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| example of science conclusion: Reproducibility and Replicability in Science National Academies of Sciences, Engineering, and Medicine, Policy and Global Affairs, Committee on Science, Engineering, Medicine, and Public Policy, Board on Research Data and Information, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Division on Earth and Life Studies, Nuclear and Radiation Studies Board, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Board on Behavioral, Cognitive, and Sensory Sciences, Committee on Reproducibility and Replicability in Science, 2019-10-20 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. |
| example of science conclusion: Mathematics and Science Education Around the World National Research Council, Division of Behavioral and Social Sciences and Education, Mathematical Sciences Education Board, Board on Science Education, Mathematical Sciences Education Board and Committee on Science Education K-12, 1996-10-18 Amid current efforts to improve mathematics and science education in the United States, people often ask how these subjects are organized and taught in other countries. They hear repeatedly that other countries produce higher student achievement. Teachers and parents wonder about the answers to questions like these: Why do the children in Asian cultures seem to be so good at science and mathematics? How are biology and physics taught in the French curriculum? What are textbooks like elsewhere, and how much latitude do teachers have in the way they follow the texts? Do all students receive the same education, or are they grouped by ability or perceived educational promise? If students are grouped, how early is this done? What are tests like, and what are the consequences for students? Are other countries engaged in Standards-like reforms? Does anything like standards play a role in other countries? Questions such as these reflect more than a casual interest in other countries' educational practices. They grow out of an interest in identifying ways to improve mathematics and science education in the United States. The focus of this short report is on what the Third International Mathematics and Science Study (TIMSS), a major international investigation of curriculum, instruction, and learning in mathematics and science, will be able to contribute to understandings of mathematics and science education around the world as well as to current efforts to improve student learning, particularly in the United States. |
| example of science conclusion: Janice VanCleave's Great Science Project Ideas from Real Kids Janice VanCleave, 2006-10-20 There's plenty for you to choose from in this collection of forty terrific science project ideas from real kids, chosen by well-known children's science writer Janice VanCleave. Developing your own science project requires planning, research, and lots of hard work. This book saves you time and effort by showing you how to develop your project from start to finish and offering useful design and presentation techniques. Projects are in an easy-to-follow format, use easy-to-find materials, and include dozens illustrations and diagrams that show you what kinds of charts and graphs to include in your science project and how to set up your project display. You’ll also find clear scientific explanations, tips for developing your own unique science project, and 100 additional ideas for science projects in all science categories. |
| example of science conclusion: Concepts of Biology Samantha Fowler, Rebecca Roush, James Wise, 2023-05-12 Black & white print. Concepts of Biology is designed for the typical introductory biology course for nonmajors, covering standard scope and sequence requirements. The text includes interesting applications and conveys the major themes of biology, with content that is meaningful and easy to understand. The book is designed to demonstrate biology concepts and to promote scientific literacy. |
| example of science conclusion: Frontiers in Massive Data Analysis National Research Council, Division on Engineering and Physical Sciences, Board on Mathematical Sciences and Their Applications, Committee on Applied and Theoretical Statistics, Committee on the Analysis of Massive Data, 2013-09-03 Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data. |
| example of science conclusion: How People Learn National Research Council, Division of Behavioral and Social Sciences and Education, Board on Behavioral, Cognitive, and Sensory Sciences, Committee on Developments in the Science of Learning with additional material from the Committee on Learning Research and Educational Practice, 2000-08-11 First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from the original book can translate into actions and practice, now making a real connection between classroom activities and learning behavior. This edition includes far-reaching suggestions for research that could increase the impact that classroom teaching has on actual learning. Like the original edition, this book offers exciting new research about the mind and the brain that provides answers to a number of compelling questions. When do infants begin to learn? How do experts learn and how is this different from non-experts? What can teachers and schools do-with curricula, classroom settings, and teaching methodsâ€to help children learn most effectively? New evidence from many branches of science has significantly added to our understanding of what it means to know, from the neural processes that occur during learning to the influence of culture on what people see and absorb. How People Learn examines these findings and their implications for what we teach, how we teach it, and how we assess what our children learn. The book uses exemplary teaching to illustrate how approaches based on what we now know result in in-depth learning. This new knowledge calls into question concepts and practices firmly entrenched in our current education system. Topics include: How learning actually changes the physical structure of the brain. How existing knowledge affects what people notice and how they learn. What the thought processes of experts tell us about how to teach. The amazing learning potential of infants. The relationship of classroom learning and everyday settings of community and workplace. Learning needs and opportunities for teachers. A realistic look at the role of technology in education. |
| example of science conclusion: Statistics Done Wrong Alex Reinhart, 2015-03-01 Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong. |
| example of science conclusion: Experiments in International Benchmarking of US Research Fields Institute of Medicine, National Academy of Engineering, National Academy of Sciences, Committee on Science, Engineering, and Public Policy, 2000-02-28 How can the federal government gauge the overall health of scientific researchâ€as a whole and in its partsâ€and determine whether national funding adequately supports national research objectives? It is feasible to monitor US performance with field-by-field peer assessments. This might be done through the establishment of independent panels consisting of researchers who work in a field, individuals who work in closely related fields, and research users who follow the field closely. Some of these individuals should be outstanding foreign scientists in the field being examined. This technique of comparative international assessments is also known as international benchmarking. Experiments in International Benchmarking of U.S. Research Fields evaluates the feasibility and utility of the benchmarking technique. In order to do this, the report internationally benchmarks three fields: mathematics, immunology, and materials science and engineering, then summarizes the results of these experiments. |
| example of science conclusion: Lab Reports and Science Books Lucy Calkins, Lauren Kolbeck, Monique Knight, 2013 |
| example of science conclusion: Science Literacy National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Committee on Science Literacy and Public Perception of Science, 2016-11-14 Science is a way of knowing about the world. At once a process, a product, and an institution, science enables people to both engage in the construction of new knowledge as well as use information to achieve desired ends. Access to scienceâ€whether using knowledge or creating itâ€necessitates some level of familiarity with the enterprise and practice of science: we refer to this as science literacy. Science literacy is desirable not only for individuals, but also for the health and well- being of communities and society. More than just basic knowledge of science facts, contemporary definitions of science literacy have expanded to include understandings of scientific processes and practices, familiarity with how science and scientists work, a capacity to weigh and evaluate the products of science, and an ability to engage in civic decisions about the value of science. Although science literacy has traditionally been seen as the responsibility of individuals, individuals are nested within communities that are nested within societiesâ€and, as a result, individual science literacy is limited or enhanced by the circumstances of that nesting. Science Literacy studies the role of science literacy in public support of science. This report synthesizes the available research literature on science literacy, makes recommendations on the need to improve the understanding of science and scientific research in the United States, and considers the relationship between scientific literacy and support for and use of science and research. |
| example of science conclusion: Conducting Biosocial Surveys National Research Council, Division of Behavioral and Social Sciences and Education, Committee on Population, Committee on National Statistics, Panel on Collecting, Storing, Accessing, and Protecting Biological Specimens and Biodata in Social Surveys, 2010-10-02 Recent years have seen a growing tendency for social scientists to collect biological specimens such as blood, urine, and saliva as part of large-scale household surveys. By combining biological and social data, scientists are opening up new fields of inquiry and are able for the first time to address many new questions and connections. But including biospecimens in social surveys also adds a great deal of complexity and cost to the investigator's task. Along with the usual concerns about informed consent, privacy issues, and the best ways to collect, store, and share data, researchers now face a variety of issues that are much less familiar or that appear in a new light. In particular, collecting and storing human biological materials for use in social science research raises additional legal, ethical, and social issues, as well as practical issues related to the storage, retrieval, and sharing of data. For example, acquiring biological data and linking them to social science databases requires a more complex informed consent process, the development of a biorepository, the establishment of data sharing policies, and the creation of a process for deciding how the data are going to be shared and used for secondary analysis-all of which add cost to a survey and require additional time and attention from the investigators. These issues also are likely to be unfamiliar to social scientists who have not worked with biological specimens in the past. Adding to the attraction of collecting biospecimens but also to the complexity of sharing and protecting the data is the fact that this is an era of incredibly rapid gains in our understanding of complex biological and physiological phenomena. Thus the tradeoffs between the risks and opportunities of expanding access to research data are constantly changing. Conducting Biosocial Surveys offers findings and recommendations concerning the best approaches to the collection, storage, use, and sharing of biospecimens gathered in social science surveys and the digital representations of biological data derived therefrom. It is aimed at researchers interested in carrying out such surveys, their institutions, and their funding agencies. |
| example of science conclusion: The Primary Science and Technology Encyclopedia Christopher Collier, Dan Davies, Alan Howe, Kendra McMahon, 2010-12-13 The book provides clear descriptions, definitions and explanations of difficult scientific concepts, carefully chosen to reflect the needs of those involved in primary science education. |
| example of science conclusion: Data Science in Education Using R Ryan A. Estrellado, Emily Freer, Joshua M. Rosenberg, Isabella C. Velásquez, 2020-10-26 Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a learn by doing approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development. |
| example of science conclusion: The Popular Science Monthly , 1888 |
| example of science conclusion: Scientific Explanation Philip Kitcher, Wesley C. Salmon, 1962-05-25 Scientific Explanation was first published in 1962. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions. Is a new consensus emerging in the philosophy of science? The nine distinguished contributors to this volume apply that question to the realm of scientific explanation and, although their conclusions vary, they agree in one respect: there definitely was an old consensus. Co-editor Wesley Salmon's opening essay, Four Decades of Scientific Explanation, grounds the entire discussion. His point of departure is the founding document of the old consensus: a 1948 paper by Carl G. Hempel and Paul Oppenheim, Studies in the Logic of Explanation, that set forth, with remarkable clarity, a mode of argument that came to be known as the deductive-nomological model. This approach, holding that explanation dies not move beyond the sphere of empirical knowledge, remained dominant during the hegemony of logical empiricism from 1950 to 1975. Salmon traces in detail the rise and breakup of the old consensus, and examines the degree to which there is, if not a new consensus, at least a kind of reconciliation on this issue among contemporary philosophers of science and clear agreement that science can indeed tell us why. The other contributors, in the order of their presentations, are: Peter Railton, Matti Sintonen, Paul W. Humphreys, David Papineau, Nancy Cartwright, James Woodward, Merrilee H. Salmon, and Philip Kitcher. |
| example of science conclusion: Science, Medicine, and Animals Committee on the Use of Animals in Research (U.S.), Institute of Medicine (U.S.), 1991 The necessity for animal use in biomedical research is a hotly debated topic in classrooms throughout the country. Frequently teachers and students do not have access to balanced,  factual material to foster an informed discussion on the topic. This colorful, 50-page booklet is designed to educate teenagers about the role of animal research in combating disease, past and present; the perspective of animal use within the whole spectrum of biomedical research; the regulations and oversight that govern animal research; and the continuing efforts to use animals more efficiently and humanely. |
| example of science conclusion: On science and revelation, presidential address sir George Gabriel Stokes (1st bart.), 1883 |
| example of science conclusion: Attribution of Extreme Weather Events in the Context of Climate Change National Academies of Sciences, Engineering, and Medicine, Division on Earth and Life Studies, Board on Atmospheric Sciences and Climate, Committee on Extreme Weather Events and Climate Change Attribution, 2016-07-28 As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities. |
| example of science conclusion: Philosophy of Science for Biologists Kostas Kampourakis, Tobias Uller, 2020-09-24 A short and accessible introduction to philosophy of science for students and researchers across the life sciences. |
| example of science conclusion: From Scarcity to Visibility National Research Council, Policy and Global Affairs, Committee on Women in Science and Engineering, Panel for the Study of Gender Differences in the Career Outcomes of Science and Engineering Ph.D.s, 2001-11-16 Although women have made important inroads in science and engineering since the early 1970s, their progress in these fields has stalled over the past several years. This study looks at women in science and engineering careers in the 1970s and 1980s, documenting differences in career outcomes between men and women and between women of different races and ethnic backgrounds. The panel presents what is known about the following questions and explores their policy implications: In what sectors are female Ph.D.s employed? What salary disparities exist between men and women in these fields? How is marital status associated with career attainment? Does it help a career to have a postdoctoral appointment? How well are female scientists and engineers represented in management? Within the broader context of education and the labor market, the book provides detailed comparisons between men and women Ph.D.s in a number of measures: financial support for education, academic rank achieved, salary, and others. The study covers engineering; the mathematical, physical, life, and social and behavioral sciences; medical school faculty; and recipients of National Institutes of Health grants. Findings and recommendations in this volume will be of interest to practitioners, faculty, and students in science and engineering as well as education administrators, employers, and researchers in these fields. |
| example of science conclusion: Interview Research in Political Science Maria Elayna Mosley, 2013-05-15 Interviews are a frequent and important part of empirical research in political science, but graduate programs rarely offer discipline-specific training in selecting interviewees, conducting interviews, and using the data thus collected. Interview Research in Political Science addresses this vital need, offering hard-won advice for both graduate students and faculty members. The contributors to this book have worked in a variety of field locations and settings and have interviewed a wide array of informants, from government officials to members of rebel movements and victims of wartime violence, from lobbyists and corporate executives to workers and trade unionists. The authors encourage scholars from all subfields of political science to use interviews in their research, and they provide a set of lessons and tools for doing so. The book addresses how to construct a sample of interviewees; how to collect and report interview data; and how to address ethical considerations and the Institutional Review Board process. Other chapters discuss how to link interview-based evidence with causal claims; how to use proxy interviews or an interpreter to improve access; and how to structure interview questions. A useful appendix contains examples of consent documents, semistructured interview prompts, and interview protocols. |
| example of science conclusion: Development Research in Practice Kristoffer Bjärkefur, Luíza Cardoso de Andrade, Benjamin Daniels, Maria Ruth Jones, 2021-07-16 Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University |
| example of science conclusion: Journal of the Transactions of the Victoria Institute, Or Philosophical Society of Great Britain Victoria Institute (Great Britain), 1889 |
| example of science conclusion: Nature , 1887 |
| example of science conclusion: Guide to Implementing the Next Generation Science Standards National Research Council, Division of Behavioral and Social Sciences and Education, Board on Science Education, Committee on Guidance on Implementing the Next Generation Science Standards, 2015-03-27 A Framework for K-12 Science Education and Next Generation Science Standards (NGSS) describe a new vision for science learning and teaching that is catalyzing improvements in science classrooms across the United States. Achieving this new vision will require time, resources, and ongoing commitment from state, district, and school leaders, as well as classroom teachers. Successful implementation of the NGSS will ensure that all K-12 students have high-quality opportunities to learn science. Guide to Implementing the Next Generation Science Standards provides guidance to district and school leaders and teachers charged with developing a plan and implementing the NGSS as they change their curriculum, instruction, professional learning, policies, and assessment to align with the new standards. For each of these elements, this report lays out recommendations for action around key issues and cautions about potential pitfalls. Coordinating changes in these aspects of the education system is challenging. As a foundation for that process, Guide to Implementing the Next Generation Science Standards identifies some overarching principles that should guide the planning and implementation process. The new standards present a vision of science and engineering learning designed to bring these subjects alive for all students, emphasizing the satisfaction of pursuing compelling questions and the joy of discovery and invention. Achieving this vision in all science classrooms will be a major undertaking and will require changes to many aspects of science education. Guide to Implementing the Next Generation Science Standards will be a valuable resource for states, districts, and schools charged with planning and implementing changes, to help them achieve the goal of teaching science for the 21st century. |
| example of science conclusion: Communicating Science Effectively National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on the Science of Science Communication: A Research Agenda, 2017-03-08 Science and technology are embedded in virtually every aspect of modern life. As a result, people face an increasing need to integrate information from science with their personal values and other considerations as they make important life decisions about medical care, the safety of foods, what to do about climate change, and many other issues. Communicating science effectively, however, is a complex task and an acquired skill. Moreover, the approaches to communicating science that will be most effective for specific audiences and circumstances are not obvious. Fortunately, there is an expanding science base from diverse disciplines that can support science communicators in making these determinations. Communicating Science Effectively offers a research agenda for science communicators and researchers seeking to apply this research and fill gaps in knowledge about how to communicate effectively about science, focusing in particular on issues that are contentious in the public sphere. To inform this research agenda, this publication identifies important influences †psychological, economic, political, social, cultural, and media-related †on how science related to such issues is understood, perceived, and used. |
| example of science conclusion: Objectivity: A Very Short Introduction Stephen Gaukroger, 2012-05-24 - Is objectivity possible? - Can there be objectivity in matters of morals, or tastes? - What would a truly objective account of the world be like? - Is everything subjective, or relative? - Are moral judgments objective or culturally relative? Objectivity is both an essential and elusive philosophical concept. An account is generally considered to be objective if it attempts to capture the nature of the object studied without judgement of a conscious entity or subject. Objectivity stands in contrast to subjectivity: an objective account is impartial, one which could ideally be accepted by any subject, because it does not draw on any assumptions, prejudices, or values of particular subjects. Stephen Gaukroger shows that it is far from clear that we can resolve moral or aesthetic disputes in this way and it has often been argued that such an approach is not always appropriate for disciplines that deal with human, rather than natural, phenomena. Moreover, even in those cases where we seek to be objective, it may be difficult to judge what a truly objective account would look like, and whether it is achievable. This Very Short Introduction demonstrates that there are a number of common misunderstandings about what objectivity is, and explores the theoretical and practical problems of objectivity by assessing the basic questions raised by it. As well as considering the core philosophical issues, Gaukroger also deals with the way in which particular understandings of objectivity impinge on social research, science, and art. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| example of science conclusion: Story Starters and Science Notebooking Sandy Buczynski, Kristin Fontichiaro, 2009-05-19 Story Starters and Science Notebooking: Developing Student Thinking Through Literacy and Inquiry is designed to provide a meaningful, comfortable framework in which teachers and parents can encourage elementary children to explore scientific ideas in an inquiry-oriented format. The basis for each scientific concept presented in Story Starters and Science Notebooking is embedded in a story appropriate for elementary-aged children. The activity that follows each narrative encourages learners to observe, compare, gather data, organize or classify, and draw conclusions about the problem posed from the story. Because current scientific knowledge and understanding guide scientific investigations, background information in each chapter provides teachers with a synopsis of the scientific concept involved in the activity for that story. The story starters present a framework for inquiry, which eliminates the free-wheeling, uncontrolled, and unstructured view some teachers have of inquiry. These are either original stories or familiar children's stories that ask learners to investigate a possible scientific explanation for a problem or scenario. Learners then communicate their findings in an oral, written, pictorial, or technological form back to a lead character from the story. Extension activities provide an opportunity for learners to compare their answers with what scientists already know about the world and also motivate them to frame new questions. Grades 3-6 |
| example of science conclusion: Journal of the Transactions of the Victoria Institute, Or Philosophical Society of Great Britain , 1889 |
| example of science conclusion: Biophysical Measurement in Experimental Social Science Research Gigi Foster, 2019-02-08 Biophysical Measurement in Experimental Social Science Research is an ideal primer for the experimental social scientist wishing to update their knowledge and skillset in the area of laboratory-based biophysical measurement. Many behavioral laboratories across the globe have acquired increasingly sophisticated biophysical measurement equipment, sometimes for particular research projects or for financial or institutional reasons. Yet the expertise required to use this technology and integrate the measures it can generate on human subjects into successful social science research endeavors is often scarce and concentrated amongst a small minority of researchers. This book aims to open the door to wider and more productive use of biophysical measurement in laboratory-based experimental social science research. Suitable for doctoral students through to established researchers, the volume presents examples of the successful integration of biophysical measures into analyses of human behavior, discussions of the academic and practical limitations of laboratory-based biophysical measurement, and hands-on guidance about how different biophysical measurement devices are used. A foreword and concluding chapters comprehensively synthesize and compare biophysical measurement options, address academic, ethical and practical matters, and address the broader historical and scientific context. Research chapters demonstrate the academic potential of biophysical measurement ranging fully across galvanic skin response, heart rate monitoring, eye tracking and direct neurological measurements. An extended Appendix showcases specific examples of device adoption in experimental social science lab settings. - Demonstrates the strengths and limitations of different tools, in terms of both research objectives and practicality - Provides hands-on guidance for device usage and data integration and assessment - Compares and contrasts the use of different biophysical data options for different research objectives and in different disciplines |
| example of science conclusion: Social Science Research Anol Bhattacherjee, 2012-04-01 This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages. |
| example of science conclusion: Science John Michels (Journalist), 1926 |
| example of science conclusion: Communicating in Science Vernon Booth, 1993-03-25 Writing scientific papers and giving talks at meetings and conferences are essential parts of research scientists' work, and this short, straightforwardly written book will help workers in all scientific disciplines to present their results effectively. The first chapter is about writing a scientific paper and is a revision of a prize-winning essay. Later chapters discuss the preparation of typescripts, speaking at meetings and writing theses. There are also chapters addressed particularly to those scientists to whom English is a foreign language and to those in North America. The last chapter gives information about dictionaries, style books and other literature. The book draws on the author's wealth of experience in presenting his own work and in editing the work of others, and he draws his examples from a range of subjects. |
| example of science conclusion: Technen: Elements of Recent History of Information Technologies with Epistemological Conclusions Andrzej Piotr Wierzbicki, 2014-07-25 The book expresses the conviction that the art of creating tools – Greek techne – changes its character together with the change of civilization epochs and co-determines such changes. This does not mean that tools typical for a civilization epoch determine it completely, but they change our way of perceiving and interpreting the world. There might have been many such epochs in the history of human civilization (much more than the three waves of agricultural, industrial and information civilization). This is expressed by the title Technen of the book, where n denotes a subsequent civilization epoch. During last fifty years we observed a decomposition of the old episteme (understood as a way of creating and interpreting knowledge characteristic for a given civilization epoch) of modernism, which was an episteme typical for industrial civilization. Today, the world is differently understood by the representatives of three different cultural spheres: of strict and natural sciences; of human and social sciences (especially by their part inclined towards postmodernism) and technical sciences that have a different episteme than even that of strict and natural sciences. Thus, we observe today not two cultures, but three different episteme. The book consists of four parts. First contains basic epistemological observations, second is devoted to selected elements of recent history of information technologies, third contains more detailed epistemological and general discussions, fourth specifies conclusions. The book is written from the cognitive perspective of technical sciences, with a full awareness – and discussion – of its differences from the cognitive perspective of strict sciences or human and social sciences. The main thesis of the book is that informational revolution will probably lead to a formation of a new episteme. The book includes discussions of many issues related to such general perspective, such as what is technology proper; what is intuition from a perspective of technology and of evolutionary naturalism; what are the reasons for and how large are the delays between a fundamental invention and its broad social utilization; what is the fundamental logical error (using paradoxes that are not real, only apparent) of the tradition of sceptical philosophy; what are rational foundations and examples of emergence of order out of chaos; whether civilization development based on two positive feedbacks between science, technology and the market might lead inevitably to a self-destruction of human civilization; etc. |
| example of science conclusion: Fragments of Science John Tyndall, 1915 |
| example of science conclusion: The Great Mental Models, Volume 1 Shane Parrish, Rhiannon Beaubien, 2024-10-15 Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage. |
| example of science conclusion: Science Conspectus , 1910 |
| example of science conclusion: The Oxford Companion to the History of Modern Science John L. Heilbron, 2003-02-14 Containing 609 encyclopedic articles written by more than 200 prominent scholars, The Oxford Companion to the History of Modern Science presents an unparalleled history of the field invaluable to anyone with an interest in the technology, ideas, discoveries, and learned institutions that have shaped our world over the past five centuries. Focusing on the period from the Renaissance to the early twenty-first century, the articles cover all disciplines (Biology, Alchemy, Behaviorism), historical periods (the Scientific Revolution, World War II, the Cold War), concepts (Hypothesis, Space and Time, Ether), and methodologies and philosophies (Observation and Experiment, Darwinism). Coverage is international, tracing the spread of science from its traditional centers and explaining how the prevailing knowledge of non-Western societies has modified or contributed to the dominant global science as it is currently understood. Revealing the interplay between science and the wider culture, the Companion includes entries on topics such as minority groups, art, religion, and science's practical applications. One hundred biographies of the most iconic historic figures, chosen for their contributions to science and the interest of their lives, are also included. Above all The Oxford Companion to the History of Modern Science is a companion to world history: modern in coverage, generous in breadth, and cosmopolitan in scope. The volume's utility is enhanced by a thematic outline of the entire contents, a thorough system of cross-referencing, and a detailed index that enables the reader to follow a specific line of inquiry along various threads from multiple starting points. Each essay has numerous suggestions for further reading, all of which favor literature that is accessible to the general reader, and a bibliographical essay provides a general overview of the scholarship in the field. Lastly, as a contribution to the visual appeal of the Companion, over 100 black-and-white illustrations and an eight-page color section capture the eye and spark the imagination. |
| example of science conclusion: Intelligent Systems And Soft Computing For Nuclear Science And Industry - Proceedings Of The 2nd International Flins Workshop Da Ruan, Pierre D'hondt, Etienne E Kerre, Paul Govaerts, 1996-07-29 Following FLINS '94, the 1st International workshop on fuzzy logic and intelligent technologies in nuclear science, FLINS '96 aimed to introduce the principles of intelligent systems and soft computing, such as fuzzy logic, neural networks, genetic algorithms (and any combination of these three), knowledge-based expert systems and complex problem-solving techniques, in nuclear science and industry and in related fields.This volume presents carefully selected papers drawn from more than 20 countries. It covers theoretical aspects of intelligent systems and soft computing, together with their applications in nuclear science and industry. |
| example of science conclusion: The Science of Logic Peter Coffey, 1912 |
EXAMPLE Definition & Meaning - Merriam-Webster
The meaning of EXAMPLE is one that serves as a pattern to be imitated or not to be imitated. How to use example in a sentence. Synonym Discussion of Example.
EXAMPLE | English meaning - Cambridge Dictionary
EXAMPLE definition: 1. something that is typical of the group of things that it is a member of: 2. a way of helping…. Learn more.
EXAMPLE Definition & Meaning | Dictionary.com
one of a number of things, or a part of something, taken to show the character of the whole. This painting is an example of his early work. a pattern or model, as of something to be imitated or …
Example - definition of example by The Free Dictionary
1. one of a number of things, or a part of something, taken to show the character of the whole. 2. a pattern or model, as of something to be imitated or avoided: to set a good example. 3. an …
Example Definition & Meaning - YourDictionary
To be illustrated or exemplified (by). Wear something simple; for example, a skirt and blouse.
EXAMPLE - Meaning & Translations | Collins English Dictionary
An example of something is a particular situation, object, or person which shows that what is being claimed is true. 2. An example of a particular class of objects or styles is something that …
example noun - Definition, pictures, pronunciation and usage …
used to emphasize something that explains or supports what you are saying; used to give an example of what you are saying. There is a similar word in many languages, for example in …
Example - Definition, Meaning & Synonyms - Vocabulary.com
An example is a particular instance of something that is representative of a group, or an illustration of something that's been generally described. Example comes from the Latin word …
example - definition and meaning - Wordnik
noun Something that serves as a pattern of behaviour to be imitated (a good example) or not to be imitated (a bad example). noun A person punished as a warning to others. noun A parallel …
EXAMPLE Synonyms: 20 Similar Words - Merriam-Webster
Some common synonyms of example are case, illustration, instance, sample, and specimen. While all these words mean "something that exhibits distinguishing characteristics in its …
EXAMPLE Definition & Meaning - Merriam-Webster
The meaning of EXAMPLE is one that serves as a pattern to be imitated or not to be imitated. How to use example in a sentence. Synonym Discussion of Example.
EXAMPLE | English meaning - Cambridge Dictionary
EXAMPLE definition: 1. something that is typical of the group of things that it is a member of: 2. a way of helping…. Learn more.
EXAMPLE Definition & Meaning | Dictionary.com
one of a number of things, or a part of something, taken to show the character of the whole. This painting is an example of his early work. a pattern or model, as of something to be imitated or …
Example - definition of example by The Free Dictionary
1. one of a number of things, or a part of something, taken to show the character of the whole. 2. a pattern or model, as of something to be imitated or avoided: to set a good example. 3. an …
Example Definition & Meaning - YourDictionary
To be illustrated or exemplified (by). Wear something simple; for example, a skirt and blouse.
EXAMPLE - Meaning & Translations | Collins English Dictionary
An example of something is a particular situation, object, or person which shows that what is being claimed is true. 2. An example of a particular class of objects or styles is something that …
example noun - Definition, pictures, pronunciation and usage …
used to emphasize something that explains or supports what you are saying; used to give an example of what you are saying. There is a similar word in many languages, for example in …
Example - Definition, Meaning & Synonyms - Vocabulary.com
An example is a particular instance of something that is representative of a group, or an illustration of something that's been generally described. Example comes from the Latin word …
example - definition and meaning - Wordnik
noun Something that serves as a pattern of behaviour to be imitated (a good example) or not to be imitated (a bad example). noun A person punished as a warning to others. noun A parallel …
EXAMPLE Synonyms: 20 Similar Words - Merriam-Webster
Some common synonyms of example are case, illustration, instance, sample, and specimen. While all these words mean "something that exhibits distinguishing characteristics in its …
