Analysis of students’ learning and psychological features by contrast frequent patterns mining on academic performance
- 13 Downloads
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.
KeywordsContrast 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).
- 2.Avella JT, Kebritchi M, Nunn SG, Kanai T (2016) Learning analytics methods, benefits, and challenges in higher education: a systematic literature review. Online Learn 20(2):13–29Google Scholar
- 6.Tian F, Zheng Q, Zheng D (2010) Mining patterns of e-learner emotion communication in turn level of Chinese interactive texts: experiments and findings. In: 14th international conference on computer supported cooperative work in design, pp 664–670Google Scholar
- 7.Borkar S, Rajeswari K (2014) Attributes selection for predicting students’ academic performance using education data mining and artificial neural network. Int J Comput Appl 86(10):25–29Google Scholar
- 9.Paiva ROA, Bittencourt Santa Pinto II, Da Silva AP, Isotani S, Jaques P (2014) A systematic approach for providing personalized pedagogical recommendations based on educational data mining, vol 8474. Lecture notes in computer science. Springer, Berlin, pp 362–367Google Scholar
- 11.Lee JE, Recker MM, Choi H et al (2015) Applying data mining methods to understand user interactions within learning management systems: approaches and lessons learned. J Educ Technol Dev Exch 8(2):99–116Google Scholar
- 19.Mane RV, Ghorpade VR (2018) Association rule mining for finding admission tendency of engineering student with pattern growth approach. Big data analytics. Springer, Singapore, pp 749–758Google Scholar
- 21.Huang J, Zhu A, Luo Q (2007) Personality mining method in web based education system using data mining. In: IEEE international conference on grey systems and intelligent services. GSIS 2007, pp 155–158Google Scholar
- 22.Gara GPP, Padao FRF (2015) mining association rules on students’ profiles and personality types. Lect Not Eng Comput Sci 2215(1):307–312Google Scholar