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Author: Bruce R. Joyce
Publisher:
ISBN:
Category : Apprendimento/Insegnamento - Modelli riflessivi
Languages : en
Pages : 226
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Book Description
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.
Author: Bruce R. Joyce
Publisher:
ISBN:
Category : Apprendimento/Insegnamento - Modelli riflessivi
Languages : en
Pages : 226
Get Book
Book Description
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.
Author: Dirk Ifenthaler
Publisher: Springer Science & Business Media
ISBN: 038776898X
Category : Education
Languages : en
Pages : 334
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Book Description
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.
Author: David Klahr
Publisher: MIT Press
ISBN: 9780262111140
Category : Psychology
Languages : en
Pages : 492
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Book Description
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.
Author: Jeanine M. Dell'Olio
Publisher: SAGE Publications
ISBN: 1483316874
Category : Education
Languages : en
Pages : 504
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Book Description
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.
Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Artificial intelligence
Languages : en
Pages : 320
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Book Description
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.
Author: M.I. Jordan
Publisher: Springer Science & Business Media
ISBN: 9401150141
Category : Computers
Languages : en
Pages : 630
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Book Description
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.
Author: Sebastian Thrun
Publisher: Springer Science & Business Media
ISBN: 1461555299
Category : Computers
Languages : en
Pages : 346
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Book Description
Over the past three decades or so, research on machine learning and data mining has led to a wide variety of algorithms that learn general functions from experience. As machine learning is maturing, it has begun to make the successful transition from academic research to various practical applications. Generic techniques such as decision trees and artificial neural networks, for example, are now being used in various commercial and industrial applications. Learning to Learn is an exciting new research direction within machine learning. Similar to traditional machine-learning algorithms, the methods described in Learning to Learn induce general functions from experience. However, the book investigates algorithms that can change the way they generalize, i.e., practice the task of learning itself, and improve on it. To illustrate the utility of learning to learn, it is worthwhile comparing machine learning with human learning. Humans encounter a continual stream of learning tasks. They do not just learn concepts or motor skills, they also learn bias, i.e., they learn how to generalize. As a result, humans are often able to generalize correctly from extremely few examples - often just a single example suffices to teach us a new thing. A deeper understanding of computer programs that improve their ability to learn can have a large practical impact on the field of machine learning and beyond. In recent years, the field has made significant progress towards a theory of learning to learn along with practical new algorithms, some of which led to impressive results in real-world applications. Learning to Learn provides a survey of some of the most exciting new research approaches, written by leading researchers in the field. Its objective is to investigate the utility and feasibility of computer programs that can learn how to learn, both from a practical and a theoretical point of view.
Author:
Publisher: Oxford University Press
ISBN: 0197506720
Category : Psychology
Languages : en
Pages : 813
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Book Description
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.
Author: Stephen R. Covey
Publisher: Simon and Schuster
ISBN: 147110446X
Category : Self-Help
Languages : en
Pages : 218
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Book Description
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.
Author: Keith S. Taber
Publisher: Springer
ISBN: 9789402405224
Category : Science
Languages : en
Pages : 0
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Book Description
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.
