Work place: Department of Computer Science, Periyar University, Salem-636011, Tamilnadu, India
Research Interests: Computational Learning Theory
R.Kaviyarasi (Corresponding author) received her MCA Degree from Karpagam College of Engineering, Coimbatore affiliated with Anna University, Chennai and M. Phil Degree with university rank from Periyar University, Salem. She has qualified in NET & SET eligibility examinations. Now, she is pursuing her Ph. D (Part time) in Periyar University, Salem. Currently she is working as a Assistant Professor in Department of Computer Science & Applications at Sri Vidya Mandir Arts and Science College, Uthangarai, Krishnagiri(Dt), Tamilnadu. Her research area is Machine Learning Techniques.
DOI: https://doi.org/10.5815/ijeme.2018.06.02, Pub. Date: 8 Nov. 2018
The rapid increase in student population has resulted in expansion of educational facilities at all level. Nowadays, responsibilities of teachers are many. It is the responsibilities of teachers to guide the students to choose their carrier field according to their abilities and aptitudes. The Data Mining field mines the educational data from large volumes of data to improve the quality of educational processes. Today’s need of educational system is to develop the individual to enhance problem solving and decision making skills in addition to build their social skills. Educational Data Mining is one of the applications of Data Mining to find out the hidden patterns and knowledge in Educational Institutions. There are three important groups of students have been identified: Fast Learners, Average Learners, and Slow Learners. In fact, students are probably struggles in many factors. This work focuses on finding the high potential factors that affects the performance of college students. This finding will improve the students’ academic performance positively.
[...] Read more.Subscribe to receive issue release notifications and newsletters from MECS Press journals