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Data Mining Techniques for the performance Analysis of a Learning Model – A Case Study

by P. K. Srimani, Annapurna S. Kamath
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 5
Year of Publication: 2012
Authors: P. K. Srimani, Annapurna S. Kamath
10.5120/8421-1896

P. K. Srimani, Annapurna S. Kamath . Data Mining Techniques for the performance Analysis of a Learning Model – A Case Study. International Journal of Computer Applications. 53, 5 ( September 2012), 36-42. DOI=10.5120/8421-1896

@article{ 10.5120/8421-1896,
author = { P. K. Srimani, Annapurna S. Kamath },
title = { Data Mining Techniques for the performance Analysis of a Learning Model – A Case Study },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 5 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number5/8421-1896/ },
doi = { 10.5120/8421-1896 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:53:23.354668+05:30
%A P. K. Srimani
%A Annapurna S. Kamath
%T Data Mining Techniques for the performance Analysis of a Learning Model – A Case Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 5
%P 36-42
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with a comparative study of the application of various data mining algorithms for the performance analysis of the learning model. The learning model for Mathematics is an integration of the various components used for effective learning of mathematics and assessment at the elementary level of education. Performance analysis is the analysis of the data stored by the learning model in the mathematical pathway database which is used to track the progress of each child. The analysis classifies the performance of a child into average, below average and above average categories. This aids in timely intervention. The performance analysis using Data Mining (DM) approach validates the accuracy and efficiency of the learning model leading to reliable and authentic predictions. Further any algorithm can be used for predictions of the mathematics learning trends as the performance of all techniques is comparable. This generic novel approach can be extended to other disciplines as well.

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Index Terms

Computer Science
Information Sciences

Keywords

Mathematical Pathway Learning Model Performance Analysis Confusion Matrix Accuracy

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