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"This is a splendid, down-to-earth book-especially for elementary teachers who want to do science but are unsure how to go about it. The intensity of children's interest is unmistakable. And Ellen's low-key style reassures the reader that children in any classroom can do work that is just as fine." Eleanor Duckworth, Harvard University "I want to embolden teachers who are uncertain about teaching science, and encourage others to give children's observations a central place in the curriculum." Ellen Doris When it first published, Ellen Doris' now-classic text rapidly became an indispensable resource for teachers who were searching for new ways to introduce students to science. This second edition will be every bit as essential for teachers and science leaders. Novice teachers and those looking to refresh their practice will find support to help children explore, experiment, and figure things out. Ellen deftly translates the theory of inquiry-based science instruction into methods teachers can use. She answers questions and offers advice on these central elements: how to begin how to inspire children's curiosity and facilitate their investigations how to assess children's understanding through their drawing, discussion, and writing how to structure classroom spaces, supervise fieldwork, and help children learn from one another how to keep children's priorities as well as science standards in mind. Lively classroom examples enrich Ellen's discussion. Her latest thinking will guide teachers and science leaders as they create contexts in which children can inquire, investigate, and collaborate.
What do scientists do all day? Find out in this beautifully illustrated book that features more than 100 scientists at work. Little ones can explore 14 different colorful scenes, turning the page after each to learn about eight special scientists you will find there. Spot the scientists and learn about the jobs they do in these fascinating places: nature reserve, health center, Arctic research station, hospital, museum, our new city, mission control and on the space station, observatory, aerospace center, botanical gardens, Earth Science center, energy plant, university, and technology and computer lab. Meet the environmentalist at the nature reserve, the nurse at the hospital, the archaeologist at the museum, the navigation engineer at mission control, the astronomer at the observatory, the fungi specialist at the botanical gardens...you'll be amazed at the range of things scientists work on.
This Palgrave Policy Essential draws together recent developments in the field of science in government, policy and public debate. Practice and academic insights from a wide variety of fields have both moved on in the last decade and this book provides a consolidated survey of the relatively well established but highly scattered set of insights about the provision of deeply technical expertise in policy making (models of climate or disease, risk, Artificial Intelligence and ethics, and so on). It goes on to link this to emerging ideas about futures thinking, public engagement, narrative, and the role of values and sentiment alongside the place of scientific and scholarly insights in public decision-making and debate. The book offers an accessible overview aimed at practitioners; policy-makers looking to understand how to work with researchers, researchers looking to work with policy-makers, and the increasing numbers and types of “brokers” - people working at the interface, in science advice, public engagement and communication of science, and in expert support to decision-making in the public and private sectors. In addition to outlining recent insights and placing them in the established frameworks of authors such as Pielke and Jasanoff, the book also brings in relevant areas less traditionally associated with the subject but of increasing importance, such as modelling, futures and narrative.
In early 2012, the global scientific community erupted with news that the elusive Higgs boson had likely been found, providing potent validation for the Standard Model of how the universe works. Scientists from more than one hundred countries contributed to this discovery—proving, beyond any doubt, that a new era in science had arrived, an era of multinationalism and cooperative reach. Globalization, the Internet, and digital technology all play a role in making this new era possible, but something more fundamental is also at work. In all scientific endeavors lies the ancient drive for sharing ideas and knowledge, and now this can be accomplished in a single tongue— English. But is this a good thing? In Does Science Need a Global Language?, Scott L. Montgomery seeks to answer this question by investigating the phenomenon of global English in science, how and why it came about, the forms in which it appears, what advantages and disadvantages it brings, and what its future might be. He also examines the consequences of a global tongue, considering especially emerging and developing nations, where research is still at a relatively early stage and English is not yet firmly established. Throughout the book, he includes important insights from a broad range of perspectives in linguistics, history, education, geopolitics, and more. Each chapter includes striking and revealing anecdotes from the front-line experiences of today’s scientists, some of whom have struggled with the reality of global scientific English. He explores topics such as student mobility, publication trends, world Englishes, language endangerment, and second language learning, among many others. What he uncovers will challenge readers to rethink their assumptions about the direction of contemporary science, as well as its future.
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.
A groundbreaking treatise by one of the great mathematicians of our time, who argues that highly effective thinking can be learned. What spurs on and inspires a great idea? Can we train ourselves to think in a way that will enable world-changing understandings and insights to emerge? Richard Hamming said we can, and first inspired a generation of engineers, scientists, and researchers in 1986 with "You and Your Research," an electrifying sermon on why some scientists do great work, why most don't, why he did, and why you should, too. The Art of Doing Science and Engineering is the full expression of what "You and Your Research" outlined. It's a book about thinking; more specifically, a style of thinking by which great ideas are conceived. The book is filled with stories of great people performing mighty deeds––but they are not meant to simply be admired. Instead, they are to be aspired to, learned from, and surpassed. Hamming consistently returns to Shannon’s information theory, Einstein’s relativity, Grace Hopper’s work on high-level programming, Kaiser’s work on digital fillers, and his own error-correcting codes. He also recounts a number of his spectacular failures as clear examples of what to avoid. Originally published in 1996 and adapted from a course that Hamming taught at the U.S. Naval Postgraduate School, this edition includes an all-new foreword by designer, engineer, and founder of Dynamicland Bret Victor, and more than 70 redrawn graphs and charts. The Art of Doing Science and Engineering is a reminder that a childlike capacity for learning and creativity are accessible to everyone. Hamming was as much a teacher as a scientist, and having spent a lifetime forming and confirming a theory of great people, he prepares the next generation for even greater greatness.
A vivid portrait of how Naval oversight shaped American oceanography, revealing what difference it makes who pays for science. What difference does it make who pays for science? Some might say none. If scientists seek to discover fundamental truths about the world, and they do so in an objective manner using well-established methods, then how could it matter who’s footing the bill? History, however, suggests otherwise. In science, as elsewhere, money is power. Tracing the recent history of oceanography, Naomi Oreskes discloses dramatic changes in American ocean science since the Cold War, uncovering how and why it changed. Much of it has to do with who pays. After World War II, the US military turned to a new, uncharted theater of warfare: the deep sea. The earth sciences—particularly physical oceanography and marine geophysics—became essential to the US Navy, which poured unprecedented money and logistical support into their study. Science on a Mission brings to light how this influx of military funding was both enabling and constricting: it resulted in the creation of important domains of knowledge but also significant, lasting, and consequential domains of ignorance. As Oreskes delves into the role of patronage in the history of science, what emerges is a vivid portrait of how naval oversight transformed what we know about the sea. It is a detailed, sweeping history that illuminates the ways funding shapes the subject, scope, and tenor of scientific work, and it raises profound questions about the purpose and character of American science. What difference does it make who pays? The short answer is: a lot.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
A scientific twist on a beloved children's classic that's sure to delight both parent and child! Scientist, Scientist, Who do you see? I see Marie Curie in her laboratory! The adored children's classic Brown Bear, Brown Bear gets a nerdy makeover in this science picture book by the #1 bestselling science author for kids. Chris Ferrie! Young readers will delight at taking a familiar text and poking fun at it all while learning about scientists and how they changed the world. Back matter includes brief biographical information of the featured scientists. This sweet baby scientist book parody is the perfect inspiration for scientists of all ages! One of the best books about scientists for kids of the year! Full of scientific rhyming fun, Scientist, Scientist, Who Do You See? features appearances by some of the world's greatest scientists! From Albert Einstein to Marie Curie and Ahmed Zewail, from Charles Darwin to Chien-Shiung Wu and Grace Hopper... and more!