887 resultados para Theory Practice Relationship


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In “The English Patient: English Grammar and teaching in the Twentieth Century”, Hudson and Walmsley (2005) contens that the decline of grammar in schools was linked to a similar decline in English universities, where no serious research or teaching on English grammar took place. This article argues that such a decline was due not only to a lack of research, but also because it suited educational policies of the time. It applies Bernstein’s theory of pedagogic discourse (1990 & 1996) to the case study of the debate surrounding the introduction of a national curriculum in English in England in the late 1980s and the National Literacy Strategy in the 1990s, to demonstrate the links between academic theory and educational policy.

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A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

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