2017 |
Volume 5 |
Issue 2
Predicting Student Performance Using Data Mining
1.
R. Lakshmi
– Student, Department Of Computer Science And Engineering, Kerala, India.
2.
K. S. Narayanan
– Student, Department Of Computer Science And Engineering, Kerala, India.
3.
R. Swathikrishna
– Student, Department Of Computer Science And Engineering, Kerala, India.
4.
K. M. Sameera
– Student, Department Of Computer Science And Engineering, Kerala, India.
Received
19-Feb-2018
|
Accepted
-
|
Published
19-Feb-2018
|
Abstract
The objective of the paper is to analyze the performance of a student by evaluating EQ and IQ level and also to check the correlation between EQ IQ and performance. Present system predicts the performance of student by comparing their EQ and IQ with some tests referred by the psychology department. Our study aims to establish and monitor the performance using EQ and IQ achievement among the undergraduate students by data mining procedures. Initially prepared the questionnaire of EQ and IQ. The data were collected from 150 students. Using WEKA tool, the data given as input. Using different classification algorithms predicted the individual performance of student by data mining concepts. And also compare the efficiency of classification algorithms and find the efficient one among them. EQ IQ is found to have a significant relation with the performance of students. Logistics function and random tree were used to explore the performance of student semester by semester. By means of applying these methods, the performance by graduation is predicted and accuracy is evaluated.
Keywords Data mining, Emotional quotient, Intelligent quotient, Logistic function, WEKA tool
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