A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance
S. Arumugam1 , A. Kovalan2 , A.E. Narayanan3
Section:Research Paper, Product Type: Journal Paper
Volume-7 ,
Issue-5 , Page no. 616-624, May-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i5.616624
Online published on May 31, 2019
Copyright © S. Arumugam, A. Kovalan , A.E. Narayanan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: S. Arumugam, A. Kovalan , A.E. Narayanan, “A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.616-624, 2019.
MLA Style Citation: S. Arumugam, A. Kovalan , A.E. Narayanan "A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance." International Journal of Computer Sciences and Engineering 7.5 (2019): 616-624.
APA Style Citation: S. Arumugam, A. Kovalan , A.E. Narayanan, (2019). A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance. International Journal of Computer Sciences and Engineering, 7(5), 616-624.
BibTex Style Citation:
@article{Arumugam_2019,
author = {S. Arumugam, A. Kovalan , A.E. Narayanan},
title = {A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {616-624},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4289},
doi = {https://doi.org/10.26438/ijcse/v7i5.616624}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.616624}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4289
TI - A Novel Educational Data Mining Model using Classification Algorithm for evaluating Students’ E-learning Performance
T2 - International Journal of Computer Sciences and Engineering
AU - S. Arumugam, A. Kovalan , A.E. Narayanan
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 616-624
IS - 5
VL - 7
SN - 2347-2693
ER -
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Abstract
It is possible to assess the learning behavior in online systems or computed based learning backgrounds using data mining techniques on ‘e-learning session activity log data’ from different learning sessions. This information is very useful to improve the e-learning system better. There is a possibility to identify learners’ performance well before the conduction of an examination. The objective of the research is to find weather it is possible to apply Data Mining techniques on this transformed dataset and to predict some information. The educational dataset is used for analyze and also improve any e-Learning models. This research work proposes an Educational Data Mining (EDM) model which provides good performance with precision, recall and f-score. It shows the predictability of students’ grades by mining the e-learning session log data.
Key-Words / Index Term
E-learning, Learning Analytics(LA), Technology Enhanced Learning(TEL), Educational Data Mining(EDM).
References
[1]. M. Vahdat, L. Oneto, D. Anguita, M. Funk, M. Rauterberg.: “A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator”. In: G. Conole et al. (eds.): EC-TEL 2015, LNCS 9307, pp. 352-366. Springer, DOI: 10.1007/978-3-319-24258-3 26,2015
[2]. M. Vahdat, A. Ghio, L. Oneto, D. Anguita, M. Funk, M. Rauterberg, “Advances in learning analytics and educational data mining, in: European Symposium on Artificial Neural Networks”, Computational Intelligence and Machine Learning, 2015.
[3]. Mohamed, N., Sulaiman, R.F., Endut, W.R.: “The use of cyclomatic complexity metrics in programming performance`s assessment”. ProcediaSoc. Beha. Sci. 90, 497-503, 2013
[4]. S. Arumugam, A. Kovalan, A.E.Narayanan " A Study of Easy Educational Data Mining for E-Learning Log Data from complex and large Dataset", IJIET, Volume 11 Issue 1, 39-47, August 2018.
[5]. R. Baker ,"Data Mining for Education". In McGaw, B., Peterson, P., Baker, E. (Eds.) International Encyclopedia of Education (3rd edition), vol. 7, pp. 112-118. Oxford, UK: Elsevier, 2010
[6]. Jay Gholap,”Performance Tuning Of J48 Algorithm For Prediction Of Soil Fertilityby” Asian Journal of Computer Science and Information Technology,Vol 2,No. 8, 2012
[7]. Merceron and Yacef, "Revisiting interestingness of strong symmetric association rules in educational data", International Workshop on Applying Data Mining in e-Learning (ADML`07), Second European Conference on Technology Enhanced Learning,2007
[8]. García et al ,"Drawbacks and solutions of applying association rule mining in learning management systems", International Workshop on Applying Data Mining in e-Learning (ADML`07), Second European Conference on Technology Enhanced Learning, 2007
[9]. Bravo et al.,"A Problem`-Oriented Method for Supporting AEH Authors through Data Mining" International Workshop on Applying Data Mining in e-Learning (ADML`07), Second European Conference on Technology Enhanced Learning, 2007
[10]. ShafiqAslam and Imran Ashraf , “Data Mining Algorithms and their applications in Education Data Mining", International Journal of Advance Research in Computer Science and Management Studies Volume 2, Issue 7, July 2014
[11]. Amjad Abu Saa, “Educational Data Mining & Students’ Performance Prediction”, International Journal of Advanced Computer Science and Applications, Vol. 7, No. 5, 2016
[12]. Brijesh Kumar Baradwaj, Saurabh Pal , “Mining Educational Data to Analyze Students Performance” International Journal of Advanced Computer Science and Applications, Vol. 2, No. 6, 2011
[13]. Mashael Al luhaybi, Allan Tucker and Leila Yousefi ,”The Prediction Of Student Failure Using Classification Methods: A Case study", IPPR, SOENG, DaMi, CSIT, AIS, CSE, CSIP, CCNET - 2018 pp. 79–90, 2018. © CS & IT-CSCP 2018
[14]. DriyaniRajeshinigo, J. Patricia Annie Jebamalar ,”Educational Mining: A Comparative Study of Classification Algorithms Using WEKA”, International Journal of Innovative Research in Computer and Communication Engineering Vol. 5, Issue 3, March 2017
[15]. Shimaa Abd Elkader AbdElaal, "E-learning using data mining", Chinese-Egyptian Research Journal
[16]. ChandiniLulla, YashAgarwal, SnehalKankariya, PrateekSakaray, PankajaAlappanavar ,”Student Academic Performance Prediction using Machine Learning and Data Mining Techniques”,, International Journal of Computer Science and Mobile Computing, Vol.6 Issue.5, pg. 301-307, May- 2017
[17]. N.Sujatha , K. Prakash, “An Efficient and Scalable Auto Recommender System Based on Users Behavior”, International Journal of Scientific Research in Computer Science Engineering, Vol.6, Issue.6, pp.35-40, December 2018
[18]. Himanshi , Komal Kumar Bhatia, “Prediction Model for Under-Graduating Student’s Salary Using Data Mining Techniques”, International Journal of Scientific Research in Network Security and Communication, Volume-6, Issue-2, April 2018
[19]. Jiawei Han and Micheline Kamber, “Data Mining Concepts and Techniques”, 2nd Edition, Morgan Kaufmann Publisher, ELSEVIER, 2006