Analysis of Students’ Study Activities in Virtual Learning Environments Using Data Mining Methods Cover Image

Analysis of Students’ Study Activities in Virtual Learning Environments Using Data Mining Methods
Analysis of Students’ Study Activities in Virtual Learning Environments Using Data Mining Methods

Author(s): Leonidas Sakalauskas, Saulius Preidys
Subject(s): Economy
Published by: Vilnius Gediminas Technical University
Keywords: distance education; data mining; e-learning; virtual learning environments; clustering; online learners’ behaviour

Summary/Abstract: This article deals with application of data mining methods’ to analysis of learners’ behaviour using the distance learning platform BlackBoard Vista (BlackBoard 2008). Before planning a distance learning course, instructors have to pay attention to the fact that there exist different study methods: some students start reading learning materials from the very beginning to the end, some students look at unclear topics only, some start with the discussions, etc. Therefore after analyzing the learning factors and identifying learner’s style, it is possible to prepare individualized learning materials and to choose a proper way of course presentation. Such a way of study organization would improve the quality of studies and make it possible to reach better results. The research was performed by observing the behaviour and results achieved by 528 students in 15 distance learning courses and, using the clustering method, 3 learner’s styles using virtual learning environments (VLE) have been identified and work methods proposed for students with regard to those learners’ styles. Besides, the research aims to find out the factors that influence final evaluations of students’.

  • Issue Year: 2010
  • Issue No: 1
  • Page Range: 94-108
  • Page Count: 15
  • Language: English