Improving university e-Learning with exploratory data analysis and web log mining

Conference proceedings article

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Publication Details

Author list: Nukoolkit C., Chansripiboon P., Sopitsirikul S.

Publisher: Hindawi

Publication year: 2011

Start page: 176

End page: 179

Number of pages: 4

ISBN: 9781424497188

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-80054017845&doi=10.1109%2fICCSE.2011.6028611&partnerID=40&md5=272fcadf9ece34a3cccbb5d704c9a167

Languages: English-Great Britain (EN-GB)

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Abstract

The success of an e-Learning system depends on several factors: a supportive infrastructure, high-quality content, effective format, and high availability to satisfy ongoing user needs. In this paper, we perform exploratory data analysis and data mining on an e-Learning web log, which spans one academic year. The study uncovers the e-Learning users' usage behavior in accessing the content. The study discovers e-Learning media popularity and usage patterns, and helps the institution fine tune future courseware, from strategic changes to the fine-grain of lesson content improvement. ฉ 2011 IEEE.

Keywords

curriculum design, exploratory data analysis, web log mining