A Data Mining Based Approach to Evaluate Assessment Performances of Graduating Students of Schools

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Rituraj Jain, Yohannes Bekuma, Bipin Pandey, Jaishri Gothania


In the current trends of advance computing methodologies, data of students’ performances in different grades can be used to improve the quality of managerial decisions. Student’s academic performance is based upon various factors like personal characteristics and psychological factors. Educational database contains useful information for predicting a students’ performance, rank factor and details. By applying different data mining techniques to educational data to analyse them as well as to develop good methods to knowledge gain and management. Finding better correlation between different data variables can allow us to make better and beneficial decision which can facilitate better resource utilization in terms of educational service delivery. 

This paper aims to analyses and predict the correlation between English, Mathematics and science subjects in terms of student academic result in 10th and 12th grade by using Aprior data mining techniques which mines required information. National level examination results of 10th and 12th grade students’ have been used for this research. The results show strong relationships between subjects as well as subject relationships with gender of the student in a specific grade. The results of this research help educationist to develop proper education model to improve results and to get better achievements in the areas where lacking

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