This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations. Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners. Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines? The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

This 1983 book is a lively and clearly written introduction to the philosophy of natural science, organized around the central theme of scientific realism. It has two parts. 'Representing' deals with the different philosophical accounts of scientific objectivity and the reality of scientific entities. The views of Kuhn, Feyerabend, Lakatos, Putnam, van Fraassen, and others, are all considered. 'Intervening' presents the first sustained treatment of experimental science for many years and uses it to give a new direction to debates about realism. Hacking illustrates how experimentation often has a life independent of theory. He argues that although the philosophical problems of scientific realism can not be resolved when put in terms of theory alone, a sound philosophy of experiment provides compelling grounds for a realistic attitude. A great many scientific examples are described in both parts of the book, which also includes lucid expositions of recent high energy physics and a remarkable chapter on the microscope in cell biology.

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.

This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations. Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners. Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines? The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

What Is Scientific Knowledge? is a much-needed collection of introductory-level chapters on the epistemology of science. Renowned historians, philosophers, science educators, and cognitive scientists have authored 19 original contributions specifically for this volume. The chapters, accessible for students in both philosophy and the sciences, serve as helpful introductions to the primary debates surrounding scientific knowledge. First-year undergraduates can readily understand the variety of discussions in the volume, and yet advanced students and scholars will encounter chapters rich enough to engage their many interests. The variety and coverage in this volume make it the perfect choice for the primary text in courses on scientific knowledge. It can also be used as a supplemental book in classes in epistemology, philosophy of science, and other related areas. Key features: * an accessible and comprehensive introduction to the epistemology of science for a wide variety of students (both undergraduate- and graduate-level) and researchers * written by an international team of senior researchers and the most promising junior scholars * addresses several questions that students and lay people interested in science may already have, including questions about how scientific knowledge is gained, its nature, and the challenges it faces.

We are accustomed to thinking of science and its findings as universal. After all, one atom of carbon plus two of oxygen yields carbon dioxide in Amazonia as well as in Alaska; a scientist in Bombay can use the same materials and techniques to challenge the work of a scientist in New York; and of course the laws of gravity apply worldwide. Why, then, should the spaces where science is done matter at all? David N. Livingstone here puts that question to the test with his fascinating study of how science bears the marks of its place of production. Putting Science in Its Place establishes the fundamental importance of geography in both the generation and the consumption of scientific knowledge, using historical examples of the many places where science has been practiced. Livingstone first turns his attention to some of the specific sites where science has been made—the laboratory, museum, and botanical garden, to name some of the more conventional locales, but also places like the coffeehouse and cathedral, ship's deck and asylum, even the human body itself. In each case, he reveals just how the space of inquiry has conditioned the investigations carried out there. He then describes how, on a regional scale, provincial cultures have shaped scientific endeavor and how, in turn, scientific practices have been instrumental in forming local identities. Widening his inquiry, Livingstone points gently to the fundamental instability of scientific meaning, based on case studies of how scientific theories have been received in different locales. Putting Science in Its Place powerfully concludes by examining the remarkable mobility of science and the seemingly effortless way it moves around the globe. From the reception of Darwin in the land of the Maori to the giraffe that walked from Marseilles to Paris, Livingstone shows that place does matter, even in the world of science.

What is science for a child? How do children learn about science and how to do science? Drawing on a vast array of work from neuroscience to classroom observation, Taking Science to School provides a comprehensive picture of what we know about teaching and learning science from kindergarten through eighth grade. By looking at a broad range of questions, this book provides a basic foundation for guiding science teaching and supporting students in their learning. Taking Science to School answers such questions as: When do children begin to learn about science? Are there critical stages in a child's development of such scientific concepts as mass or animate objects? What role does nonschool learning play in children's knowledge of science? How can science education capitalize on children's natural curiosity? What are the best tasks for books, lectures, and hands-on learning? How can teachers be taught to teach science? The book also provides a detailed examination of how we know what we know about children's learning of scienceâ€"about the role of research and evidence. This book will be an essential resource for everyone involved in K-8 science educationâ€"teachers, principals, boards of education, teacher education providers and accreditors, education researchers, federal education agencies, and state and federal policy makers. It will also be a useful guide for parents and others interested in how children learn.

Science is continually confronted by new and difficult social and ethical problems. Some of these problems have arisen from the transformation of the academic science of the prewar period into the industrialized science of the present. Traditional theories of science are now widely recognized as obsolete. In Scientific Knowledge and Its Social Problems (originally published in 1971), Jerome R. Ravetz analyzes the work of science as the creation and investigation of problems. He demonstrates the role of choice and value judgment, and the inevitability of error, in scientific research. Ravetz's new introductory essay is a masterful statement of how our understanding of science has evolved over the last two decades.

Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments.

Researchers, historians, and philosophers of science have debated the nature of scientific research in education for more than 100 years. Recent enthusiasm for "evidence-based" policy and practice in educationâ€"now codified in the federal law that authorizes the bulk of elementary and secondary education programsâ€"have brought a new sense of urgency to understanding the ways in which the basic tenets of science manifest in the study of teaching, learning, and schooling. Scientific Research in Education describes the similarities and differences between scientific inquiry in education and scientific inquiry in other fields and disciplines and provides a number of examples to illustrate these ideas. Its main argument is that all scientific endeavors share a common set of principles, and that each fieldâ€"including education researchâ€"develops a specialization that accounts for the particulars of what is being studied. The book also provides suggestions for how the federal government can best support high-quality scientific research in education.