Usage of Measures of Interestingness in Educational Data


With the growing amount of data a new field called data mining is emerging extremely quickly. Data mining tools which perform data analysis may uncover important data patterns, contributing greatly to business strategies, knowledge bases, and scientific, educational and medical research. Association rules mining is one of the most well studied data mining tasks. It discovers relationships among attributes in databases, producing if-then statements concerning attribute-values. There are increasing research interests in using data mining in education. This new emerging field, called Educational Data Mining, concerns with developing methods that discover knowledge from data come from educational environments. This paper shows how data mining can be used to come up with interesting knowledge from student database. We identify the measure of interestingness and implement them on student database and come up with interesting rules that can help teachers and related people to deal with students and understand their behavior and activities.

Authors and Affiliations

Monika Srivastava| Department of Information Technology Technocrat Institute of Technology Bhopal, India [email protected], Sweta Gupta| Department of Information Technology Technocrat Institute of Technology Bhopal, India [email protected]


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  • EP ID EP8269
  • DOI -
  • Views 347
  • Downloads 28

How To Cite

Monika Srivastava, Sweta Gupta (2011). Usage of Measures of Interestingness in Educational Data. International Journal of Electronics Communication and Computer Technology, 1(2), 30-35.