Computer Simulations In Science And Technology Studies
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Computer Simulations in Science and Technology Studies
Author: Petra Ahrweiler
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
What is it about the structure and organisation of science and technology that has led to the spectacularly successful growth of knowledge during this century? This book explores this important and much debated question in an innovative way, by using computer simulations. The computer simulation of societies and social processes is a methodology which is rapidly becoming recognised for its potential in the social sciences. This book applies the tools of simulation systematically to a specific domain: science and technology studies. The book shows how computer simulation can be applied both to questions in the history and philosophy of science and to issues of concern to sociologists of science and technology. Chapters in the book demonstrate the use of simulation for clarifying the notion of creativity and for understanding the logical processes employed by eminent scientists to make their discoveries. The book begins with three introductory chapters. The first introduces simulation for the social sciences, surveying current work and explaining the advantages and pitfalls of this new methodology. The second and third chapters review recent work on theoretical aspects of social simulation, introducing fundamental concepts such as self organisation and complexity and relating these to the simulation of scientific discovery.
Learning Science Through Computer Games and Simulations
Author: National Research Council
language: en
Publisher: National Academies Press
Release Date: 2011-04-12
At a time when scientific and technological competence is vital to the nation's future, the weak performance of U.S. students in science reflects the uneven quality of current science education. Although young children come to school with innate curiosity and intuitive ideas about the world around them, science classes rarely tap this potential. Many experts have called for a new approach to science education, based on recent and ongoing research on teaching and learning. In this approach, simulations and games could play a significant role by addressing many goals and mechanisms for learning science: the motivation to learn science, conceptual understanding, science process skills, understanding of the nature of science, scientific discourse and argumentation, and identification with science and science learning. To explore this potential, Learning Science: Computer Games, Simulations, and Education, reviews the available research on learning science through interaction with digital simulations and games. It considers the potential of digital games and simulations to contribute to learning science in schools, in informal out-of-school settings, and everyday life. The book also identifies the areas in which more research and research-based development is needed to fully capitalize on this potential. Learning Science will guide academic researchers; developers, publishers, and entrepreneurs from the digital simulation and gaming community; and education practitioners and policy makers toward the formation of research and development partnerships that will facilitate rich intellectual collaboration. Industry, government agencies and foundations will play a significant role through start-up and ongoing support to ensure that digital games and simulations will not only excite and entertain, but also motivate and educate.
Introduction to Mathematical Modeling and Computer Simulations
Introduction to Mathematical Modeling and Computer Simulations is written as a textbook for readers who want to understand the main principles of Modeling and Simulations in settings that are important for the applications, without using the profound mathematical tools required by most advanced texts. It can be particularly useful for applied mathematicians and engineers who are just beginning their careers. The goal of this book is to outline Mathematical Modeling using simple mathematical descriptions, making it accessible for first- and second-year students.