Dictionary of French and English, English and French PDF Download

Author: John Bellows
Publisher:
ISBN:
Category : English language
Languages : en
Pages : 708

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Book Description

Author: Elena Nardi
Publisher: Springer Science & Business Media
ISBN: 0387371419
Category : Education
Languages : en
Pages : 349

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Book Description
This book offers a unique perspective on ways in which mathematicians: perceive their students' learning; teach; reflect on their teaching practice. Elena Nardi achieves this by employing two fictional, yet entirely data-grounded, characters to create a conversation on these important issues. The construction of these characters is based on large bodies of data including intense focused group interviews with mathematicians and extensive analyses of students' written work, collected and analyzed over a substantial period.

Author: Electre
Publisher:
ISBN: 9782765408468
Category :
Languages : fr
Pages : 1798

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Book Description

Author: Neural Information Processing Systems Foundation
Publisher: MIT Press
ISBN: 0262026171
Category : Algorithms
Languages : en
Pages : 361

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Book Description
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Author: Marianna Bosch
Publisher: Routledge
ISBN: 0429582420
Category : Education
Languages : en
Pages : 254

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Book Description
This book presents the main research veins developed within the framework of the Anthropological Theory of the Didactic (ATD), a paradigm that originated in French didactics of mathematics. While a great number of publications on ATD are available in French and Spanish, Working with the Anthropological Theory of the Didactic in Mathematics Education is the first directed at English-speaking international audiences. Written and edited by leading researchers in ATD, the book covers all aspects of ATD theory and practice, including teaching applications. The chapters feature the most relevant and recent investigations presented at the 6th international conference on the ATD, offering a unique opportunity for an international audience interested in the study of mathematics teaching and learning to keep in touch with advances in educational research. The book is divided into four sections and the contributions explore key topics such as: The core concept of ‘praxeology’, including its development and functionalities The need for new teaching praxeologies in the paradigm of questioning the world The impact of ATD on the teaching profession and the education of teachers This is the second volume in the New Perspectives on Research in Mathematics Education. This comprehensive casebook is an indispensable resource for researchers, teachers and graduate students around the world.

Author: Derek Holton
Publisher: Springer Science & Business Media
ISBN: 0792371917
Category : Education
Languages : en
Pages : 559

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Book Description
This is a text that contains the latest in thinking and the best in practice. It provides a state-of-the-art statement on tertiary teaching from a multi-perspective standpoint. No previous book has attempted to take such a wide view of the topic. The book will be of special interest to academic mathematicians, mathematics educators, and educational researchers. It arose from the ICMI Study into the teaching and learning of mathematics at university level (initiated at the conference in Singapore, 1998).

Author: A. G. Howson
Publisher: Cambridge University Press
ISBN: 9780521357036
Category : Mathematics
Languages : en
Pages : 106

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Book Description
Based on the 1987 International Commission on Mathematical Instruction conference, this volume comprises key papers on the role of mathematics in applied subjects.

Author: David Tall
Publisher: Cambridge University Press
ISBN: 1107035708
Category : Education
Languages : en
Pages : 483

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Book Description
How Humans Learn to Think Mathematically describes the development of mathematical thinking from the young child to the sophisticated adult. Professor David Tall reveals the reasons why mathematical concepts that make sense in one context may become problematic in another. For example, a child's experience of whole number arithmetic successively affects subsequent understanding of fractions, negative numbers, algebra, and the introduction of definitions and proof. Tall's explanations for these developments are accessible to a general audience while encouraging specialists to relate their areas of expertise to the full range of mathematical thinking. The book offers a comprehensive framework for understanding mathematical growth, from practical beginnings through theoretical developments, to the continuing evolution of mathematical thinking at the highest level.

Author: Michael J. Kearns
Publisher: MIT Press
ISBN: 9780262111935
Category : Computers
Languages : en
Pages : 230

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Book Description
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Author: Vladimir Vapnik
Publisher: Springer Science & Business Media
ISBN: 1475732643
Category : Mathematics
Languages : en
Pages : 324

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Book Description
The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.