The field of distributed learning is constantly evolving. Online technology provides instructors with the flexibility to offer meaningful instruction to students who are at a distance or in some cases right on campus, but still unable to be physically present in the classroom. This dynamic environment challenges librarians to monitor, learn, adapt, collaborate, and use new technological advances in order to make the best use of techniques to engage students and improve learning outcomes and success rates. Distributed Learning provides evidence based information on a variety of issues, surrounding online teaching and learning from the perspective of librarians. - Includes extensive literature search on distributed learning - Provides pedagogy, developing content, and technology by librarians - Shows the importance of collaboration and buy-in from all parties involved

At a time of increasing globalisation, the concept of open and distance learning is being constantly redefined. New technologies have opened up new ways of understanding and participating in Learning. Distributed Learning offers a collection of perspectives from a social and cultural practice-based viewpoint, with contributions from leading international authors in the field. Key issues in this comprehensive text are: *the challenges of ICT to traditional teaching and learning practices *the value and relevance of 'activity theory' and 'communities of practice' in educational institutions and the workplace *perspectives on the relationship between globalisation and distributed learning, and the breakdown of distinctions between global and local contexts *issues of identity and community in designing courses for the virtual student *language and literacies in distributed learning contexts This book provides useful introductory reading, building a sound theoretical framework for practitioners interested in how distributed learning is shaping post-compulsory education.

"This volume will appeal to a wide array of readers, from novices to those already working in the field. Recommended for all collections." --CHOICE "Reference literature has been hard put to keep pace with its (distance learning) changes so the appearance of an Encyclopedia is most welcome. Recommended for academic and public libraries." --LIBRARY JOURNAL In today′s fast-paced world, with multiple demands on time and resources as well as pressures for career advancement and productivity, self-directed learning is an increasingly popular and practical alternative in continuing education. The Encyclopedia of Distributed Learning defines and applies the best practices of contemporary continuing education designed for adults in corporate settings, Open University settings, graduate coursework, and in similar learning environments. Written for a wide audience in the distance and continuing education field, the Encyclopedia is a valuable resource for deans and administrators at universities and colleges, reference librarians in academic and public institutions, HR officials involved with continuing education/training programs in corporate settings, and those involved in the academic disciplines of Education, Psychology, Information Technology, and Library Science. Sponsored by The Fielding Graduate Institute, this extensive reference work is edited by long-time institute members, bringing with them the philosophy and authoritative background of this premier institution. The Fielding Graduate Institute is well known for offering mid-career professionals opportunities for self-directed, mentored study with the flexibility of time and location that enables students to maintain commitments to family, work, and community. The Encyclopedia of Distributed Learning includes over 275 entries, each written by a specialist in that area, giving the reader comprehensive coverage of all aspects of distributed learning, including use of group processes, self-assessment, the life line experience, and developing a learning contract. Topics Covered Administrative Processes Policy, Finance and Governance Social and Cultural Perspectives Student and Faculty Issues Teaching and Learning Processes and Technologies Technical Tools and Supports Key Features * A-to-Z organization plus Reader′s Guide groups entries by broad topic areas * Over 275 entries, each written by a specialist in that area * Comprehensive index and cross-references between entries add to the encyclopedia′s ease of use * Annotated listings for additional resources, including distance learning programs, print and non-print resources, and conferences Advisory Board Tony Bates University of British Columbia Gregory S. Blimling Appalachian State University Ellie Chambers The Open University, U.K. Paul Duguid University of California, Berkeley Kenneth C. Green The Campus Computing Project Linda Harasim Simon Fraser University Sally Johnstone WCET Sara Kiesler Carnegie Mellon University William Maehl Fielding Graduate Institute Michael G. Moore Pennsylvania State University Jeremy Shapiro Fielding Graduate Institute Ralph A. Wolff Executive Director, Western Association of Schools and Colleges

A vision of the future of education in which the classroom experience is distributed across space and time without compromising learning. What if there were a model for learning in which the classroom experience was distributed across space and time--and students could still have the benefits of the traditional classroom, even if they can't be present physically or learn synchronously? In this book, two experts in online learning envision a future in which education from kindergarten through graduate school need not be tethered to a single physical classroom. The distributed classroom would neither sacrifice students' social learning experience nor require massive development resources. It goes beyond hybrid learning, so ubiquitous during the COVID-19 pandemic, and MOOCs, so trendy a few years ago, to reimagine the classroom itself. David Joyner and Charles Isbell, both of Georgia Tech, explain how recent developments, including distance learning and learning management systems, have paved the way for the distributed classroom. They propose that we dispense with the dichotomy between online and traditional education, and the assumption that online learning is necessarily inferior. They describe the distributed classroom's various delivery modes for in-person students, remote synchronous students, and remote asynchronous students; the goal would be a symmetry of experiences, with both students and teachers able to move from one mode to another. With The Distributed Classroom, Joyner and Isbell offer an optimistic, learner-centric view of the future of education, in which every person on earth is turned into a potential learner as barriers of cost, geography, and synchronicity disappear.

Designing Distributed Learning Environments with Intelligent Software Agents reports on the most recent advances in agent technologies for distributed learning. Chapters are devoted to the various aspects of intelligent software agents in distributed learning, including the methodological and technical issues on where and how intelligent agents can contribute to meeting distributed learning needs today and tomorrow. This book benefits the AI (artificial intelligence) and educational communities in their research and development, offering new and interesting research issues surrounding the development of distributed learning environments in the Semantic Web age. In addition, the ideas presented in the book are applicable to other domains such as Agent-Supported Web Services, distributed business process and resource integration, computer-supported collaborative work (CSCW) and e-Commerce.

Practical patterns for scaling machine learning from your laptop to a distributed cluster. Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters. In Distributed Machine Learning Patterns, you’ll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.