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Application of Data mining Techniques In Higher Education System

Albunskuba*, M. Venkatesh Saravanakuma**

* PG Scholar, Department of Computer Science, Sri Vijay Vidyalaya College of Arts and Science, Dharmapuri, India.

** Assistant Professor, Department of Computer Science, Sri Vijay Vidyalaya College of Arts and Science, Dharmapuri, India.

Periodicity:March - May'2016
DOI : https://doi.org/10.26634/jcom.4.1.5987

Abstract

Data mining is used to extract meaningful information and develop significant relationship among variables stored in large data. Data mining techniques can be applied in various fields like microbiology, bio-informatics, medical imaging, finance, healthcare, education, etc. Education is the one of the fields where we can apply data mining algorithms to find unidentified patterns. An educational organization is one of the most important part of a society that plays a vital role in growth and development of any nation. The main objective of higher education institution is to provide quality education to their students. This paper predicts the relationship between post-graduation and research enrollment of students. In this paper, the authors present a model in context of higher education admission. In this paper, student enrollment for post-graduation and research from various higher education providers of UK for 5 consequent academic years (2009-2014) has been taken as the data set. Based on candidate enrollment, association rule mining has been applied and classified to show the variations in admission. Based on findings, decision makers from Higher Education System (HES) can frame norms to improve students enrollment.

Keywords

Data Mining, Higher Education System, Association Rule Mining.

How to Cite this Article?

Albunskuba, J., and Saravanakumar, M.V. (2016). Application of Data mining Techniques In Higher Education System. i-manager’s Journal on Computer Science, 4(1), 8-15. https://doi.org/10.26634/jcom.4.1.5987

References

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