Educational Data Mining for Problem Identification

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

Students face a number of difficulties studying mathematics on all educational levels. Data mining techniques applied on educational data can allow better understanding of the large amount of challenges students meet taking mathematical courses. Many researches focus on investigating various factors causing exam failure or even drop out. They often refer to study anxiety as being one of the serious reasons for students failure in mathematics. We believe that application of methods from market basket analysis can assist for identifying students, experiencing significant difficulties in their studies.

Keywords

Data mining Problem identification Learning 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Stord/Haugesund University CollegeHaugesundNorway

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