International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 181 - Number 30 |
Year of Publication: 2018 |
Authors: Sharad Gangele, Kirti Soni, Sunil Patil |
10.5120/ijca2018918099 |
Sharad Gangele, Kirti Soni, Sunil Patil . Data Mining Approach towards Students Behavior Assessment Methods for Higher Studies. International Journal of Computer Applications. 181, 30 ( Nov 2018), 11-14. DOI=10.5120/ijca2018918099
The quality education to the students is primary point of higher educational institutions. One of the method to achieve high quality education in higher education system is analysis of students behavior with reference to examination performance, mark sheets, abnormal values and other students activities. Data mining methods discovers knowledge from these records for analysis and prediction about students behavior. In this paper, data mining techniques such as association rules and classification are applied to analyze and present a behavior model of students. The students behavior assessment framework is proposed as model for analysis using data mining technique, the model presents the indication to the critical quantities that regulate the students behavior on learning method. The proposed framework can be applied to extract valuable data that shows all characteristic of student behavior by clustering and subdivision of the student behavior large data set.