Data mining techniques for e-learning

Journal Title: Journal of Applied Computer Science & Mathematics - Year 2016, Vol 10, Issue 22

Abstract

Data Mining (DM), sometimes called Knowledge Discovery in Databases (KDD), is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected via transactions. In the education field, the prediction of students learning performance, detection of inappropriate learning behaviours, and development of student profile may be considered e-learning problems where data mining can successfully solve them. In this paper, the authoress analyses the possibilities to apply data mining techniques in e-learning context, to predict the students’ status referring to their activities and the interest in using advanced tutoring tools. The experiments were performed on the basis of data provided by an e-learning platform (Moodle) regarding the logging parameters of students enrolled on Interactive Tutoring Systems discipline during the second semester of current year.

Authors and Affiliations

Irina IONIȚĂ

Keywords

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  • EP ID EP446534
  • DOI 10.4316/JACSM.201602004
  • Views 115
  • Downloads 0

How To Cite

Irina IONIȚĂ (2016). Data mining techniques for e-learning. Journal of Applied Computer Science & Mathematics, 10(22), 26-31. https://europub.co.uk/articles/-A-446534