Analysis of students’ learning and psychological features by contrast frequent patterns mining on academic performance

  • Jie KongEmail author
  • Jiaxin Han
  • Junping Ding
  • Haiyang Xia
  • Xin Han
Brain- Inspired computing and Machine learning for Brain Health


In recent years, data mining techniques have been widely applied in education. However, studies on analyzing the similarity or difference of the same learning pattern in different student groups are still rare. In this study, a data mining method which combines the concepts of contrast sets mining and association rules mining is introduced. It could provide quantitative analysis for the similarity and difference of association rules obtained from the academic records datasets of multiple grades. On this basis, student psychological features are deduced without being sensitive to privacy. The work in this study can help educators understand the learning and psychological states of students in different grades, so as to formulate teaching plans that are more targeted to improve their academic performance.


Contrast frequent patterns Data mining Learning feature Psychological feature 



This work is supported by the Science Research Project of Shaanxi Provincial Department of Education (CN) (Grant No: 17JK0614) and the Youth Science and Technology Innovation Fund of X’ian Shiyou University (CN) (Grant No: 2013BS025).


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  • Jie Kong
    • 1
    Email author
  • Jiaxin Han
    • 1
  • Junping Ding
    • 2
  • Haiyang Xia
    • 1
  • Xin Han
    • 1
  1. 1.School of Computer ScienceXi’an Shiyou UniversityXi’anChina
  2. 2.Newegg Inc.City of IndustryUSA

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