T. Balasubramanian

Work place: Department of Computer Science, Periyar University, Salem-636011, Tamilnadu, India.


Website: https://scholar.google.com/citations?user=Q5xnuEgAAAAJ&hl=en

Research Interests: Data Mining, Network Security, Information Security, Big data and learning analytics


Dr. T. Balasubramanian received his Master Degree in Computer Science from Bharathidasan University, Trichy in 1996. He has received his Master of Philosophy degree from Periyar University Salem in year 2007. In the specialization of Data Mining, he received his Doctorate from Bharathiar University in 2015. He published more than 32 research papers in various International and National Journals. He also presented 8 research articles in various International Conferences and 12 papers in National and State level conferences & seminars. He has written 5 books under various domains of computer science. Currently he is working as a Associate Professor in the PG and Research Department of of Computer Science in Sri Vidya Mandir Arts and Science College, Uthangarai, Krishnagiri (Dt). He has more than 17 Years of teaching experience. His domain interest is Data mining, Big data, Network Security.

Author Articles
Exploring the High Potential Factors that Affects Students’ Academic Performance

By R. Kaviyarasi T. Balasubramanian

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.

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