In Intentional Talk: How to Structure and Lead Productive Mathematical Discussions , authors Elham Kazemi and Allison Hintz provide teachers with a framework for planning and facilitating purposeful math talks that move group discussions to the next level while achieving a mathematical goal.Through detailed vignettes from both primary and upper elementary classrooms, the authors provide a window into how teachers lead discussions and make important pedagogical decisions along the way. By creating equitable opportunities to share ideas, teachers can orient students to one another while enforcing that all students are sense makers and their ideas are valued. They examine students’ roles as both listeners and talkers, offering numerous strategies for improving student participation. Intentional Talk includes a collection of lesson planning templates in the appendix to help teachers apply the right structure to discussions in their own classrooms.

    Time magazine has called him'perhaps the country's most outspoken critic of education's fixation on grades [and] test scores.' And the Washington Post says he is 'the most energetic and charismatic figure standing in the way of a major federal effort to make standardized curriculums and tests a fact of life in every U.S. school.'In this new collection of essays, Kohn takes on some of the most important and controversial topics in education of the last few years. His central focus is on the real goals of education-a topic, he argues, that we systematically ignore while lavishing attention on misguided models of learning and counterproductive techniques of motivation.The shift to talking about goals yields radical conclusions and wonderfully pungent essays that only Alfie Kohn could have written. From the title essay's challenge to conventional, conservative definitions of a good education to essays on standards and testing and grades that tally the severe educational costs of overemphasizing a narrow conception of achievement, Kohn boldly builds on his earlier work and writes for a wide audience. Kohn's new book will be greeted with enthusiasm by his many readers and by any teacher or parent looking for a refreshing perspective on today's debates about schools.

    To reach this unique audience, Whitlock and Schluter motivate learning with interesting biological and medical examples; they emphasize intuitive understanding; and they focus on real data. The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments. It also introduces the principles behind such modern topics as likelihood, linear models, meta-analysis and computer-intensive methods. Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and its variety of fascinating and relevant biological examples.

    students on international comparisons of mathematics competency. Paradoxically, Chinese teachers receive far less education than U.S. teachers--11 to 12 years of schooling versus 16 to 18 years of schooling.Studies of U.S. teacher knowledge often document insufficient subject matter knowledge in mathematics. But, they give few examples of the knowledge teachers need to support teaching, particularly the kind of teaching demanded by recent reforms in mathematics education.This book describes the nature and development of the "profound understanding of fundamental mathematics" that elementary teachers need to become accomplished mathematics teachers, and suggests why such teaching knowledge is much more common in China than the United States, despite the fact that Chinese teachers have less formal education than their U.S. counterparts.The studies described in this book suggest that Chinese teachers begin their teaching careers with a better understanding of elementary mathematics than that of most U.S. elementary teachers. Their understanding of the mathematics they teach and--equally important--of the ways that elementary mathematics can be presented to students, continues to grow throughout their professional lives.Teaching conditions in the United States, unlike those in China, militate against the development of elementary teachers' mathematical knowledge and its organization for teaching. The concluding chapter of the book suggests changes in teacher preparation, teacher support, and mathematics education research that might allow teachers in the United States to attain profound understanding of fundamental mathematics.

    From the moon landing hoax, to chemtrails, to the mind control dangers of fluoride, Dunning is here to sort the truth from the lies to tell you what really happened.

    Between their children’s educational needs; their roles as spouse, parent, and more; and their own individual desires and goals, these mothers and fathers struggle to accomplish all that must be done. In Help for the Harried Homeschooler, experienced homeschooler, author, and mother of four Christine Field offers sound advice for parents who want not only to achieve homeschooling success but also to reach a balance in their lives.

    Why, he wondered, do we inflict a full menu of mathematics—algebra, geometry, trigonometry, even calculus—on all young Americans, regardless of their interests or aptitudes?The Math Myth expands Hacker’s scrutiny of many widely held assumptions, like the notions that mathematics broadens our minds, that mastery of azimuths and asymptotes will be needed for most jobs, that the entire Common Core syllabus should be required of every student. He worries that a frenzied emphasis on STEM is diverting attention from other pursuits and subverting the spirit of the country.In fact, Hacker honors mathematics as a calling (he has been a professor of mathematics) and extols its glories and its goals. Yet he shows how mandating it for everyone prevents other talents from being developed and acts as an irrational barrier to graduation and careers. He proposes alternatives, including teaching facility with figures, quantitative reasoning, and understanding statistics.The Math Myth is sure to spark a heated and needed national conversation not just about mathematics but about the kind of people and society we want to be.

    H. Freeman and Company.  Visit the  Life, Eighth Edition preview site.  LIFE HAS EVOLVED. . . from its original publication to this dramatically revitalized Eighth Edition. LIFE has always shown students how biology works, offering an engaging and coherent presentation of the fundamentals of biology by describing the landmark experiments that revealed them. This edition builds on those strengths and introduces several innovations.As with previous editions, the Eighth Edition will also be available in three paperback volumes:  • Volume I: The Cell and Heredity, Chapters 1-20  • Volume II: Evolution, Diversity and Ecology, Chapters 1, 21-33, 52-57  • Volume III: Plants and Animals, Chapters 1, 34-51

    This is a clear, vivid text with charts and maps showing the positions of the constellations the year round.

    Julia Diggins masterfully recreates the atmosphere of ancient times, when men, using three simple tools, the string, the straightedge, and the shadow, discovered the basic principles and constructions of elementary geometry. Her book reveals how these discoveries related to the early civilizations of Mesopotamia, Egypt, and Greece.The fabric of the story is woven out of archeological and historical records and legends about the major men of mathematics. By reconstructing the events as they might have happened, Diggins enables the attentive reader to easily follow the pattern of reasoning that leads to an ingenious proof of the Pythagorean theorem, an appreciation of the significance of the Golden Mean in art and architecture, and the construction of the five regular solids.Out of print for 34 years, Julia Diggins' classic book is back and is a must-read for middle school students or for parents helping their children through their first geometry course. You will be fascinated with the graphic illustrations and written depiction of how the knowledge and wisdom of so many cultures helped shape our civilization today. This book is popular with teachers and parents who use Jamie York's Making Math Meaningful curriculum books.

    

    You will have numerous opportunities to practice statistical techniques through learning checks, examples, demonstrations, and problems. Exam preparation is made easy with a student companion website that provides tutorials, crossword puzzles, flashcards, learning objectives, and more!

    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

    It takes the student from the beginning assignment of a paper through the research phase to the finished paper. This second edition gives improvements and added material for such things as the expanding field of online research and doing church-related research in a professional manner. Resources for doing research are updated throughout the book.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details