IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Self-Normalizing Distance Learning Tools

Self-Normalizing Distance Learning Tools
View Sample PDF
Author(s): Eduardo Costa (Utah State University, USA), Reny Cury (UFU/CNPq, Brazil) and Junia Magellan (Utah State University, USA)
Copyright: 2009
Pages: 5
Source title: Encyclopedia of Distance Learning, Second Edition
Source Author(s)/Editor(s): Patricia L. Rogers (Bemidji State University, USA), Gary A. Berg (California State University Channel Islands (Retired), USA), Judith V. Boettcher (Designing for Learning, USA), Caroline Howard (HC Consulting, USA), Lorraine Justice (Hong Kong Polytechnic University, Hong Kong) and Karen D. Schenk (K. D. Schenk and Associates Consulting, USA)
DOI: 10.4018/978-1-60566-198-8.ch274

Purchase

View Self-Normalizing Distance Learning Tools on the publisher's website for pricing and purchasing information.

Abstract

Communication system designers minimize noise with self-correcting codes that add redundant information to the signal, increasing the probability of error detection, and recovery of the uncorrupted data. Evolutionary biologists claim that knowledge transmitted between generations of biological organisms have mechanisms that create probability traps for errors. Designers of online systems are starting to mimic these systems.

Related Content

Fernando Bandeira, João Casqueira Cardoso. © 2021. 23 pages.
Gulgun Afacan Adanır. © 2021. 19 pages.
Ingrid N. Pinto-López, Cynthia M. Montaudon-Tomas. © 2021. 35 pages.
Teresa Oliveira Ramos, Carla Morais, Cristina Ribeiro. © 2021. 39 pages.
Ashleigh J. Fletcher, Mark Haw, Miguel Jorge, Kenneth Moffat. © 2021. 31 pages.
Maria Minerva P. Calimag. © 2021. 22 pages.
Tiago da Silva Carvalho, Pedro Almeida, Ana Balula. © 2021. 23 pages.
Body Bottom