E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Washington, DC, USA ISBN 978-1-880094-54-9 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
This paper reports on an investigation focusing on improving the reliability and efficiency in current database-oriented search-and-retrieval mechanisms in e-learning applications through the use of topic map technology (ISO/IEC 13250). The development of our topic maps is grounded in a theory of cognitive information-processing and information retrieval. We outline the development, implementation and evaluation of a topic map designed to help graduate students search for online resources in preparation for an essay assignment. Sources of data include (a) hard data drawn from observations, tracking of search-related steps, ; and (b) soft data concerning judgments of utility of information and users' understandings of the search process. The results indicate that, in comparison to search engines, topic maps enable students to provide more precise answers and higher recall than the search engine employed in our study.
Shaw, S., Venkatesh, V., Lowerison, G., Dicks, D. & Zhang, D. (2004). Search-and-Retrieval Tools in E-learning Applications: An Empirical Comparison of Search Engines and Topic Maps in an Educational Context. In J. Nall & R. Robson (Eds.), Proceedings of E-Learn 2004--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 435-442). Washington, DC, USA: Association for the Advancement of Computing in Education (AACE). Retrieved March 20, 2019 from https://www.learntechlib.org/primary/p/11358/.
© 2004 Association for the Advancement of Computing in Education (AACE)
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Vivek Venkatesh, Concordia University, Canada
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2007 (Oct 15, 2007) pp. 1311–1319
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