This is an essential resource for anyone designing or facilitating online learning. It introduces an easy, practical model (R2D2: read, reflect, display, and do) that will show online educators how to deliver content in ways that benefit all types of learners (visual, auditory, observational, and kinesthetic) from a wide variety of backgrounds and skill levels. With a solid theoretical foundation and concrete guidance and examples, this book can be used as a handy reference, a professional guidebook, or a course text. The authors intend for it to help online instructors and instructional designers as well as those contemplating such positions design, develop, and deliver learner-centered online instruction. Empowering Online Learning has 25 unique activities for each phase of the R2D2 model as well as summary tables helping you pick and choose what to use whenever you need it. Each activity lists a description, skills addressed, advice, variations, cost, risk, and time index, and much more. This title is loaded with current information about emerging technologies (e.g., simulations, podcasts, wikis, blogs) and the Web 2.0. With a useful model, more than 100 online activities, the latest information on emerging technologies, hundreds of quickly accessible Web resources, and relevance to all types and ages of learners--Empowering Online Learning is a book whose time has come.

What's it really like to learn online?Learning Online: The Student Experience Online learning is ubiquitous for millions of students worldwide, yet our understanding of student experiences in online learning settings is limited. The geographic distance that separates faculty from students in an online environment is its signature feature, but it is also one that risks widening the gulf between teachers and learners. In Learning Online, George Veletsianos argues that in order to critique, understand, and improve online learning, we must examine it through the lens of student experience. Approaching the topic with stories that elicit empathy, compassion, and care, Veletsianos relays the diverse day-to-day experiences of online learners. Each in-depth chapter follows a single learner's experience while focusing on an important or noteworthy aspect of online learning, tackling everything from demographics, attrition, motivation, and loneliness to cheating, openness, flexibility, social media, and digital divides. Veletsianos also draws on these case studies to offer recommendations for the future and lessons learned. The elusive nature of online learners' experiences, the book reveals, is a problem because it prevents us from doing better: from designing more effective online courses, from making evidence-informed decisions about online education, and from coming to our work with the full sense of empathy that our students deserve. Writing in an evocative, accessible, and concise manner, Veletsianos concretely demonstrates why it is so important to pay closer attention to the stories of students—who may have instructive and insightful ideas about the future of education.

At a time when more and more of what people learn both in formal courses and in everyday life is mediated by technology, Learning Online provides a much-needed guide to different forms and applications of online learning. This book describes how online learning is being used in both K-12 and higher education settings as well as in learning outside of school. Particular online learning technologies, such as MOOCs (massive open online courses), multi-player games, learning analytics, and adaptive online practice environments, are described in terms of design principles, implementation, and contexts of use. Learning Online synthesizes research findings on the effectiveness of different types of online learning, but a major message of the book is that student outcomes arise from the joint influence of implementation, context, and learner characteristics interacting with technology--not from technology alone. The book describes available research about how best to implement different forms of online learning for specific kinds of students, subject areas, and contexts. Building on available evidence regarding practices that make online and blended learning more effective in different contexts, Learning Online draws implications for institutional and state policies that would promote judicious uses of online learning and effective implementation models. This in-depth research work concludes with a call for an online learning implementation research agenda, combining education institutions and research partners in a collaborative effort to generate and share evidence on effective practices.

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Learning Theory and Online Technologies offers a powerful overview of the current state of elearning, a foundation of its historical roots and growth, and a framework for distinguishing among the major approaches to elearning. It effectively addresses pedagogy (how to design an effective online environment for learning), evaluation (how to know that students are learning), and history (how past research can guide successful online teaching and learning outcomes). An ideal textbook for undergraduate education and communication programs, and Educational Technology Masters, PhD, and Certificate programs, readers will find Learning Theory and Online Technologies provides a synthesis of the key advances in elearning theory, the key frameworks of research, and clearly links theory and research to successful learning practice.

This book has strategies and tips that every online professor wants students to know before they sign up for an online class. Bowman has provided a reference tool for students to develop self-directed learning skills that will help them become secure and knowledgeable about technology, studying, communicating online, and getting work done on time.

This practical resource draws on the best of neuroscience to inform decision-making about digital learning. We live in unprecedented times that have pushed schools to make many decisions that have been postponed for years. For the first time since the inception of public education, teachers have been invited to redesign the learning landscape by integrating an intelligent selection of digital educational resources and changing pedagogical approaches based on information from the learning sciences. This handbook will help teachers make the most of this opportunity by showing them how to use digital tools to differentiate learning, employ alternative options to standardized testing, personalize learning, prioritize social-emotional skills, and inspire students to think more critically. The author identifies some gems in quality teaching that are amplified in online contexts, including 40 evidence-informed pedagogies from the learning sciences. This book will help all educators move online teaching and learning to new levels of confidence and success. Book Features: Provides quick references to key planning tools like decision-trees, graphics, app recommendations, and step-by-step directions to help teachers create their own online learning courses.Guides teachers through a 12-step model for instructional design that meets both national and international standards.Shows educators how to use an all-new Digital Resource Taxonomy to select resources, and how to research and keep them up to date.Explains why good instructional design and educational technology are complementary with best practices in learning sciences like Mind, Brain, and Education Science.Shares ways teachers can leverage technology to create more time for the personalized aspects of learning. Shows educators how to design online courses with tools that let all students begin at their own starting points and how to differentiate homework.Offers evidence-informed pedagogies to make online intimate and authentic for students.