A Data Mining Service to Assist Instructors Involved in Virtual Education

A Data Mining Service to Assist Instructors Involved in Virtual Education

Marta E. Zorrilla (University of Cantabria, Spain) and Diego García (University of Cantabria, Spain)
DOI: 10.4018/978-1-61350-038-5.ch010
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In this chapter we present a BI application delivered as a service on-demand. In particular, it is a data mining service that aims to help instructors involved in distance education to discover their students’ behavior profiles and models about how they navigate and work in their virtual courses offered in Learning Content Management Systems such as Blackboard or Moodle. The main characteristic is that the users do not require data mining knowledge to use the service; they only have to send a data file according to one of the templates provided by the system and request the results. The service carries out the KDD process itself. Furthermore, the service provides an interface based on Web services, which can be called by external software. In short, the chapter talks about the necessity of a service with these characteristics and includes the description of its architecture and its method of operation as well as a discussion about some of the patterns it offers and how these provide instructors valuable knowledge to make decisions.
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The well-established field of study of Computer-Supported Learning has seen, after the advent of Learning Content Management Systems (LCMS) and the Web 2.0, a great impulse; powerful systems supporting virtual learning activities have been very widely deployed and are now used daily in many institutions, and in particular, in universities and other educational centers.

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