Application of Clustering for Student Result Analysis
Deepshikha Aggarwal1, Deepti Sharma2
1Deepshikha Aggarwal, Department of Information Technology, Jagan Institute of Management Studies, (Delhi), India.
2Deepti Sharma, Department of Information Technology, Jagan Institute of Management Studies, (Delhi), India.
Manuscript received on 26 March 2019 | Revised Manuscript received on 03 April 2019 | Manuscript Published on 12 April 2019 | PP: 50-53 | Volume-7 Issue-6C April 2019 | Retrieval Number: F90290476C19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The analysis of academic performance of students is an important concern for the universities and colleges of higher learning as it is very important for planning and management of the teaching pedagogy. There is a need for the system to examine and assess the results of students in order to understand how effective the existing education system is. In this study, we have analysed the students’ performance using the clustering and some other statistical tools and methods. This paper studies the actual result of university examination for the students of MCA (Masters in Computer Application), a 3 year post graduate course in information technology. In order to analyse the data k-means clustering algorithm is applied. The elbow method is used to choose appropriate number of clusters. Analysis has also been conducted gender wise to understand whether there is a pattern based on the gender of students. Academic planners can make operational decisions and future planning on the base of results attained in this research.
Keywords: K – Mean Clustering, Elbow Method, Academic Performance, Statistical Algorithm.
Scope of the Article: Software Engineering & Its Applications