PDF Mathematics Inside the Black Box Download
- Author: Dylan Wiliam
- Publisher: Granada Learning
- ISBN: 9780708716878
- Category : Juvenile Nonfiction
- Languages : en
- Pages : 28
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English Inside the Black Box is an easy-to-follow booklet offering great advice and guidance on how to develop formative assessment in English.
Are some areas of fast Fourier transforms still unclear to you? Do the notation and vocabulary seem inconsistent? Does your knowledge of their algorithmic aspects feel incomplete? The fast Fourier transform represents one of the most important advancements in scientific and engineering computing. Until now, however, treatments have been either brief, cryptic, intimidating, or not published in the open literature. Inside the FFT Black Box brings the numerous and varied ideas together in a common notational framework, clarifying vague FFT concepts. Examples and diagrams explain algorithms completely, with consistent notation. This approach connects the algorithms explicitly to the underlying mathematics. Reviews and explanations of FFT ideas taken from engineering, mathematics, and computer science journals teach the computational techniques relevant to FFT. Two appendices familiarize readers with the design and analysis of computer algorithms, as well. This volume employs a unified and systematic approach to FFT. It closes the gap between brief textbook introductions and intimidating treatments in the FFT literature. Inside the FFT Black Box provides an up-to-date, self-contained guide for learning the FFT and the multitude of ideas and computing techniques it employs.
Enrich, grow, and sustain AfL in your classroom. Twenty years after the publication of Inside the Black Box, the landmark review of formative classroom assessment, international education experts Christine Harrison and Margaret Heritage tackle assessment for learning (AfL) anew, with fresh insights gained from two decades of research, theory, and classroom practice. Packed with key AfL ideas and supports, vignettes that illustrate AfL in action, and practice-based evidence to enrich understanding of AfL from both the teacher’s and the student’s perspectives, this book is a ‘sounding board’ for educators to explore and reflect on their own AfL practices and beliefs.
The process of technological change takes a wide variety of forms. Propositions that may be accurate when referring to the pharmaceutical industry may be totally inappropriate when applied to the aircraft industry or to computers or forest products. The central theme of Nathan Rosenberg's new book is the idea that technological changes are often 'path dependent', in the sense that their form and direction tend to be influenced strongly by the particular sequence of earlier events out of which a new technology has emerged. The book advances the understanding of technological change by explictly recognising its essential diversity and path-dependent nature. Individual chapters explore the particular features of new technologies in different historical and sectoral contexts. This book presents a unique account of how technological change is generated and the processes by which improved technologies are introduced.
Assessment for Learning is based on a two-year project involving thirty-six teachers in schools in Medway and Oxfordshire. After a brief review of the research background and of the project itself, successive chapters describe the specific practices which teachers found fruitful and the underlying ideas about learning that these developments illustrate. Later chapters discuss the problems that teachers encountered when implementing the new practices in their classroom and give guidance for school management and LEAs about promoting and supporting the changes. --from publisher description
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I. Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead). Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region). Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures. Benchmarking techniques are also presented in the appendix.