Research 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.
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Issue 15
Published: February 2012
Authors: Sunita B. Aher, Lobo L.M.R.J.
10.5120/5053-7085
PDF

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 },
                        year    = { 2012 },
                        volume  = { 40 },
                        number  = { 15 },
                        pages   = { 1-7 },
                        doi     = { 10.5120/5053-7085 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2012
                        %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%T 
                        %J International Journal of Computer Applications
                        %V 40
                        %N 15
                        %P 1-7
                        %R 10.5120/5053-7085
                        %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
  • 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.
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  • Jiayun Guo, Vlado Ke?selj, and Qigang Gao:”Integrating Web Content Clustering into Web Log Association Rule Mining?” supported by NSERC
  • Hassan H. Malik, John R. Kender:”Clustering Web Images using Association Rules,Interestingness Measures, and Hypergraph Partitions” ICWE’06, July 11–14, 2006, Palo Alto, California, USA. ACM 1-59593-352-2/06/0007.
  • “Data Mining Introductory and Advanced Topics” by Margaret H. Dunham
  • 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)
  • 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
  • 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
  • Silky Makker, R.K Rathy: “Web Server Performance Optimization using Prediction Prefetching Engine” International Journal of Computer Applications (0975 – 8887) Volume 23– No.9, June 2011
  • So Young Sohn, Yoonseong Kim” Searching customer patterns of mobile service using clustering and quantitative association rule” Published in journal Expert Systems with Applications: An International Journal, Volume 34 Issue 2, February, 2008
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Simple K-means Clustering Algorithm Apriori association Rule Weka Moodle

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