Mining learners' behavior in accessing web-based interface

Man Wai Lee, Sherry Y. Chen, Xiaohui Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Web-based technology has already been adopted as a tool to support teaching and learning in higher education. One criterion affecting the usability of such a technology is the design of web-based interface (WBI) within web-based learning programs. How different users access the WBIs has been investigated by several studies, which mainly analyze the collected data using statistical methods. In this paper, we propose to analyze users' learning behavior using Data Mining (DM) techniques. Findings in our study show that learners with different cognitive styles seem to have various learning preferences, and DM is an efficient tool to analyze the behavior of different cognitive style groups.

Original languageEnglish
Title of host publicationTechnologies for E-Learning and Digital Entertainment - Second International Conference, Edutainment 2007, Proceedings
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783540730101
StatePublished - 2007
Event2nd International Conference on Edutainment, Edutainment 2007 - Hong Kong, Hong Kong
Duration: 11 Jun 200713 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4469 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Conference on Edutainment, Edutainment 2007
Country/TerritoryHong Kong
CityHong Kong


  • Classification and regression tree
  • Cognitive styles
  • Data mining
  • Web-based interface
  • Web-based learning


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