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Foundations of the Theory of Learning Systems
Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.
The essential textbook in the field of blindness and visual impairment has been updated for the 21st c. Volume I includes new chapters focusing on crucial topics connecting the education of students with visual impairments to the context of educational theory. Icons in the book direct readers to supplemental materials in an online Learning Center.
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.
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
Foundations of Embodied Learning advances learning, instruction, and the design of educational technologies by rethinking the learner as an integrated system of mind, body, and environment. Body-based processes—direct physical, social, and environmental interactions—are constantly mediating intellectual performance, sensory stimulation, communication abilities, and other conditions of learning. This book’s coherent, evidence-based framework articulates principles of grounded and embodied learning for design and its implications for curriculum, classroom instruction, and student formative and summative assessment for scholars and graduate students of educational psychology, instructional design and technology, cognitive science, the learning sciences, and beyond.
"This open access textbook offers a comprehensive introduction to instruction in all types of library and information settings. Designed for students in library instruction courses, the text is also a resource for new and experienced professionals seeking best practices and selected resources to support their instructional practice. Organized around the backward design approach and written by LIS faculty members with expertise in teaching and learning, this book offers clear guidance on writing learning outcomes, designing assessments, and choosing and implementing instructional strategies, framed by clear and accessible explanations of learning theories. The text takes a critical approach to pedagogy and emphasizes inclusive and accessible instruction. Using a theory into practice approach that will move students from learning to praxis, each chapter includes practical examples, activities, and templates to aid readers in developing their own practice and materials."--Publisher's description.
"Neither an academic tome nor a prescriptive 'how to' guide, The Theory and Practice of Online Learning is an illuminating collection of essays by practitioners and scholars active in the complex field of distance education. Distance education has evolved significantly in its 150 years of existence. For most of this time, it was an individual pursuit defined by infrequent postal communication. But recently, three more developmental generations have emerged, supported by television and radio, teleconferencing, and computer conferencing. The early 21st century has produced a fifth generation, based on autonomous agents and intelligent, database-assisted learning, that has been referred to as Web 2.0. The second edition of "The Theory and Practice of Online Learning" features updates in each chapter, plus four new chapters on current distance education issues such as connectivism and social software innovations."--BOOK JACKET.
Shows how leaders can access the deepest source of inspiration and vision • Includes dozens of tested exercises, practices, and real-world examples We live in a time of massive institutional failure, one that requires a new consciousness and a new collective leadership capacity. In this groundbreaking book, Otto Scharmer invites us to see the world in new ways and in so doing discover a revolutionary approach to leadership. What we pay attention to and how we pay attention is key to what we create. What prevents us from attending to situations more effectively is that we aren’t fully aware of and in touch with the inner place from which attention and intention originate. This is what Scharmer calls our blind spot. By moving through Scharmer’s U process, we consciously access the blind spot and learn to connect to our authentic Self—the deepest source of knowledge and inspiration—in the realm of “presencing,” a term coined by Scharmer that combines the concepts of presence and sensing. Based on ten years of research and action learning and interviews with over 150 practitioners and thought leaders, Theory U offers a rich diversity of compelling stories and examples and includes dozens of exercises and practices that allow leaders, and entire organizations, to shift awareness, connect with the best future possibility, and gain the ability to realize it.