Title: Critical success factor for implementing data mining in higher education: Indian perspective

Authors: Raju Ranjan; Jayanthi Ranjan; Vishal Bhatnagar

Addresses: Uttarakhand Technical University, Dehradun-248007, India ' Institute of Management Technology, Raj Nagar, Ghaziabad – 201001, India ' Ambedkar Institute of Advanced Communication Technologies and Research, Geeta Colony, Delhi – 110031, India

Abstract: Higher educational institutions (HEI) in India aims at providing education in some specialised field and was controlled by state universities and institutes/institutions that were highly subsidised. In recent years, efforts were made to make it self-financing and private participation was brought in. As a result, there is mushrooming growth of higher education centres in India now. Data mining (DM) is applied in various perspectives in education, for example, to spot weaknesses and strengths of not just schools, but groups of kids and even individual students. In this paper, the authors explore the purpose of applying DM in higher educational institutions in light of the growing globalisation of the Indian higher educational institutions. This paper presents the critical success factor for the same, for any higher educational institutions to adopt DM. This paper finds the factors or parameters which can be taken into consideration when applying DM in higher educational institutions to improve the academic performance and overall quality of the institute.

Keywords: data mining; higher education institutions; HEIs; data mart; Training and Placement Office; TPO; critical success factors; CSFs; Vice Chancellors; VCs; India.

DOI: 10.1504/IJCSYSE.2013.052585

International Journal of Computational Systems Engineering, 2013 Vol.1 No.3, pp.151 - 161

Published online: 26 Jul 2014 *

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