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Friday, October 9, 2020 | History

3 edition of Distance-based and distributed learning found in the catalog.

Distance-based and distributed learning

Distance-based and distributed learning

a decision tool for education leaders

  • 173 Want to read
  • 39 Currently reading

Published by AEL, U.S. Dept. of Education, Office of Educational Research and Improvement, Educational Resources Information Center in [Charleston, WV], [Washington, DC] .
Written in English

    Subjects:
  • Distance education.,
  • Instructional systems -- Design -- Planning.,
  • Curriculum planning.

  • Edition Notes

    Other titlesDistance based and distributed learning, Decision tool for education leaders
    StatementTammy M. McGraw, John D. Ross.
    ContributionsRoss, John D., Educational Resources Information Center (U.S.)
    The Physical Object
    FormatMicroform
    Pagination1 v.
    ID Numbers
    Open LibraryOL18346982M

    This series, Distributed Education: Challenges, Choices, and a New Environment, has been sustained with generous support from the AT&T Foundation, Accenture, and the Compaq Corporation. “Distance” or “distributed” learning raises a strategic and financial challenge for every type of . Distance-based algorithms are machine learning algorithms that classify queries by computing distances between these queries and a number of internally stored exemplars. Exemplars that are closest to the query have the largest influence on the classification assigned to the query.

    Usually distributed learning or spaced learning is defined as opposed to massed learning. Distributed learning means that the material to be learned is distributed over a long period of time so that the learner must integrate the various separated parts of material into a unique entity. Browse Education > Distance Education & Learning eBooks to read online or download in EPUB or PDF format on your mobile device and PC.

    Distributed learning is an instructional model that allows instructor, students, and content to be located in different, noncentralized locations so that instruction and learning can occur independent of time and place. The distributed learning model can be used in combination with traditional classroom-based courses and traditional distance education courses (in which it is also deferred to. Let's explore the distributed deep learning concept next. Model versus data parallelization When are training large amounts of data, or when the network structure is huge, we usually need to distribute the training across different machines/threads so that learning can be performed in parallel.


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Distance-based and distributed learning Download PDF EPUB FB2

Books Advanced Search New Releases Best Sellers & More Children's Books Textbooks Textbook Rentals Best Books of the Month of over 8, results for Books: Education & Teaching: Schools & Teaching: Distance & Online Learning. *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.

Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Format: Paperback. The field of distributed learning is constantly Distance-based and distributed learning book.

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 : Paperback. Distance Education and Distributed Learning addresses the latest thinking on the integration of older and new teaching and learning technologies.

Comprised of ten chapters written by renowned scholars, this book examines issues pertaining to the use of interactive media in distance education contexts. This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms.

Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by /5(2).

*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 by: This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction.

A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs assessment, including learner profile and technology Author: Tammy M. McGraw, John D. Ross. This comprehensive, six-volume collection addresses all prominent aspects of online and distance learning, including information communication technologies applied to education, virtual classrooms, pedagogical systems, Web-based learning communities and library information systems, virtual universities, and numerous other topics.

Distance education is a term that refers to learning undertaken by students who are physically distant from the instructor. Today, the term has come to connote long-distance instruction carried out with the help of technology. Parallel versus distributed computing While both distributed computing and parallel systems are widely available these days, the main difference between these two is that a parallel computing system consists of multiple processors that communicate with each other using a shared memory, whereas a distributed computing system contains multiple.

Designing Data-Intensive Applications ( book) by Martin Kleppmann is so good. Not only the technical content, but also the writing style. Even if “Distributed” is not in the title, “data-intensive” (or “streaming data”, or the now archaic “big. Get this from a library.

Distance-based and distributed learning: a decision tool for education leaders. [Tammy M McGraw; John D Ross; Educational Resources Information Center (U.S.)]. Chapter 1 Introduction Libraries must meet the information and scholarship needs of their users.

The norm now seems to be that many users are away from the physical library or - Selection from Distributed Learning [Book]. Online learning refers to instruction that is delivered electronically through various multimedia and Internet platforms and applications.

It is used interchangeably with other terms such as web-based learning, e-learning, computer-assisted instruction, and Internet-based learning. This chapter includes a review of the literature published between and on online learning in information literacy instruction (ILI) in academic libraries.

Writing Across Distances and Disciplines: Research and Pedagogy in Distributed Learning - Kindle edition by Neff, Joyce Magnotto, Whithaus, Carl. Download it once and read it on your Kindle device, PC, phones or tablets.

Use features like bookmarks, note taking and highlighting while reading Writing Across Distances and Disciplines: Research and Pedagogy in Distributed by: 3. Purchase Distributed Learning - 1st Edition.

Print Book & E-Book. ISBN SAGE Video Bringing teaching, learning and research to life. SAGE Books The ultimate social sciences digital library. SAGE Reference The complete guide for your research journey. SAGE Navigator The essential social sciences literature review tool.

SAGE Business Cases Real world cases at your fingertips. CQ Press Your definitive resource for politics, policy and people. This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms.

Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by.

books. Educators now have more options than ever when it comes to methods of delivering a distance course. The majority are already blending various technologies to encourage student learning, engagement, and retention. As noted, the research on models has not kept pace with continual developments; however, a thorough review.

putation effort distributed for several of the most popular machine learning algorithms, e.g., support vector machine (SVM) [Burges, ], and logistic regression [Lee et al., ]. After applying our proposed approach to these ma-chine learning algorithms, they can be readily used to solve problems involving big data.

To be more specific. In distributed learning and training, which are now prevalent in industry, academia, and the government, students can be separated by both time and space. The increased use of such technology raises the question of how best to implement it for optimal : This work discusses issues relating to distance education and distributed learning.

There are essays covering: rethinking assessment for the online environment; the role of collaborative learning in social and intellectual development; and the embodiment of knowledge in virtual environments.Description. 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.