文章基本信息

标题：Understanding Teacher Users of a Digital Library Service: A Clustering Approach
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作者：Beijie Xu ; Mimi Recker
期刊名称：Journal of Educational Data Mining
电子版ISSN：2157-2100
出版年度：2011
卷号：3
期号：1
页码：1-28
出版社：International EDM Society
摘要：This article describes the Knowledge Discovery and Data Mining (KDD) process and its application in the field of educational data mining (EDM) in the context of a digital library service called the Instructional Architect (IA.usu.edu). In particular, the study reported in this article investigated a certain type of data mining problem, clustering, and used a statistical model, latent class analysis, to group the IA teacher users according to their diverse online behaviors. The use of LCA successfully helped us identify different types of users, ranging from window shoppers, lukewarm users to the most dedicated users, and distinguish the isolated users from the key brokers of this online community. The article concludes with a discussion of the implications of the discovered usage patterns on system design and on EDM in general.