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Mining Longitudinal E-Learning Research: Trends and Patterns
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, , Boise State University, United States

Society for Information Technology & Teacher Education International Conference, in Las Vegas, Nevada, USA ISBN 978-1-880094-64-8 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA

Abstract

This study will focus on investigating longitudinal trends of e-learning research. Text mining techniques will be used to extract implicit, hidden knowledge from the open source global e-learning research literature. An extensive e-learning focused query will be applied to the Social Science Citation Index (SSCI) and ED/IT-Lib database. The taxonomies of e-learning articles will be grouped into clusters by analyzing abstract with text mining techniques. The results will provide aggregate e-learning research time trends, aggregate e-learning article bibliometrics, and overall research themes based on total e-learning article retrieved.

Citation

Hung, J.L. & Snelson, C. (2008). Mining Longitudinal E-Learning Research: Trends and Patterns. In K. McFerrin, R. Weber, R. Carlsen & D. Willis (Eds.), Proceedings of SITE 2008--Society for Information Technology & Teacher Education International Conference (pp. 1106-1108). Las Vegas, Nevada, USA: Association for the Advancement of Computing in Education (AACE). Retrieved June 27, 2019 from .

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