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Novel Approach to evaluate Student performance using Data Mining

Rahul Raghavan, Sagar Wahal, Manas Saxena, Anil Vasoya Published in Data Mining

IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014
Year of Publication: 2014
© 2014 by IJAIS Journal
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  1. Rahul Raghavan, Sagar Wahal, Manas Saxena and Anil Vasoya. Article: Novel Approach to evaluate Student performance using Data Mining. IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014 ICWAC 2014(2):4-9, June 2014. BibTeX

    @article{key:article,
    	author = "Rahul Raghavan and Sagar Wahal and Manas Saxena and Anil Vasoya",
    	title = "Article: Novel Approach to evaluate Student performance using Data Mining",
    	journal = "IJAIS Proceedings on International Conference and workshop on Advanced Computing 2014",
    	year = 2014,
    	volume = "ICWAC 2014",
    	number = 2,
    	pages = "4-9",
    	month = "June",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Data mining is a process of extracting hidden information from huge volumes of data. The various data mining techniques used are Classification, Clustering and Association mining. All these techniques can be applied to educational data to predict a student's academic performance and also to determine the areas he is currently lacking in. The student can evaluate his performance and find out area to improve. While calculating a student's performance a student's marks in previous semesters and his term test marks, attendance and other factors. This paper proposes the use of One R algorithm and Frequency table to predict the "score" which determines how important a particular area is. The accuracy of this algorithm can be measured by comparing the predicted score with the actual score. Teachers can forward the result of student's report. They can also determine which students are currently lacking based on their marks and other factors. Using this data teacher can motivate a student to improve his performance in a particular area. Also students can view the report themselves and can make improvements based on area which they are lacking in.

Reference

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Keywords

One R Algorithm, Score, Decision Tree, Neural Networks, Knowledge Discovery.