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Mining Topic Taxonomies of the Distance Education Literature with Text-Mining Techniques
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, Boise State University, United States ; , Wayne State University, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, Nevada, USA ISBN 978-1-880094-66-2 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

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Abstract

This study will focus on investigating longitudinal trends of distance education research. Text mining techniques will be used to extract implicit, hidden knowledge from the open source global distance education research literature. An extensive distance education focused query will be applied to the Web of Knowledge database. The taxonomies of distance education articles will be grouped into clusters by analyzing abstract with text mining techniques. The results will provide aggregate research time trends, aggregate article bibliometrics, and overall research themes based on total distance education article retrieved.

Citation

Hung, J.L. & Zhang, K. (2008). Mining Topic Taxonomies of the Distance Education Literature with Text-Mining Techniques. In C. Bonk, M. Lee & T. Reynolds (Eds.), Proceedings of E-Learn 2008--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 2764-2766). Las Vegas, Nevada, USA: Association for the Advancement of Computing in Education (AACE). Retrieved August 11, 2024 from .

© 2008 Association for the Advancement of Computing in Education (AACE)

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