Grouping users' communities in an interactive web-based learning system: A data mining approach

Christine G. Minetou, Sherry Y. Chen, Xiaohui Liu

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

8 Scopus citations

Abstract

Discovery of user communities can help designers to develop learning systems that are more suitable to the needs of different individuals. The study builds user communities based on their common navigation behavior using the K-means algorithm. The results indicated that three user groups could be identified and cognitive style is a potential factor that may influence the patterns of each group.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Pages474-475
Number of pages2
DOIs
StatePublished - 2005
Event5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005 - Kaohsiung, Taiwan
Duration: 5 Jul 20058 Jul 2005

Publication series

NameProceedings - 5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Volume2005

Conference

Conference5th IEEE International Conference on Advanced Learning Technologies, ICALT 2005
Country/TerritoryTaiwan
CityKaohsiung
Period5/07/058/07/05

Fingerprint

Dive into the research topics of 'Grouping users' communities in an interactive web-based learning system: A data mining approach'. Together they form a unique fingerprint.

Cite this