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Data Preparation Strategy in E-Learning System using Association Rule Algorithm

by Sunita B Aher, Lobo L.m.r.j.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 3
Year of Publication: 2012
Authors: Sunita B Aher, Lobo L.m.r.j.
10.5120/5524-7563

Sunita B Aher, Lobo L.m.r.j. . Data Preparation Strategy in E-Learning System using Association Rule Algorithm. International Journal of Computer Applications. 41, 3 ( March 2012), 35-40. DOI=10.5120/5524-7563

@article{ 10.5120/5524-7563,
author = { Sunita B Aher, Lobo L.m.r.j. },
title = { Data Preparation Strategy in E-Learning System using Association Rule Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 3 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 35-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number3/5524-7563/ },
doi = { 10.5120/5524-7563 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:41.908809+05:30
%A Sunita B Aher
%A Lobo L.m.r.j.
%T Data Preparation Strategy in E-Learning System using Association Rule Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 3
%P 35-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data preparation is the important step in Course Recommendation System which aims at predicting the course selected by student. In this paper we present the data preparation strategy for Course Recommendation System. Here we have used the real data of courses offered through Moodle package of the college & apply the data preparation strategy to it to find out the best combination of courses. We are using the open source data mining tool Weka to check the result.

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. Cristóbal Romero, Sebastián Ventura, Pedro G. Espejo and César Hervás: Data Mining Algorithms to Classify Students-accessed from http://sci2s. ugr. es/keel/pdf/specific/congreso/Data%20Mining%20Algorithms%20to%20Classify%20Students. pdf on 15-03-2012
  3. J Lu: A personalized e-Learning Material Recommender system: Proceedings of the 2nd International Conference on IT for application, ISBN: 0646423134
  4. Seki, K. , Tsukahara, W. , Okamoto, T. : System Development and Practice of e-Learning in Graduate School. In: The Fifth IEEE International Conference on Advanced Learning Technologies, ICALT'05. IEEE Computer Society, Los Angeles, CA (2005) 740-744.
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  6. Hamalainen, W. , Suhonen, J. , Sutinen, E. , & Toivonen, H. (2004). Data mining in personalizing distance education courses. In World conference on open learning and distance education, Hong Kong (pp. 1–11).
  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
  9. "Data Mining Introductory and Advanced Topics" by Margaret H. Dunham
  10. Galit Ben-Zadok, Arnon Hershkovitz, Rachel Mintz and Rafi Nachmias: "Examining online learning processes based on log files analysis: A case study" Research, Reflections and Innovations in Integrating ICT in Education.
Index Terms

Computer Science
Information Sciences

Keywords

Apriori Association Rule Weka Moodle

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