates the intellectual foundations, explores the organizational and policy contexts, reviews approaches, and examines methods of improvement research. It features contributions from a plural community of researchers with expertise in the learning sciences, instructional improvement, organizational and policy studies, and research methodologies, many with extensive experience collaborating with teachers, leadership, families, and advocates in local problem solving and design.
In the last few decades what it means to be rich has changed dramatically. Forget the 1%; it's the wealthiest .01% who are fast outpacing the rest of us. Today's colossal fortunes are amassed by the diligent toiling of smart, perceptive businessmen who see themselves as deserving victors in a cutthroat international competition. Cracking open this tight-knit world is Chrystia Freeland, an acclaimed business journalist. At ease in Davos or Dubai, Freeland has reported on the lives and minds of these new super-elites for nearly a decade. Grounding her interviews in the economics and history of modern capitalism, she provides examples of the new wealth and its consequences. She showcases the $3 million birthday party of a New York financier months before the financial meltdown; details the closed-door 2005 SEC meeting where the US government allowed investment banks to write their own regulatory laws; and tells how the Bank of Canada's Mark Carney became a key figure in the central battle between the plutocracy and the rest of us. Brightly written and powerfully researched, Freeland's Plutocrats will be a lightning rod event in the midst of the US election season.
Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.