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From the bestselling author of What the Best College Teachers Do, the story of a new breed of amazingly innovative courses that inspire students and improve learning Decades of research have produced profound insights into how student learning and motivation can be unleashed—and it’s not through technology or even the best of lectures. In Super Courses, education expert and bestselling author Ken Bain tells the fascinating story of enterprising college, graduate school, and high school teachers who are using evidence-based approaches to spark deeper levels of learning, critical thinking, and creativity—whether teaching online, in class, or in the field. Visiting schools across the United States as well as in China and Singapore, Bain, working with his longtime collaborator, Marsha Marshall Bain, uncovers super courses throughout the humanities and sciences. At the University of Virginia, undergrads contemplate the big questions that drove Tolstoy—by working with juveniles at a maximum-security correctional facility. Harvard physics students learn about the universe not through lectures but from their peers in a class where even reading is a social event. And students at a Dallas high school use dance to develop growth mindsets—and many of them go on to top colleges, including Juilliard. Bain defines these as super courses because they all use powerful researched-based elements to build a “natural critical learning environment” that fosters intrinsic motivation, self-directed learning, and self-reflective reasoning. Complete with sample syllabi, the book shows teachers how they can build their own super courses. The story of a hugely important breakthrough in education, Super Courses reveals how these classes can help students reach their full potential, equip them to lead happy and productive lives, and meet the world’s complex challenges.
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
The second edition of this innovative work again provides a unique perspective on the clinical discovery process by providing input from experts within the NIH on the principles and practice of clinical research. Molecular medicine, genomics, and proteomics have opened vast opportunities for translation of basic science observations to the bedside through clinical research. As an introductory reference it gives clinical investigators in all fields an awareness of the tools required to ensure research protocols are well designed and comply with the rigorous regulatory requirements necessary to maximize the safety of research subjects. Complete with sections on the history of clinical research and ethics, copious figures and charts, and sample documents it serves as an excellent companion text for any course on clinical research and as a must-have reference for seasoned researchers.*Incorporates new chapters on Managing Conflicts of Interest in Human Subjects Research, Clinical Research from the Patient's Perspective, The Clinical Researcher and the Media, Data Management in Clinical Research, Evaluation of a Protocol Budget, Clinical Research from the Industry Perspective, and Genetics in Clinical Research *Addresses the vast opportunities for translation of basic science observations to the bedside through clinical research*Delves into data management and addresses how to collect data and use it for discovery*Contains valuable, up-to-date information on how to obtain funding from the federal government
This collaboratively authored guide helps institutions navigate the uncharted waters of tagging course material as open educational resources (OER) or under a low-cost threshold by summarizing relevant state legislation, providing tips for working with stakeholders, and analyzing technological and process considerations. The first half of the book provides high-level analysis of the technology, legislation, and cultural change needed to operationalize course markings. The second half features case studies by Alexis Clifton, Rebel Cummings-Sauls, Michael Daly, Juville Dario-Becker, Tony DeFranco, Cindy Domaika, Ann Fiddler, Andrea Gillaspy Steinhilper, Rajiv Jhangiani, Leslie Kennedy, Brian Lindshield, Andrew McKinney, Nathan Smith, and Heather White.
Delpit explores a wide range of little-known research that conclusively demonstrates there is no achievement gap at birth and argues that poor teaching, negative stereotypes about African American intellectual inferiority, and a curriculum that still does not adequately connect to poor children's lives all conspire against the education prospects of poor children of color.
What makes a great teacher great? Who are the professors students remember long after graduation? This book, the conclusion of a fifteen-year study of nearly one hundred college teachers in a wide variety of fields and universities, offers valuable answers for all educators. The short answer is—it’s not what teachers do, it’s what they understand. Lesson plans and lecture notes matter less than the special way teachers comprehend the subject and value human learning. Whether historians or physicists, in El Paso or St. Paul, the best teachers know their subjects inside and out—but they also know how to engage and challenge students and to provoke impassioned responses. Most of all, they believe two things fervently: that teaching matters and that students can learn. In stories both humorous and touching, Ken Bain describes examples of ingenuity and compassion, of students’ discoveries of new ideas and the depth of their own potential. What the Best College Teachers Do is a treasure trove of insight and inspiration for first-year teachers and seasoned educators.