Preliminary communication
Cluster analysis of student activity in a web-based intelligent tutoring system
Igor Jugo
; University of Rijeka, Department of Informatics, Rijeka, Croatia
Božidar Kovačić
; University of Rijeka, Department of Informatics, Rijeka, Croatia
Edvard Tijan
orcid.org/0000-0002-7642-0496
; University of Rijeka, Faculty of Maritime Studies Rijeka
Abstract
In this paper we present a model of a system for integration of an intelligent tutoring system with data mining tools. The purpose of the integration is twofold; a) to power the system adaptability based on clustering and sequential pattern mining, and b) to enable teachers (non-experts in data mining) to use data mining techniques in their web browser on a daily basis, and get useful visualizations that provide insights into the learning progress of their students. We also present an approach to clustering results evaluation developed so that the system can independently deduce the best number of clusters for the k-means algorithm as well as order the clusters in terms of learning efficiency of cluster members (students).
Keywords
Intelligent tutoring systems; Educational data mining; Clustering students; Maritime e-learning
Hrčak ID:
140275
URI
Publication date:
30.6.2015.
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