What School Could Be offers an inspiring vision of what our teachers and students can accomplish if trusted with the challenge of developing the skills and ways of thinking needed to thrive in a world of dizzying technological change.
Innovation expert Ted Dintersmith took an unprecedented trip across America, visiting all fifty states in a single school year. He originally set out to raise awareness about the urgent need to reimagine education to prepare students for a world marked by innovation--but America's teachers one-upped him. All across the country, he met teachers in ordinary settings doing extraordinary things, creating innovative classrooms where children learn deeply and joyously as they gain purpose, agency, essential skillsets and mindsets, and real knowledge. Together, these new ways of teaching and learning offer a vision of what school could be―and a model for transforming schools throughout the United States and beyond. Better yet, teachers and parents don't have to wait for the revolution to come from above. They can readily implement small changes that can make a big difference.
America's clock is ticking. Our archaic model of education trains our kids for a world that no longer exists, and accelerating advances in technology are eliminating millions of jobs. But the trailblazing of many American educators gives us reasons for hope.
Capturing bold ideas from teachers and classrooms across America, What School Could Be provides a realistic and profoundly optimistic roadmap for creating cultures of innovation and real learning in all our schools.
From two leading experts in education and entrepreneurship, an urgent call for the radical re-imagining of American education so that we better equip students for the realities of the twenty-first century economy.
Today more than ever, we prize academic achievement, pressuring our children to get into the “right” colleges, have the highest GPAs, and pursue advanced degrees. But while students may graduate with credentials, by and large they lack the competencies needed to be thoughtful, engaged citizens and to get good jobs in our rapidly evolving economy. Our school system was engineered a century ago to produce a work force for a world that no longer exists. Alarmingly, our methods of schooling crush the creativity and initiative young people need to thrive in the twenty-first century.
In Most Likely to Succeed, bestselling author and education expert Tony Wagner and venture capitalist Ted Dintersmith call for a complete overhaul of the function and focus of American schools, sharing insights and stories from the front lines, including profiles of successful students, teachers, parents, and business leaders.
Most Likely to Succeed presents a new vision of American education, one that puts wonder, creativity, and initiative at the very heart of the learning process and prepares students for today’s economy. This book offers parents and educators a crucial guide to getting the best for their children and a roadmap for policymakers and opinion leaders.
WPCampus 2018 is three-day conference event filled with sessions, networking, and social events, covering a variety of topics, focused on WordPress in higher education. The third annual WPCampus conference will take place July 12-14, 2018 at Washington University in St. Louis in St. Louis, Missouri.
(1.0 is coming soon, but yes, I wouldn’t blame you for coming to this entirely correct conclusion. Returning to life.)
— Ben Werdmuller (@benwerd) May 8, 2018
There’s about to be a lot of deleted code. Convoy and commercial elements are going away. But the open source project will be properly revived.
— Ben Werdmuller (@benwerd) May 8, 2018
This book introduces a temporal type theory, the first of its kind as far as we know. It is based on a standard core, and as such it can be formalized in a proof assistant such as Coq or Lean by adding a number of axioms. Well-known temporal logics---such as Linear and Metric Temporal Logic (LTL and MTL)---embed within the logic of temporal type theory. The types in this theory represent "behavior types". The language is rich enough to allow one to define arbitrary hybrid dynamical systems, which are mixtures of continuous dynamics---e.g. as described by a differential equation---and discrete jumps. In particular, the derivative of a continuous real-valued function is internally defined. We construct a semantics for the temporal type theory in the topos of sheaves on a translation-invariant quotient of the standard interval domain. In fact, domain theory plays a recurring role in both the semantics and the type theory.
This morning at ACT2018, David Spivak gave a VERY cool talk on using topos theory to model how airplanes can maintain a safe distance from each other in flight. You can watch the talk here! https://t.co/pUXZhj6SXA Also check out “Temporal Type Theory” at https://t.co/6LWNOQWtqw pic.twitter.com/7x9yjBwVIA
— Tai-Danae Bradley (@math3ma) May 2, 2018
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content.
Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included.
Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.
Traditional paddy rice farmers had to share labor and coordinate irrigation in a way that most wheat farmers did not. We observed people in everyday life to test whether these agricultural legacies gave rice-farming southern China a more interdependent culture and wheat-farming northern China a more independent culture. In Study 1, we counted 8964 people sitting in cafes in six cities and found that people in northern China were more likely to be sitting alone. In Study 2, we moved chairs together in Starbucks across the country so that they were partially blocking the aisle ( n = 678). People in northern China were more likely to move the chair out of the way, which is consistent with findings that people in individualistic cultures are more likely to try to control the environment. People in southern China were more likely to adjust the self to the environment by squeezing through the chairs. Even in China’s most modern cities, rice-wheat differences live on in everyday life.
The first episode, where Bret and Jim try making a podcast for the first time, and explain what they want the show to be.
New podcast announcement: @uhhyeahbret and I have started a podcast focused on the @dat_project. Listen to our first episode! It’s short, meta & experimental. In the near future, we intend to have guests and we’ll try to summarize news from the community. https://t.co/bTJKhoo77m pic.twitter.com/Cl3oxxgiLA
— Jim Pick (@jimpick) April 27, 2018
She’s the author of bestselling books and an incredibly popular blog, but Jenny Lawson showed up to our interview wondering, at least a little, if her appearance on this show and her whole career, really, was part of some delusion. It’s not. She’s the real thing: an incredibly funny and honest writer with a legion of fans, a very old decapitated and stuffed boar’s head named James Garfield, anxiety, depression, and a clear-eyed view of the world.
A show about clinical depression...with laughs? Well, yeah. Depression is an incredibly common and isolating disease experienced by millions, yet often stigmatized by society. The Hilarious World of Depression is a series of frank, moving, and, yes, funny conversations with top comedians who have dealt with this disease, hosted by veteran humorist and public radio host John Moe. Join guests such as Maria Bamford, Paul F. Tompkins, Andy Richter, and Jen Kirkman to learn how they’ve dealt with depression and managed to laugh along the way. If you have not met the disease personally, it’s almost certain that someone you know has, whether it’s a friend, family member, colleague, or neighbor. Depression is a vicious cycle of solitude and stigma that leaves people miserable and sometimes dead. Frankly, we’re not going to put up with that anymore.
The Hilarious World of Depression is not medical treatment and should not be seen as a substitute for therapy or medication. But it is a chance to gain some insight, have a few laughs, and realize that people with depression are not alone and that together, we can all feel a bit better.
The Hilarious World of Depression is made possible by a grant from HealthPartners and its Make It OK campaign, which works to reduce the stigma of mental health. Find out more at www.makeitok.org.
Special Issue: Mathematical Oncology
Its finally out! Our mammoth special issue of the @SpringerNature Bulletin of Mathematical Biology on #mathonco Mathematical Oncology! Jointly edited with @OxUniMaths Philip Maini and this is the single biggest issue in the journals history! @MoffittNews https://t.co/K9GqAPTjy8 pic.twitter.com/tUDs1ACZCW
— Sandy Anderson (@ara_anderson) April 28, 2018
Prior work established the benefits of server-recorded user engagement measures (e.g. clickthrough rates) for improving the results of search engines and recommendation systems. Client-side measures of post-click behavior received relatively little attention despite the fact that publishers have now the ability to measure how millions of people interact with their content at a fine resolution using client-side logging. In this study, we examine patterns of user engagement in a large, client-side log dataset of over 7.7 million page views (including both mobile and non-mobile devices) of 66,821 news articles from seven popular news publishers. For each page view we use three summary statistics: dwell time, the furthest position the user reached on the page, and the amount of interaction with the page through any form of input (touch, mouse move, etc.). We show that simple transformations on these summary statistics reveal six prototypical modes of reading that range from scanning to extensive reading and persist across sites. Furthermore, we develop a novel measure of information gain in text to capture the development of ideas within the body of articles and investigate how information gain relates to the engagement with articles. Finally, we show that our new measure of information gain is particularly useful for predicting reading of news articles before publication, and that the measure captures unique information not available otherwise.
To be published by Cambridge University Press in April 2018.
Upon publication this book will be available for purchase through Cambridge University Press and other standard distribution channels. Please see the publisher's web page to pre-order the book or to obtain further details on its publication date.
A draft, pre-publication copy of the book can be found below. This draft copy is made available for personal use only and must not be sold or redistributed.
This largely self-contained book on the theory of quantum information focuses on precise mathematical formulations and proofs of fundamental facts that form the foundation of the subject. It is intended for graduate students and researchers in mathematics, computer science, and theoretical physics seeking to develop a thorough understanding of key results, proof techniques, and methodologies that are relevant to a wide range of research topics within the theory of quantum information and computation. The book is accessible to readers with an understanding of basic mathematics, including linear algebra, mathematical analysis, and probability theory. An introductory chapter summarizes these necessary mathematical prerequisites, and starting from this foundation, the book includes clear and complete proofs of all results it presents. Each subsequent chapter includes challenging exercises intended to help readers to develop their own skills for discovering proofs concerning the theory of quantum information.
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