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.
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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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Kong, J., Han, J., Ding, J. et al. Analysis of students’ learning and psychological features by contrast frequent patterns mining on academic performance. Neural Comput & Applic 32, 205–211 (2020) doi:10.1007/s00521-018-3802-9
- Contrast frequent patterns
- Data mining
- Learning feature
- Psychological feature