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Distributed Learning by Mary R. Lea,Kathy Nicoll Pdf
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.
Distributed Learning by Tasha Maddison,Maha Kumaran Pdf
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
Designing Distributed Learning Environments with Intelligent Software Agents by Fuhua Oscar Lin Pdf
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.
Encyclopedia of Distributed Learning by Anna DiStefano,Kjell Erik Rudestam,Robert Silverman Pdf
"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
Distributed Machine Learning Patterns by Yuan Tang Pdf
Practical patterns for scaling machine learning from your laptop to a distributed cluster. Distributing machine learning systems allow developers to handle extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. This book reveals best practice techniques and insider tips for tackling the challenges of scaling machine learning systems. In Distributed Machine Learning Patterns you will learn how to: Apply distributed systems patterns to build scalable and reliable machine learning projects Build ML pipelines with data ingestion, distributed training, model serving, and more Automate ML tasks with Kubernetes, TensorFlow, Kubeflow, and Argo Workflows Make trade-offs between different patterns and approaches Manage and monitor machine learning workloads at scale Inside Distributed Machine Learning Patterns you’ll learn to apply established distributed systems patterns to machine learning projects—plus explore cutting-edge new patterns created specifically for machine learning. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Hands-on projects and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. About the technology Deploying a machine learning application on a modern distributed system puts the spotlight on reliability, performance, security, and other operational concerns. In this in-depth guide, Yuan Tang, project lead of Argo and Kubeflow, shares patterns, examples, and hard-won insights on taking an ML model from a single device to a distributed cluster. About the book Distributed Machine Learning Patterns provides dozens of techniques for designing and deploying distributed machine learning systems. In it, you’ll learn patterns for distributed model training, managing unexpected failures, and dynamic model serving. You’ll appreciate the practical examples that accompany each pattern along with a full-scale project that implements distributed model training and inference with autoscaling on Kubernetes. What's inside Data ingestion, distributed training, model serving, and more Automating Kubernetes and TensorFlow with Kubeflow and Argo Workflows Manage and monitor workloads at scale About the reader For data analysts and engineers familiar with the basics of machine learning, Bash, Python, and Docker. About the author Yuan Tang is a project lead of Argo and Kubeflow, maintainer of TensorFlow and XGBoost, and author of numerous open source projects. Table of Contents PART 1 BASIC CONCEPTS AND BACKGROUND 1 Introduction to distributed machine learning systems PART 2 PATTERNS OF DISTRIBUTED MACHINE LEARNING SYSTEMS 2 Data ingestion patterns 3 Distributed training patterns 4 Model serving patterns 5 Workflow patterns 6 Operation patterns PART 3 BUILDING A DISTRIBUTED MACHINE LEARNING WORKFLOW 7 Project overview and system architecture 8 Overview of relevant technologies 9 A complete implementation
Learning Analytics in Open and Distributed Learning by Paul Prinsloo,Sharon Slade,Mohammad Khalil Pdf
This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the “data revolution” and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book’s conceptual rationale, the book discusses the potential, challenges and practices of learning analytics in various open and distributed contexts. A concluding chapter briefly summarises the chapters before providing a tentative future research agenda for learning analytics in open and distributed environments.
The Distributed Classroom by David A. Joyner,Charles Isbell Pdf
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.
Distance Learning and University Effectiveness by Caroline Howard,Karen Schenk,Richard Discenza Pdf
Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning addresses the challenges and opportunities associated with information and communication technologies (ICTs) as related to education. From discussing new and innovative educational paradigms and learning models resulting from ICTs to addressing future student needs and international issues, this book provides comprehensive coverage of the paradigm, teaching, technology and other changes that may be required of universities to remain in the new competitive marketplace of online learning.
Encyclopedia of Distance Learning by Howard, Caroline,Boettcher, Judith V.,Justice, Lorraine,Schenk, Karen D.,Rogers, Patricia L.,Berg, Gary A. Pdf
"This encyclopedia offers the most comprehensive coverage of the issues, concepts, trends, and technologies of distance learning. More than 450 international contributors from over 50 countries"--Provided by publisher.
Edge Learning for Distributed Big Data Analytics by Song Guo,Zhihao Qu Pdf
Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.
Scaling Up Machine Learning by Ron Bekkerman,Mikhail Bilenko,John Langford Pdf
This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
Transactional Distance and Adaptive Learning by Farhad Saba,Rick L. Shearer Pdf
Transactional Distance and Adaptive Learning takes a fresh look at one of the pioneering educational theories that accommodates the impact of information and communications technologies in learning. The theory of transactional distance (TTD) provides a distinct analytical and planning foundation for educators to conduct an overarching inquiry into transitioning from mass instructional and management systems in higher education to dynamic and transformational futures that focus on each individual learner. Based on the TTD, this pragmatic approach offers instructors, administrators, students, and other stakeholders a comprehensive planning method to assess the current state of their instructional, learning, and management practices and to develop alternative models to prescribe future improvements in their institution. This complex, self-organized, and adaptive method includes current and emergent properties of: hardware, software, and telecommunications systems that allow faculty, students, and administrators to communicate; instructional and curriculum systems that provide teaching and learning environments for faculty and students; and management, societal, and global systems that influence how institutions are supported, funded, and managed.
Open and Distance Learning Today by Fred Lockwood Pdf
The book presents a comprehensive account of research and development activities in open, ditance and flexible learning from acknowledged experts from around the world. The use of open, distance and flexible learning materials is expanding dramatically, not just in schools, further and higher education but also in industry, commerce and the social services. Most higher education institutions now have an open learning unit or educational development centre, and major organisations such as british Steel, National Westminster Bank, Leeds Building Society, Rover Cars and the Inland Revenue have formed units to develop teaching and training materials. Internationally, growth is even more impressive, with new open universities planned for Singapore, Bangladesh, South Africa and india, whist those in Malaysia, Thailand and Australia continue to expand. But current and future practice must be based on research evidence rather than intuition. With contributions from all the leading names in this field, this book will be a key sourcbook for teachers, trainers and students.
Assessment Strategies for Online Learning by Dianne Conrad,Jason Openo Pdf
Assessment has provided educational institutions with information about student learning outcomes and the quality of education for many decades. But has it informed practice and been fully incorporated into the learning cycle? Conrad and Openo argue that the potential inherent in many of the new learning environments being explored by educators and students has not been fully realized. In this investigation of a variety of assessment methods and learning approaches, the authors aim to discover the tools that engage learners and authentically evaluate education. They insist that moving to new learning environments, specifically those online and at a distance, afford opportunities for educators to adopt only the best practices of traditional face-to-face assessment while exploring evaluation tools made available by a digital learning environment in the hopes of arriving at methods that capture the widest set of learner skills and attributes.
