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Reseach Article

Prediction of Course Selection by Student using Combination of Data Mining Algorithms in E-Learning

by Sunita B. Aher, LOBO L.M.R.J.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 15
Year of Publication: 2012
Authors: Sunita B. Aher, LOBO L.M.R.J.
10.5120/5053-7085

Sunita B. Aher, LOBO L.M.R.J. . Prediction of Course Selection by Student using Combination of Data Mining Algorithms in E-Learning. International Journal of Computer Applications. 40, 15 ( February 2012), 1-7. DOI=10.5120/5053-7085

@article{ 10.5120/5053-7085,
author = { Sunita B. Aher, LOBO L.M.R.J. },
title = { Prediction of Course Selection by Student using Combination of Data Mining Algorithms in E-Learning },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 40 },
number = { 15 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number15/5053-7085/ },
doi = { 10.5120/5053-7085 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:07.589830+05:30
%A Sunita B. Aher
%A LOBO L.M.R.J.
%T Prediction of Course Selection by Student using Combination of Data Mining Algorithms in E-Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 15
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Course recommender system aims at predicting the best combination of courses selected by students. Here in this paper we present how the combination of clustering algorithm- Simple K-means Algorithm & association rule algorithm- Apriori Association Rule is useful in Course Recommender system. If we use only the Apriori association rule algorithm then we need to preprocess the data obtained from Moodle database. But if we use this combination of clustering & association rule then there is no need to preprocess the data. So we present this new approach & also present the result. To test the result we have used the open source data mining tool Weka.

References
  1. Castro, F., Vellido, A., Nebot, A., & Mugica, F. (in press). Applying data mining techniques to e-learning problems: A survey and state of the art. In L. C. Jain, R. Tedman, & D. Tedman (Eds.), Evolution of Teaching and learning paradigms in intelligent environment. Studies in Computational Intelligence (Vol. 62). Springer-Verlag.
  2. Lili He, Hongtao Bai:”Aspect Mining Using Clustering and Association Rule Method” IJCSNS International Journal of Computer Science and Network Security, VOL.6 No.2A, February 2006
  3. Al¶³pio Jorge:”Hierarchical Clustering for thematic browsing and summarization of large sets of Association Rules” Supported by the POSI/SRI/39630/2001/Class Project
  4. Jiayun Guo, Vlado Ke?selj, and Qigang Gao:”Integrating Web Content Clustering into Web Log Association Rule Mining?” supported by NSERC
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  6. “Data Mining Introductory and Advanced Topics” by Margaret H. Dunham
  7. Sunita B Aher and Lobo L.M.R.J.. Data Mining in Educational System using WEKA. IJCA Proceedings on International Conference on Emerging Technology Trends (ICETT) (3):20-25, 2011. Published by Foundation of Computer Science, New York, USA (ISBN: 978-93-80864-71-13)
  8. Sunita B Aher and Lobo L.M.R.J. Article: A Framework for Recommendation of courses in E-learning System. International Journal of Computer Applications 35(4):21-28, December 2011. Published by Foundation of Computer Science, New York, USA ISSN 0975 – 8887
  9. Sunita B Aher and Lobo L.M.R.J.: “Preprocessing Technique for Association Rule Based Course Recommendation System in E-learning” selected in ICECT-12, proceeding published by IEEE
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Index Terms

Computer Science
Information Sciences

Keywords

Simple K-means Clustering Algorithm Apriori association Rule Weka Moodle