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A Discussion List Analyzer: Using an Artificial Neural Network to Reveal Cognitive Effort Expressed in Online Discussion List Messages
PROCEEDINGS

, , Georgia Tech, United States ; , University of Georgia, United States ; , University System of Georgia, United States

EdMedia + Innovate Learning, in Honolulu, Hawaii, USA ISBN 978-1-880094-48-8 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC

Abstract

This paper details the work performed toward building a reliable, automatic, content analysis suite of tools that analyzes online educational discussion list messages. This project is conducted under contract by Georgia Tech's Center for Education Integrating Science, Mathematics, and Computing (CEISMC) with the Institute of Higher Education at the University of Georgia under a service agreement with the University System of Georgia Board of Regents' Advanced Learning Technologies Unit. This study is based on the cognitive presence element of Garrison, Anderson, and Archer's (2000, 2001) community of inquiry model and seeks to answer two broad questions: Can an artificial neural network (ANN) be used to reliably create an automatic discussion list analysis tool, and can such a tool reveal the cognitive effort behind a body of discussion list messages?

Citation

McKlin, T., Oliver, P., Morris, L. & Finnegan, C. (2003). A Discussion List Analyzer: Using an Artificial Neural Network to Reveal Cognitive Effort Expressed in Online Discussion List Messages. In D. Lassner & C. McNaught (Eds.), Proceedings of ED-MEDIA 2003--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 876-879). Honolulu, Hawaii, USA: Association for the Advancement of Computing in Education (AACE). Retrieved August 22, 2019 from .

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