This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic microarray data. Among those, the book focuses on a new application for dialog systems which can be thereby made adaptable and portable to different domains. Clustering evaluation metrics and new approaches, such as the ensembles of clustering algorithms, are also described.
Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm—creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making. Chapters include: Introduction to Reinforcement and Systemic Machine Learning Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning Systemic Machine Learning and Model Inference and Information Integration Adaptive Learning Incremental Learning and Knowledge Representation Knowledge Augmentation: A Machine Learning Perspective Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.
Learning the City: Translocal Assemblage and Urban Politics critically examines the relationship between knowledge, learning, and urban politics, arguing both for the centrality of learning for political strategies and developing a progressive international urbanism. Presents a distinct approach to conceptualising the city through the lens of urban learning Integrates fieldwork conducted in Mumbai's informal settlements with debates on urban policy, political economy, and development Considers how knowledge and learning are conceived and created in cities Addresses the way knowledge travels and opportunities for learning about urbanism between North and South
How can you use technology for pedagogic purposes in the language classroom? Technology Enhanced Language Learning discusses how the use of technology opens up opportunities for learning, how it enables different types of learning, and how it affects language use.
Since the first edition of E-learning by Design, e-learning has evolved rapidly and fringe techniques have moved into the mainstream. Underlying and underwriting these changes in e–learning are advances in technology and changes in society. The second edition of the bestselling book E-Learning by Design offers a comprehensive look at the concepts and processes of developing, creating, and implementing a successful e-learning program. This practical, down-to-earth resource is filled with clear information and instruction without over simplification. The book helps instructors build customized e-learning programs from scratch—building on core principles of instructional design to: develop meaningful activities and lessons; create and administer online tests and assessments; design learning games and simulations; and implement an individualized program. «Every newcomer to the field will find this edition indispensable, while professionals will find much needed contemporary information to manage the rapid changes happening in our field. Even if you own the first edition, buy this update as soon as possible.» —Michael W. Allen, CEO of Allen Interactions, Inc.; author, Michael Allen's e-Learning Library Series «Covers the full range of options for presenting learning materials online—including designing useful topics, engaging activities, and reliable tests—and it takes into account the realities and issues of today's instructional designers, such as social learning and mobile learning.» —Saul Carliner, associate professor, Concordia University; author, The E-Learning Handbook «Horton nails it! Perfectly timed, robust, and practical, this second edition of brings together the latest strategies for learning without losing its critical premise—technology enables e-learning, but great design makes it work.» —Marc J. Rosenberg, e-learning strategist; author, Beyond E-Learning «An e-learning encyclopedia loaded with detailed guidelines and examples ranging from basic instructional design techniques to the latest applications in games, social media, and mobile-learning. An essential reference for anyone involved in e-learning design, development, or evaluation» —Ruth Colvin Clark, author, e-Learning and the Science of Instruction
В статье рассматриваются такие проекты, как «Постоянная среда для оценки качества в e-learning» (SEEQUEL), который координирует сеть MENON при содействии Еврокомиссии; «Поддержка усовершенствований в e-learning» (SEEL), который координирует Европейский институт e-learning (EIFeL), а также их совместный проект – TRIANGLE, призванный создать прочную систему и развивать исследования по качеству e-learning в Европе. Рассматривается работа Ассоциации гарантии качества e-learning (EFQUEL), которая занимается повышением качества программ e-learning в Европе, создав новую схему оказания услуг для членов образовательного сообщества и поддержав все заинтересованные стороны, категории которых представлены в данной статье, а также руководит работой ряда основных рабочих групп II Конференции EFQUEL в Париже в январе 2007 года. Автор обратил внимание на такой парадокс: с одной стороны, большинство участников образовательного процесса желают прийти к общему мнению о качестве e-learning, а с другой – универсальной модели качества не существует.