Download or read book Teaching Machines written by Audrey Watters and published by MIT Press. This book was released on 2023-02-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: How ed tech was born: Twentieth-century teaching machines--from Sidney Pressey's mechanized test-giver to B. F. Skinner's behaviorist bell-ringing box. Contrary to popular belief, ed tech did not begin with videos on the internet. The idea of technology that would allow students to "go at their own pace" did not originate in Silicon Valley. In Teaching Machines, education writer Audrey Watters offers a lively history of predigital educational technology, from Sidney Pressey's mechanized positive-reinforcement provider to B. F. Skinner's behaviorist bell-ringing box. Watters shows that these machines and the pedagogy that accompanied them sprang from ideas--bite-sized content, individualized instruction--that had legs and were later picked up by textbook publishers and early advocates for computerized learning. Watters pays particular attention to the role of the media--newspapers, magazines, television, and film--in shaping people's perceptions of teaching machines as well as the psychological theories underpinning them. She considers these machines in the context of education reform, the political reverberations of Sputnik, and the rise of the testing and textbook industries. She chronicles Skinner's attempts to bring his teaching machines to market, culminating in the famous behaviorist's efforts to launch Didak 101, the "pre-verbal" machine that taught spelling. (Alternate names proposed by Skinner include "Autodidak," "Instructomat," and "Autostructor.") Telling these somewhat cautionary tales, Watters challenges what she calls "the teleology of ed tech"--the idea that not only is computerized education inevitable, but technological progress is the sole driver of events.
Download or read book Teaching Machines written by Bill Ferster and published by JHU Press. This book was released on 2014-11-17 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology promises to make learning better, cheaper, faster—but rarely has it kept that promise. The allure of educational technology is easy to understand. Classroom instruction is an expensive and time-consuming process fraught with contradictory theories and frustratingly uneven results. Educators, inspired by machines’ contributions to modern life, have been using technology to facilitate teaching for centuries. In Teaching Machines, Bill Ferster examines past attempts to automate instruction from the earliest use of the postal service for distance education to the current maelstrom surrounding Massive Open Online Courses. He tells the stories of the entrepreneurs and visionaries who, beginning in the colonial era, developed and promoted various instructional technologies. Ferster touches on a wide range of attempts to enhance the classroom experience with machines, from hornbooks, the Chautauqua movement, and correspondence courses to B. F. Skinner’s teaching machine, intelligent tutoring systems, and eLearning. The famed progressive teachers, researchers, and administrators that the book highlights often overcame substantial hurdles to implement their ideas, but not all of them succeeded in improving the quality of education. Teaching Machines provides invaluable new insight into our current debate over the efficacy of educational technology.
Download or read book The Technology of Teaching written by B. F. Skinner and published by B. F. Skinner Foundation. This book was released on 2016-04-26 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: On Parent's Day, in 1952, B. F. Skinner visited his daughter's fourth grade math class. As he watched the lesson, he became increasingly uncomfortable. Almost every principle of effective teaching that he had studied for more than 20 years was being violated in that classroom. Yet it was a typical class. The teacher showed how to solve the day's problems, then gave the students a worksheet to do. Some children began to work readily while others shifted uncomfortably in their chairs, or raised their hands for help. The teacher went from desk to desk, giving help and feedback. Skinner knew what was needed. Each student should be given a problem tailored precisely to his or her skill level, not to the class average, and every answer needed to be assessed immediately to determine the next step. The task was clearly impossible for one teacher. That afternoon, Skinner set to work on a teaching machine. Today's computers have made the mechanical machine obsolete, but the principles of how to design instruction in steps that lead from a basic level to competent performance are as valid today as they were in the 20th century. This book brings together Skinner's writings on education during the years he was most involved in improving education.
Download or read book The World of Teaching Machines written by Charles I. Foltz and published by . This book was released on 1961 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book digitalSTS written by Janet Vertesi and published by Princeton University Press. This book was released on 2019-05-07 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scholars across the humanities, social sciences, and information sciences are grappling with how best to study virtual environments, use computational tools in their research, and engage audiences with their results. Classic work in science and technology studies (STS) has played a central role in how these fields analyze digital technologies, but many of its key examples do not speak to today’s computational realities. This groundbreaking collection brings together a world-class group of contributors to refresh the canon for contemporary digital scholarship. In twenty-five pioneering and incisive essays, this unique digital field guide offers innovative new approaches to digital scholarship, the design of digital tools and objects, and the deployment of critically grounded technologies for analysis and discovery. Contributors cover a broad range of topics, including software development, hackathons, digitized objects, diversity in the tech sector, and distributed scientific collaborations. They discuss methodological considerations of social networks and data analysis, design projects that can translate STS concepts into durable scientific work, and much more. Featuring a concise introduction by Janet Vertesi and David Ribes and accompanied by an interactive microsite, this book provides new perspectives on digital scholarship that will shape the agenda for tomorrow’s generation of STS researchers and practitioners.
Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
Download or read book Learners Without Borders written by Yong Zhao and published by Corwin Press. This book was released on 2021-06-30 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: The future of education centers empowered students in a global learning ecosystem. Despite decades of reform, the traditional borders of education—graduation, curriculum, classrooms, schools—have failed to deliver on the goals of excellence and equity. Despite massive societal changes, education remains controlled by an old mindset. It is time to change that limiting mindset and, more importantly, the ineffective practices in education. To truly serve all learners, future classrooms must remove the boundaries of learning and become student-centered, culturally responsive, and personalized—supportive and equitable environments where each student can direct their own learning and seek multiple pathways to skills and knowledge in a global learning ecosystem. This compelling call for transformative change offers all involved in education Evidence-based arguments that reveal the need to break the traditional borders that limit learning Strategies to personalize learning and remove the confinement of traditional pathways Examples from around the world to create equitable and student-centric learning environments Resources for creating a school learning environment that expands opportunities for personalized learning into the global learning ecosystem It is time to now imagine a different kind of learning, without borders, and to begin the shifts in practice that will result in personalized learning for all students.
Download or read book Machine Learning for Kids written by Dale Lane and published by No Starch Press. This book was released on 2021-01-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
Download or read book Teaching Machines written by Bill Ferster and published by JHU Press. This book was released on 2014-11-17 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology promises to make learning better, cheaper, faster—but rarely has it kept that promise. The allure of educational technology is easy to understand. Classroom instruction is an expensive and time-consuming process fraught with contradictory theories and frustratingly uneven results. Educators, inspired by machines’ contributions to modern life, have been using technology to facilitate teaching for centuries. In Teaching Machines, Bill Ferster examines past attempts to automate instruction from the earliest use of the postal service for distance education to the current maelstrom surrounding Massive Open Online Courses. He tells the stories of the entrepreneurs and visionaries who, beginning in the colonial era, developed and promoted various instructional technologies. Ferster touches on a wide range of attempts to enhance the classroom experience with machines, from hornbooks, the Chautauqua movement, and correspondence courses to B. F. Skinner’s teaching machine, intelligent tutoring systems, and eLearning. The famed progressive teachers, researchers, and administrators that the book highlights often overcame substantial hurdles to implement their ideas, but not all of them succeeded in improving the quality of education. Teaching Machines provides invaluable new insight into our current debate over the efficacy of educational technology.
Download or read book Human Machine written by Paul R. Daugherty and published by Harvard Business Press. This book was released on 2018-03-20 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
Download or read book The Flickering Mind written by Todd Oppenheimer and published by Random House. This book was released on 2007-12-18 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Flickering Mind, by National Magazine Award winner Todd Oppenheimer, is a landmark account of the failure of technology to improve our schools and a call for renewed emphasis on what really works. American education faces an unusual moment of crisis. For decades, our schools have been beaten down by a series of curriculum fads, empty crusades for reform, and stingy funding. Now education and political leaders have offered their biggest and most expensive promise ever—the miracle of computers and the Internet—at a cost of approximately $70 billion just during the decade of the 1990s. Computer technology has become so prevalent that it is transforming nearly every corner of the academic world, from our efforts to close the gap between rich and poor, to our hopes for school reform, to our basic methods of developing the human imagination. Technology is also recasting the relationships that schools strike with the business community, changing public beliefs about the demands of tomorrow’s working world, and reframing the nation’s systems for researching, testing, and evaluating achievement. All this change has led to a culture of the flickering mind, and a generation teetering between two possible futures. In one, youngsters have a chance to become confident masters of the tools of their day, to better address the problems of tomorrow. Alternatively, they can become victims of commercial novelties and narrow measures of ability, underscored by misplaced faith in standardized testing. At this point, America’s students can’t even make a fair choice. They are an increasingly distracted lot. Their ability to reason, to listen, to feel empathy, is quite literally flickering. Computers and their attendant technologies did not cause all these problems, but they are quietly accelerating them. In this authoritative and impassioned account of the state of education in America, Todd Oppenheimer shows why it does not have to be this way. Oppenheimer visited dozens of schools nationwide—public and private, urban and rural—to present the compelling tales that frame this book. He consulted with experts, read volumes of studies, and came to strong and persuasive conclusions: that the essentials of learning have been gradually forgotten and that they matter much more than the novelties of technology. He argues that every time we computerize a science class or shut down a music program to pay for new hardware, we lose sight of what our priority should be: “enlightened basics.” Broad in scope and investigative in treatment, The Flickering Mind will not only contribute to a vital public conversation about what our schools can and should be—it will define the debate.
Download or read book Teaching Online written by Claire Howell Major and published by JHU Press. This book was released on 2015-03-15 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demystifies online teaching for both enthusiastic and wary educators and helps faculty who teach online do their best work as digital instructors. It is difficult to imagine a college class today that does not include some online component—whether a simple posting of a syllabus to course management software, the use of social media for communication, or a full-blown course offering through a MOOC platform. In Teaching Online, Claire Howell Major describes for college faculty the changes that accompany use of such technologies and offers real-world strategies for surmounting digital teaching challenges. Teaching with these evolving media requires instructors to alter the ways in which they conceive of and do their work, according to Major. They must frequently update their knowledge of learning, teaching, and media, and they need to develop new forms of instruction, revise and reconceptualize classroom materials, and refresh their communication patterns. Faculty teaching online must also reconsider the student experience and determine what changes for students ultimately mean for their own work and for their institutions. Teaching Online presents instructors with a thoughtful synthesis of educational theory, research, and practice as well as a review of strategies for managing the instructional changes involved in teaching online. In addition, this book presents examples of best practices from successful online instructors as well as cutting-edge ideas from leading scholars and educational technologists. Faculty members, researchers, instructional designers, students, administrators, and policy makers who engage with online learning will find this book an invaluable resource.
Download or read book Machine Learning for Time Series Forecasting with Python written by Francesca Lazzeri and published by John Wiley & Sons. This book was released on 2020-12-03 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models’ performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.
Download or read book Productivity Machines written by Corinna Schlombs and published by MIT Press. This book was released on 2019-10-01 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: How productivity culture and technology became emblematic of the American economic system in pre- and postwar Germany. The concept of productivity originated in a statistical measure of output per worker or per work-hour, calculated by the US Bureau of Labor Statistics. A broader productivity culture emerged in 1920s America, as Henry Ford and others linked methods of mass production and consumption to high wages and low prices. These ideas were studied eagerly by a Germany in search of economic recovery after World War I, and, decades later, the Marshall Plan promoted productivity in its efforts to help post–World War II Europe rebuild. In Productivity Machines, Corinna Schlombs examines the transatlantic history of productivity technology and culture in the two decades before and after World War II. She argues for the interpretive flexibility of productivity: different groups viewed productivity differently at different times. Although it began as an objective measure, productivity came to be emblematic of the American economic system; post-World War II West Germany, however, adapted these ideas to its own political and economic values. Schlombs explains that West German unionists cast a doubtful eye on productivity's embrace of plant-level collective bargaining; unions fought for codetermination—the right to participate in corporate decisions. After describing German responses to US productivity, Schlombs offers an in-depth look at labor relations in one American company in Germany—that icon of corporate America, IBM. Finally, Schlombs considers the emergence of computer technology—seen by some as a new symbol of productivity but by others as the means to automate workers out of their jobs.
Download or read book The Children s Machine written by Seymour Papert and published by Basic Books. This book was released on 1994-04-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his classsic book, Mindstorms: Children, Computers, and powerful Ideas, Seymour Papert set out a vision of how computers could change school. In The Children's Machine he now looks back over a decade during which American schools acquired more than three million computers and assesses progress and resistance to progress.
Download or read book Why They Can t Write written by John Warner and published by JHU Press. This book was released on 2018-12-03 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important challenge to what currently masquerades as conventional wisdom regarding the teaching of writing. There seems to be widespread agreement that—when it comes to the writing skills of college students—we are in the midst of a crisis. In Why They Can't Write, John Warner, who taught writing at the college level for two decades, argues that the problem isn't caused by a lack of rigor, or smartphones, or some generational character defect. Instead, he asserts, we're teaching writing wrong. Warner blames this on decades of educational reform rooted in standardization, assessments, and accountability. We have done no more, Warner argues, than conditioned students to perform "writing-related simulations," which pass temporary muster but do little to help students develop their writing abilities. This style of teaching has made students passive and disengaged. Worse yet, it hasn't prepared them for writing in the college classroom. Rather than making choices and thinking critically, as writers must, undergraduates simply follow the rules—such as the five-paragraph essay—designed to help them pass these high-stakes assessments. In Why They Can't Write, Warner has crafted both a diagnosis for what ails us and a blueprint for fixing a broken system. Combining current knowledge of what works in teaching and learning with the most enduring philosophies of classical education, this book challenges readers to develop the skills, attitudes, knowledge, and habits of mind of strong writers.
Download or read book Lifelong Machine Learning Second Edition written by Zhiyuan Sun and published by Springer Nature. This book was released on 2022-06-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.
