A Systematic Review on Educational Data Mining

Authors(1) :-M. Manjula

In this paper, implementing K-Means clustering algorithm for analyzing the particular dataset and data mining. The main purpose is WEKA process. In Weka process we can get perfect graph, accuracy and random process. The Pre-processing was important concept it may clear a null values, removes a unwanted data and unwanted memory space. In Data mining analyzing data set. In Data mining implementing two methods classification, clustering process. By using classification, clustering we get flexible result and large amount of database. Here, weka process and K-means algorithm going to compare whether both graphs are accurate manner.

Authors and Affiliations

M. Manjula
P. G. Student, Department of Computer Science and Engineering, Adiyamaan College of Engineering, Hosur, Tamil Nadu, India

K-means clustering, Weka process, Classification, Cluster process.

  1. C.Romero and S.Ventura, "Educational data mining: a review of the state of the art," Systems,Man,and Cybernetics,Part C: Applications and Reviews, IEEE Transactions on, vol.40, pp.601-618, 2010.
  2. (2011,01 July). International Educational Data Mining Society. Available: http://www.educationaldatamining.org/ 
  3. J. Ranjan and K. Malik,"Effective educational process: a data-mining approach," Vine, vol.37, pp.502-515, 2007.
  4. V. P. Bresfelean,M. Bresfelean,N. Ghisoiu,and C. A. Comes,"Determining students’ academic failure profile founded on data mining methods," presented at the ITI 2008 - 30th International Conference on Information Technology Interfaces, 2008.
  5. J. Vandamme,-P.,Meskens,N.,Superby,F.-,J,"Predicting Academic Performance by Data Mining Methods," Education Economics, vol.15,pp.405-419, 2007.
  6. R. S. Baker and K. Yacef,"The state of educational data mining in 2009: A review and future visions," JEDM-Journal of Educational Data Mining, 2009.
  7. J. P. Campbell,P. B. DeBlois,and D. G. Oblinger,"Academic analytics: A new tool for a new era," Educause Review, vol.42, p.40,2007.
  8. J. Luan,"Data mining applications in higher education," SPSS Executive, vol.7, 2004.
  9. S.H.Lin, "Data mining for student retention management," Journal of Computing Sciences in Colleges, vol.27, pp.92-99, 2012.
  10. T. Denley,"Austin Peay State University: Degree Compass," EDUCAUSE Review Online., 2012.
  11. M. F. M. Mohsin,N. M. Norwawi,C. F. Hibadullah,and M. H. A. Wahab,"Mining the student programming performance using rough set," presented at the Intelligent Systems and Knowledge Engineering (ISKE), 2010 International Conference on, 2010.
  12. C. Romero and S. Ventura,"Educational data mining: A survey from 1995 to 2005," Expert Systems with Applications, vol.33, pp.135-146,7/ 2007.
  13. A.Pena-Ayala, "Educational data mining: A survey and a data mining-based analysis of recent works," Expert Systems with Applications, vol. 41, pp.1432-1462, 3/ 2014.
  14. O.R.Za?ane and J.Luo, "Web usage mining for a better web-based learning environment," in Proceedings of conference on advanced technology for education, 2001, pp.60-64.
  15. O.R.Za?ane, "Building a recommender agent for e-learning systems," in Computers in Education,2002. Proceedings. International Conference on, 2002, pp.55-59.
  16. R.S.Baker, A.T.Corbett, and A.Z.Wagner, "Off-task behavior in the cognitive tutor classroom: when students game the system," in Proceedings of the SIGCHI conference on Human factors in computing systems, 2004, pp.383-390.
  17. P. Brusilovsky and C. Peylo,"Adaptive and intelligent web-based educational systems," International Journal of Artificial Intelligence in Education, vol.13, pp.159-172, 2003.
  18. J.E.Beck and B.P.Woolf, "High-level student modeling with machine learning," Intelligent tutoring systems, pp.584-593, 2000.
  19. E. Garcia,C. Romero,S. Ventura,and C. de Castro,"A collaborative educational association rule mining tool," The Internet and Higher Education, vol.14, pp.77-88, 2011.
  20. Y. H. Wang and H. C. Liao,"Data mining for adaptive learning in a TESL-based e-learning system," Expert Systems with Applications, vol. 38, pp.6480-6485, 2011.
  21. M. E. Zorrilla,E. Menasalvas,D. Marin,E. Mora,and J. Segovia,"Web usage mining project for improving web-based learning sites," in Computer Aided Systems Theory–EUROCAST 2005,ed: Springer,2005, pp.205-210.
  22. T.S.Madhulatha, "An overview on clustering methods," arXiv preprint arXiv:1205.1117, 2012.
  23. A.K.Jain and R.C.Dubes, Algorithms for clustering data.Englewood Cliffs,NJ, USA: Prentice-Hall, Inc., 1988.
  24. S.Sagiroglu and D.Sinanc, "Big Data: A Review," Proceedings of the 2013
  25. B. Kitchenham,O. Pearl Brereton,D. Budgen,M. Turner,J. Bailey,and S. Linkman,"Systematic literature reviews in software engineering–a systematic literature review," Information and software technology, vol.51, pp.7-15, 2009.
  26. H. M. Chen and M. D. Cooper,"Using clustering techniques to detect usage patterns in a Web?based information system," Journal of the American Society for Information Science and Technology, vol.52, pp. 888-904, 2001.
  27. N.A.Rashid, M.N.Taib, S.Lias, N.Sulaiman, Z.H.Murat, and R.S. S.A.Kadir, "Learners’ Learning Style Classification related to IQ and Stress based on EEG," Procedia - Social and Behavioral Sciences, vol. 29, pp.1061-1070, / 2011.

Publication Details

Published in : Volume 4 | Issue 4 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 164-170
Manuscript Number : IJSRSET184432
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

M. Manjula, " A Systematic Review on Educational Data Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.164-170, March-April-2018.
Journal URL : http://ijsrset.com/IJSRSET184432

Article Preview

Follow Us

Contact Us