Mining Association Rules from Empirical Data in the Domain of Education

  • Dragica Radosav University of Novi Sad Technical Faculty "Mihajlo Pupin"
  • Eleonora Brtka University of Novi Sad Technical Faculty "Mihajlo Pupin" Serbia, 23000 Zrenjanin, Djure Djakovica bb
  • Vladimir Brtka University of Novi Sad Technical Faculty "Mihajlo Pupin"


The data mining techniques and their applications are widely recognized as powerful tools in various domains. In the domain of education there is a variety of data of various types that are collected. The important question is: Is it possible to process collected data with the data mining technique and what are main advantages of data mining and e-learning interaction? If an e-learning system accumulates a huge volume of data, then it is possible to deploy techniques and tools from the domain of data mining in order to gain valuable information. The research presented in this paper is conducted on real-life data that originates from the Balkan region. The software system Weka is used to generate association rules. The main result of this research is the assessment of the parameters that are associated with the opinion that computer skills will be helpful in the future, from the students point of view. This result is very important because it gives the exact insight to computer technology usage in the Balkans schools. Furthermore, some advantages of the usage of data mining techniques in the domain of education are determined.

Author Biography

Dragica Radosav, University of Novi Sad Technical Faculty "Mihajlo Pupin"
Department of Mathematics and Computer Science


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How to Cite
RADOSAV, Dragica; BRTKA, Eleonora; BRTKA, Vladimir. Mining Association Rules from Empirical Data in the Domain of Education. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 7, n. 5, p. 933-944, sep. 2014. ISSN 1841-9844. Available at: <>. Date accessed: 10 aug. 2020. doi:


association rules, education, data mining