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Models Of Learning
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Book Synopsis Models of Learning by : Bruce R. Joyce
Download or read book Models of Learning written by Bruce R. Joyce and published by . This book was released on 1997 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to introduce some of the array of models of teaching that have been developed, polished & studied over the last twenty five years. Teachers, advisers, inspectors, teacher educators & educational researchers who study these models will discover elegant modes of teaching that have great power for learners. The book also contains peer coaching guides.
Book Synopsis Understanding Models for Learning and Instruction: by : Dirk Ifenthaler
Download or read book Understanding Models for Learning and Instruction: written by Dirk Ifenthaler and published by Springer Science & Business Media. This book was released on 2008-02-22 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pioneering research and theories of Norbert Seel have had a profound impact on educational thought in mathematics. In this special tribute, an international panel of researchers presents the current state of model-based education: its research, methodology, and technology. Fifteen stimulating, sometimes playful chapters link the multiple ways of constructing knowledge to the complex real world of skill development. This synthesis of latest innovations and fresh perspectives on classic constructs makes the book cutting-edge reading for the researchers and educators in mathematics instruction building the next generation of educational models.
Book Synopsis Production System Models of Learning and Development by : David Klahr
Download or read book Production System Models of Learning and Development written by David Klahr and published by MIT Press. This book was released on 1987 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive psychologists have found the production systems class of computer simulation models to be one of the most direct ways to cast complex theories of human intelligence. There have been many scattered studies on production systems since they were first proposed as computational models of human problem-solving behavior by Allen Newell some twenty years ago, but this is the first book to focus exclusively on these important models of human cognition, collecting and giving many of the best examples of current research. In the first chapter, Robert Neches, Pat Langley, and David Klahr provide an overview of the fundamental issues involved in using production systems as a medium for theorizing about cognitive processes, emphasizing their theoretical power. The remaining chapters take up learning by doing and learning by understanding, discrimination learning, learning through incremental refinement, learning by chunking, procedural earning, and learning by composition. A model of cognitive development called BAIRN is described, and a final chapter reviews John Anderson's ACT theory and discusses how it can be used in intelligent tutoring systems, including one that teaches LISP programming skills. In addition to the editors, the contributors are Yuichiro Anzai (Hokkaido University, Japan), Paul Rosenbloom (Stanford) and Allen Newell (Carnegie-Mellon), Stellan Ohlsson (University of Pittsburgh), Clayton Lewis (University of Colorado, Boulder), Iain Wallace and Kevin Bluff (Deakon University, Australia), and John Anderson (Carnegie-Mellon). David Klahr is Professor and Head of the Department of Psychology at Carnegie-Mellon University. Pat Langley is Associate Professor, Department ofInformation and Computer Science, University of California, Irvine, and Robert Neches is Research Computer Scientist at University of Southern California Information Sciences Institute. "Production System Models of Learning and Development" is included in the series Computational Models of Cognition and Perception, edited by Jerome A. Feldman, Patrick J. Hayes, and David E.Rumelhart. A Bradford Book.
Book Synopsis Models of Teaching by : Jeanine M. Dell'Olio
Download or read book Models of Teaching written by Jeanine M. Dell'Olio and published by SAGE Publications. This book was released on 2007-02-26 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of Teaching: Connecting Student Learning with Standards features classic and contemporary models of teaching appropriate to elementary and secondary settings. Authors Jeanine M. Dell'Olio and Tony Donk use detailed case studies to discuss 10 models of teaching and demonstrate how they can be connected to state content standards and benchmarks, as well as technology standards. This book provides readers with the theoretical and practical understandings of how to use models of teaching to both meet and exceed the growing expectations for research based instructional practices and student achievement.
Book Synopsis Learning in Graphical Models by : M.I. Jordan
Download or read book Learning in Graphical Models written by M.I. Jordan and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail. Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.
Book Synopsis Interpretable Machine Learning by : Christoph Molnar
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Book Synopsis The Oxford Handbook of Lifelong Learning by :
Download or read book The Oxford Handbook of Lifelong Learning written by and published by Oxford University Press. This book was released on 2021-06-01 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook provides a comprehensive and up-to-date examination of lifelong learning. Across 38 chapters, including twelve that are brand new to this edition, the approach is interdisciplinary, spanning human resources development, adult learning (educational perspective), psychology, career and vocational learning, management and executive development, cultural anthropology, the humanities, and gerontology. This volume covers trends that contribute to the need for continuous learning, considers psychological characteristics that relate to the drive to learn, reviews existing theory and research on adult learning, describes training methods and learning technologies for instructional design, and explores current and future challenges to support continuous learning.
Book Synopsis Model-Based Machine Learning by : John Winn
Download or read book Model-Based Machine Learning written by John Winn and published by CRC Press. This book was released on 2023-11-30 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.
Book Synopsis Machine Learning Models and Algorithms for Big Data Classification by : Shan Suthaharan
Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.
Book Synopsis The Leader in Me by : Stephen R. Covey
Download or read book The Leader in Me written by Stephen R. Covey and published by Simon and Schuster. This book was released on 2012-12-11 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Children in today's world are inundated with information about who to be, what to do and how to live. But what if there was a way to teach children how to manage priorities, focus on goals and be a positive influence on the world around them? The Leader in Meis that programme. It's based on a hugely successful initiative carried out at the A.B. Combs Elementary School in North Carolina. To hear the parents of A. B Combs talk about the school is to be amazed. In 1999, the school debuted a programme that taught The 7 Habits of Highly Effective Peopleto a pilot group of students. The parents reported an incredible change in their children, who blossomed under the programme. By the end of the following year the average end-of-grade scores had leapt from 84 to 94. This book will launch the message onto a much larger platform. Stephen R. Covey takes the 7 Habits, that have already changed the lives of millions of people, and shows how children can use them as they develop. Those habits -- be proactive, begin with the end in mind, put first things first, think win-win, seek to understand and then to be understood, synergize, and sharpen the saw -- are critical skills to learn at a young age and bring incredible results, proving that it's never too early to teach someone how to live well.
Book Synopsis Social Learning by : William Hoppitt
Download or read book Social Learning written by William Hoppitt and published by Princeton University Press. This book was released on 2013-07-21 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience. Social Learning provides a comprehensive, practical guide to the research methods of this important emerging field. William Hoppitt and Kevin Laland define the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. They present techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. They also describe the latest theory and empirical findings on social learning strategies, and introduce readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students. Provides a comprehensive, practical guide to social learning research Combines theoretical and empirical approaches Describes techniques for the laboratory and the field Covers social learning mechanisms and strategies, statistical modeling techniques for field data, mathematical modeling of cultural evolution, and more
Book Synopsis Model-Based Approaches to Learning by :
Download or read book Model-Based Approaches to Learning written by and published by BRILL. This book was released on 2019-02-11 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model-Based Approaches to Learning provides a new perspective called learning by system modeling. This book explores the learning impact of students when constructing models of complex systems.
Book Synopsis Modelling Learners and Learning in Science Education by : Keith S. Taber
Download or read book Modelling Learners and Learning in Science Education written by Keith S. Taber and published by Springer. This book was released on 2016-09-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sets out the necessary processes and challenges involved in modeling student thinking, understanding and learning. The chapters look at the centrality of models for knowledge claims in science education and explore the modeling of mental processes, knowledge, cognitive development and conceptual learning. The conclusion outlines significant implications for science teachers and those researching in this field. This highly useful work provides models of scientific thinking from different field and analyses the processes by which we can arrive at claims about the minds of others. The author highlights the logical impossibility of ever knowing for sure what someone else knows, understands or thinks, and makes the case that researchers in science education need to be much more explicit about the extent to which research onto learners’ ideas in science is necessarily a process of developing models. Through this book we learn that research reports should acknowledge the role of modeling and avoid making claims that are much less tentative than is justified as this can lead to misleading and sometimes contrary findings in the literature. In everyday life we commonly take it for granted that finding out what another knows or thinks is a relatively trivial or straightforward process. We come to take the ‘mental register’ (the way we talk about the ‘contents’ of minds) for granted and so teachers and researchers may readily underestimate the challenges involved in their work.
Book Synopsis Learning Partnerships by : Marcia B. Baxter Magolda
Download or read book Learning Partnerships written by Marcia B. Baxter Magolda and published by Taylor & Francis. This book was released on 2023-07-03 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: While a common goal of higher education is to improve student learning to prepare young adults for the professional, civic and personal challenges of their lives, few institutions have a model to facilitate these outcomes. Learning Partnerships offers a grounded theory and practical examples of how these objectives can be achieved at the college course, program, and institutional levels.The book takes as its foundation Marcia Baxter Magolda’s "Learning Partnerships Model" based on her seventeen-year longitudinal study of young adults’ learning and development from their undergraduate years through their thirties. Based on nearly a thousand participant narratives, the model offers an empirically grounded yet flexible approach to promote "self-authorship." Marcia Baxter Magolda describes the nature of self-authorship--its centrality to the learning goals of cognitive maturity, an integrated identity, mature relationships, and effective citizenship--and the Model.The book then documents examples of actual practice and the learning outcomes they have yielded. The settings include community college and undergraduate courses, exchange and internship programs, residential life, a Masters’ program, faculty development and student affairs organization.Learning Partnerships offers models for all educators--faculty and student affairs staff alike--who work to balance guidance and learner responsibility to prepare students for the complexity of the twenty-first century.
Book Synopsis Learning Through Practice by : Stephen Billett
Download or read book Learning Through Practice written by Stephen Billett and published by Springer Science & Business Media. This book was released on 2010-06-02 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practice-based learning—the kind of education that comes from experiencing real work in real situations—has always been a prerequisite to qualification in professions such as medicine. However, there is growing interest in how practice-based models of learning can assist the initial preparation for and further development of skills for a wider range of occupations. Rather than being seen as a tool of first-time training, it is now viewed as a potentially important facet of professional development and life-long learning. This book provides perspectives on practice-based learning from a range of disciplines and fields of work. The collection here draws on a wide spectrum of perspectives to illustrate as well as to critically appraise approaches to practice-based learning. The book’s two sections first explore the conceptual foundations of learning through practice, and then provide detailed examples of its implementation. Long-standing practice-based approaches to learning have been used in many professions and trades. Indeed, admission to the trades and major professions (e.g. medicine, law, accountancy) can only be realised after completing extended periods of practice in authentic practice settings. However, the growing contemporary interest in using practice-based learning in more extensive contexts has arisen from concerns about the direct employability of graduates and the increasing focus on occupation-specific courses in both vocations and higher education. It is an especially urgent issue in an era of critical skill shortages, rapidly transforming work requirements and an aging workforce combined with a looming shortage of new workforce entrants. We must better understand how existing models of practice-based learning are enacted in order to identify how they can be applied to different kinds of employment and workplaces. The contributions to this volume explore ways in which learning through practice can be conceptualised, enacted, and appraised through an analysis of the traditions, purposes, and processes that support this learning—including curriculum models and pedagogic practices.
Book Synopsis Instructional Models in Physical Education by : Michael Metzler
Download or read book Instructional Models in Physical Education written by Michael Metzler and published by Routledge. This book was released on 2017-06-30 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ensures that physical educators are fully armed with a comprehensive plan for incorporating instructional models in their teaching! Instructional Models for Physical Education has two primary goals for its readers. The first is to familiarize them with the notion of model-based instruction for physical education, including the components and dimensions that determine a model's pattern of teaching and how to select the most effective model for student learning in a particular unit. The second goal is to describe each of the instructional models in such a way to give readers enough information to use any of the models with confidence and good results. The book includes everything readers will need for planning, implementing, and assessing when teaching with instructional models. It will help readers incorporate research-based practices in their lessons, adapt activities to include students of varying abilities, and teach to standards. Models tied to NASPE standards! The author has revised the third edition to show how using the instructional models can help teachers meet specific NASPE standards. The book demonstrates the connection of NASPE standards with the models and clarifies that connection for students. In addition, a table in each of the model chapters shows explicitly how the model aligns with NASPE standards.
Book Synopsis Experiential Learning by : David A. Kolb
Download or read book Experiential Learning written by David A. Kolb and published by Pearson Education. This book was released on 2015 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experiential learning is a powerful and proven approach to teaching and learning that is based on one incontrovertible reality: people learn best through experience. Now, in this extensively updated book, David A. Kolb offers a systematic and up-to-date statement of the theory of experiential learning and its modern applications to education, work, and adult development. Experiential Learning, Second Edition builds on the intellectual origins of experiential learning as defined by figures such as John Dewey, Kurt Lewin, Jean Piaget, and L.S. Vygotsky, while also reflecting three full decades of research and practice since the classic first edition. Kolb models the underlying structures of the learning process based on the latest insights in psychology, philosophy, and physiology. Building on his comprehensive structural model, he offers an exceptionally useful typology of individual learning styles and corresponding structures of knowledge in different academic disciplines and careers. Kolb also applies experiential learning to higher education and lifelong learning, especially with regard to adult education. This edition reviews recent applications and uses of experiential learning, updates Kolb's framework to address the current organizational and educational landscape, and features current examples of experiential learning both in the field and in the classroom. It will be an indispensable resource for everyone who wants to promote more effective learning: in higher education, training, organizational development, lifelong learning environments, and online.
