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Mining Educational Data for Students' Placement Prediction using Sum of Difference Method

by Ramanathan. L, Swarnalatha P, D. Ganesh Gopal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 18
Year of Publication: 2014
Authors: Ramanathan. L, Swarnalatha P, D. Ganesh Gopal
10.5120/17474-8330

Ramanathan. L, Swarnalatha P, D. Ganesh Gopal . Mining Educational Data for Students' Placement Prediction using Sum of Difference Method. International Journal of Computer Applications. 99, 18 ( August 2014), 36-39. DOI=10.5120/17474-8330

@article{ 10.5120/17474-8330,
author = { Ramanathan. L, Swarnalatha P, D. Ganesh Gopal },
title = { Mining Educational Data for Students' Placement Prediction using Sum of Difference Method },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 18 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number18/17474-8330/ },
doi = { 10.5120/17474-8330 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:28:33.213040+05:30
%A Ramanathan. L
%A Swarnalatha P
%A D. Ganesh Gopal
%T Mining Educational Data for Students' Placement Prediction using Sum of Difference Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 18
%P 36-39
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The purpose of higher education organizations have to offer superior education to its students. The proficiency to forecast student's achievement is valuable in affiliated ways associated with organization education system. Students' scores which they got in an exam can be used to invent training set to dominate learning algorithms. With the academia attributes of students such as internal marks, lab marks, age etc. , it can be easily predict their performance. After getting predicted result the performance of the student to engage with desirable assistance to the students will be improved. Educational Data Mining (EDM) offers such information to educational organization from educational data. EDM provides various methods for prediction of student`s performance, which improve the future result of students. In this paper, by using the attributes such as academic records, age, and achievement etc. , EDM has been used for predicting the performance about placement of final year students. Based on the result, higher education organizations can offer superior education to its students.

References
  1. Molina, M. M. , Luna, J. M. , Romero, C. , & Ventura, S. , 2012, "Meta-learning approach for automatic parameter tuning: a case of study with educational datasets", in Proceedings of the 5th international conference on educational data mining ,pp. 180-183.
  2. Pardos, Z. A. , Wang, Q. Y. , & Trivedi, S. , 2012,"The real world significance of performance prediction".
  3. Thai-Nghe, N. , Horváth, T. , & Schmidt-Thieme, L. , 2011, "Factorization models for forecasting student performance. In Proceedings of the 4th international conference on educational data mining",pp. 11–20.
  4. B. Sen, Ucar E. , delen D. ,2012,"Predicting and analyzing secondary education placement-test scores.
  5. Baker, R. S. J. D. , Gowda, S. M. , & Corbett, A. T. ,2011, "Automatically detecting a student's preparation for future learning: Help use is key",in Proceedings of the 4th international conference on educational data mining ,pp. 179–188.
  6. Pardos, Z. A. , Gowda, S. M. , Baker, R. S. J. D. , & Heffernan, N. T. ,2011, "Ensembling predictions of student post-test scores for an intelligent tutoring system in networks",in Proceedings of the 3rd international conference on educational data mining, pp. 299–300.
  7. Marquez-Vera, C. , Romero, C. , & Ventura, S. ,2011, "Predicting school failure using data mining",in Proceedings of the 4th international conference on educational data mining,pp. 271– 275.
  8. J. Akcapinar, G. , Cosgun, E. , & Altun, A. , 2011,"Prediction of perceived disorientation in online learning environment with random forest regression", in Proceedings of the 4th international conference on educational data mining, pp. 259–263.
  9. Schoor, C. , & Bannert, M. ,2012, "Exploring regulatory processes during a computer-supported collaborative learning task using process mining. Computers in Human Behaviour", Vol. 28(4), pp. 1321–1331
  10. Wang, Y. , & Heffernan, N. T. ,2012,"Leveraging first response time into the knowledge tracing model",in Proceedings of the 5th international conference on educational data mining, pp. 176–179.
  11. Gowda, S. M. , Rowe, J. P. , Baker, R. S. J. D. , Chi, M. , & Koedinger, K. R. ,2011,"Improving models of slipping, guessing, and moment-by-moment learning with estimates of skill difficulty",in Proceedings of the 4th international conference on educational data mining,pp. 199–208.
  12. Swarnalatha, P. and. Tripathy B. K. , 2012,"A Centroid Model for the Depth Assessment of Images using Rough Fuzzy Set Techniques" at International Journal of Intelligent Systems and Applications,vol. 1. no. 3. pp. 20-26.
  13. Tripathy, B. K. , Swarnalatha P. , et. al. ,2013,"Rough Intuitionistic Fuzzy C-MeansAlgorithm and a Comparative Analysis", Proceedings of the 6th ACM India Computing Convention, COMPUTE '13, Aug 22-24, 2013 ACM 978-1-4503-2545- 5/13/08.
  14. Swarnalatha, P. and Tripathy B. K. ,2013, "Depth Computation using bit plane with clustering techniques for satellite images", International Journal of Earth Sciences and Engineering, vol. 6,no. 6(01),pp. 1541-1553.
  15. Swarnalatha, P. and Tripathy B. K. ,2014, "A Comparative Study of RIFCM with Other Related Algorithms from Their Suitability in Analysis of Satellite Images using Other Supporting Techniques", Kybernetes, Emerald Publications,vol. 43. no. 1. , pp. 53-81.
  16. Swarnalatha, P. ,. Tripathy B. K, Nithin Prakash Ladda and Debashish Ghosh,2014,"Cluster Analysis Using Hybrid Soft Computing Techniques", Proceedings of International Conference on Advances in Communication, Network, and,Computing, CNC, Elsevier,pp. 516- 524.
  17. Swarnalatha, P. ,. Tripathy B. K,. Prabu S, Ramakrishanan R. and Manthira Moorthi S. ,2014, "Depth Reconstruction using Geometric Correction with Anaglyph Approach for Satellite Imagery", Proceedings of International Conference on Advances in Communication, Network, and Computing, CNC, Elsevier, pp. 506-515.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Educational Data Mining Sum of Difference Prediction.