Science, Evidence, and Inference in Education

Science, Evidence, and Inference in Education

Author: National Research Council

Publisher: National Academies Press

Published: 2001-06-23

Total Pages: 45

ISBN-13: 030907570X

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Research on education has come into the political spotlight as the demand grows for reliable and credible information for the guidance of policy and practice in the education reform environment. Many debates among the education research community feature questions concerning the nature of evidence and these questions have also appeared in broader policy and practice arenas. Inquiry has generally, over the past years, created bodies of scientific knowledge that have profound implications for education. Dramatic advances in understanding how people learn, how young children acquire early reading skills, and how to design and evaluate educational and psychological measurements is a good example of this. However, the highly contextualized nature of education and the wide range of disciplinary perspectives that rely on it have made the identification of reducible, generalizable principles difficult and slow to achieve. Due to this, the U.S. Department of Education's National Educational Research Policy and Priorities Board (NERPPB) has asked the NRC to establish a study committee to consider the scientific underpinnings of research in education. The committee consists of members with expertise in statistics, psychology, sociology, anthropology, philosophy of science, history of education, economics, chemistry, biology, and education practice. The committee worked with the three questions in mind: What are the principles of scientific quality in education research?, How can research-based knowledge in education cumulate?, and How can a federal research agency promote and protect scientific quality in the education research it supports?. A workshop was held on March 7-8, 2001 that was organized into three main sessions: Supporting Scientific Quality at the Federal level, The Interface of Research and Practice in Education, and Evidence and Inference. Science, Evidence, and Inference in Education: Report of a Workshop summarizes this workshop through these three ideas. The report also includes what the committee plans to do next, the workshop agenda, and information on the workshop's participants and speakers.


Methods Matter

Methods Matter

Author: Richard J. Murnane

Publisher: Oxford University Press

Published: 2010-09-17

Total Pages: 414

ISBN-13: 0199890153

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Educational policy-makers around the world constantly make decisions about how to use scarce resources to improve the education of children. Unfortunately, their decisions are rarely informed by evidence on the consequences of these initiatives in other settings. Nor are decisions typically accompanied by well-formulated plans to evaluate their causal impacts. As a result, knowledge about what works in different situations has been very slow to accumulate. Over the last several decades, advances in research methodology, administrative record keeping, and statistical software have dramatically increased the potential for researchers to conduct compelling evaluations of the causal impacts of educational interventions, and the number of well-designed studies is growing. Written in clear, concise prose, Methods Matter: Improving Causal Inference in Educational and Social Science Research offers essential guidance for those who evaluate educational policies. Using numerous examples of high-quality studies that have evaluated the causal impacts of important educational interventions, the authors go beyond the simple presentation of new analytical methods to discuss the controversies surrounding each study, and provide heuristic explanations that are also broadly accessible. Murnane and Willett offer strong methodological insights on causal inference, while also examining the consequences of a wide variety of educational policies implemented in the U.S. and abroad. Representing a unique contribution to the literature surrounding educational research, this landmark text will be invaluable for students and researchers in education and public policy, as well as those interested in social science.


Model Based Inference in the Life Sciences

Model Based Inference in the Life Sciences

Author: David R. Anderson

Publisher: Springer Science & Business Media

Published: 2007-12-22

Total Pages: 203

ISBN-13: 0387740759

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This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.


Computer Age Statistical Inference, Student Edition

Computer Age Statistical Inference, Student Edition

Author: Bradley Efron

Publisher: Cambridge University Press

Published: 2021-06-17

Total Pages: 514

ISBN-13: 1108915876

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The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.


Scientific Research in Education

Scientific Research in Education

Author: National Research Council

Publisher: National Academies Press

Published: 2002-03-28

Total Pages: 204

ISBN-13: 0309133092

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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.


Inquiry and the National Science Education Standards

Inquiry and the National Science Education Standards

Author: National Research Council

Publisher: National Academies Press

Published: 2000-05-03

Total Pages: 223

ISBN-13: 0309064767

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Humans, especially children, are naturally curious. Yet, people often balk at the thought of learning scienceâ€"the "eyes glazed over" syndrome. Teachers may find teaching science a major challenge in an era when science ranges from the hardly imaginable quark to the distant, blazing quasar. Inquiry and the National Science Education Standards is the book that educators have been waiting forâ€"a practical guide to teaching inquiry and teaching through inquiry, as recommended by the National Science Education Standards. This will be an important resource for educators who must help school boards, parents, and teachers understand "why we can't teach the way we used to." "Inquiry" refers to the diverse ways in which scientists study the natural world and in which students grasp science knowledge and the methods by which that knowledge is produced. This book explains and illustrates how inquiry helps students learn science content, master how to do science, and understand the nature of science. This book explores the dimensions of teaching and learning science as inquiry for K-12 students across a range of science topics. Detailed examples help clarify when teachers should use the inquiry-based approach and how much structure, guidance, and coaching they should provide. The book dispels myths that may have discouraged educators from the inquiry-based approach and illuminates the subtle interplay between concepts, processes, and science as it is experienced in the classroom. Inquiry and the National Science Education Standards shows how to bring the standards to life, with features such as classroom vignettes exploring different kinds of inquiries for elementary, middle, and high school and Frequently Asked Questions for teachers, responding to common concerns such as obtaining teaching supplies. Turning to assessment, the committee discusses why assessment is important, looks at existing schemes and formats, and addresses how to involve students in assessing their own learning achievements. In addition, this book discusses administrative assistance, communication with parents, appropriate teacher evaluation, and other avenues to promoting and supporting this new teaching paradigm.


Taking Science to School

Taking Science to School

Author: National Research Council

Publisher: National Academies Press

Published: 2007-04-16

Total Pages: 404

ISBN-13: 0309133831

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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.


Statistical Inference as Severe Testing

Statistical Inference as Severe Testing

Author: Deborah G. Mayo

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 503

ISBN-13: 1108563309

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Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.


Computer Age Statistical Inference

Computer Age Statistical Inference

Author: Bradley Efron

Publisher: Cambridge University Press

Published: 2016-07-21

Total Pages: 496

ISBN-13: 1108107958

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The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.


The Evidential Foundations of Probabilistic Reasoning

The Evidential Foundations of Probabilistic Reasoning

Author: David A. Schum

Publisher: Northwestern University Press

Published: 2001

Total Pages: 572

ISBN-13: 9780810118218

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In this work Schum develops a general theory of evidence as it is understood and applied across a broad range of disciplines and practical undertakings. He include insights from law, philosophy, logic, probability, semiotics, artificial intelligence, psychology and history.