Intelligent Context Driven Data Mining To Analyse Student Performance in Higher Educational Institutions (HEIs)
Subhashini Sailesh Bhaskaran

Dr. Subhashini Sailesh Bhaskaran, Assistant Professor, Department of Ahlia University, Research Interests are Business Analytics Data Science, Data Mining.
Manuscript received on 13 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript published on 30 July 2019 | PP: 856-861 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1842078219/19©BEIESP | DOI: 10.35940/ijrte.B1842.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Context driven research has been conducted by many. However, very less work has been conducted in constructing a context driven data mining that helps in HEI decision-making. A Student Information System that interacts with Students, Faculties, Student Parents and Management might not have enough information of the background. Context driven data mining is an application intelligent enough to detect and examine the context from different sources and take suitable actions to improve performance and efficiency of decision-making by discovering the hidden factors. This paper recommends a context driven data mining method for understanding student performance from Student Information System in HEIs.
Keywords: HEIs; Context-Awareness; Data Mining; Student Performance;

Scope of the Article: Data Mining