Mining Educational Data to Analyze the Student Motivation Behavior
The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.
[1] J. Mostow, J. Beck, H. Cen, A. Cuneo, E. Gouvea, and C. Heiner, "An
educational data mining tool to browse tutor-student interactions: Time
will tell", In Proceedings of the Workshop on Educational Data Mining,
Pittsburgh, USA (pp. 15-22), 2005.
[2] E. García, C. Romero, S. Ventura, and C. Castro, "Using Rules
Discovery for the Continuous Improvement of e-Learning Courses,"
Lecture Notes in Computer Science, 2006, Volume 4224/2006, 887-895.
[3] M. E. Zorrilla, E. Menasalvas, D. Marin, E. Mora, and J.Segovia, "Web
usage mining project for improving web-based learning sites" , In Web
Mining Workshop. Cataluna pp. 1-22, 2005.
[4] C. Romero, S. Ventura, E. García, "Data mining in course management
systems: Moodle case study and tutorial" Computers & Education,
Volume 51, Issue 1, August 2008, pp. 368-384.
[5] Waiyamai,K "Improving Quality Graduate Student by Data
Mining".Departement of Computer engineering. Faculty of Engineering.
Kasetsart University, Bangkok Thailand. 2003.
[6] B. Minaei-Bidgoli, D. A. Kashy, G. Kortemeyer and, W. F.
Punch."Predicting student performance: an application of data mining
methods with the educational web-based system LON-CAPA" In
Proceedings of ASEE/IEEE Frontiers in Education Conference, Boulder,
CO: IEEE, 2003.
[7] H.H. Hsu, C.H. Chen, and W.P. Tai, "Towards Error-Free and
Personalized Web-Based Courses", In: The 17th International
Conference on Advanced Information Networking and Applications,
AINA-03. March 27-29, Xian,China, pp. 99-104, 2003.
[8] A. Kumar, "Rule-Based Adaptive Problem Generation in Programming
Tutors and its Evaluation", In: The 12th International Conference on
Artificial Intelligence in Education. July 18-22, Amsterdam, pp. 36-
44,2006.
[9] F. Berzal, J.C. Cubero, N. M. Sánchez, J.M. Serrano, and A. Vila,
"Association rule evaluation for classification purposes" Actas del III
Taller Nacional de Minería de Datos y Aprendizaje, TAMIDA2005,
pp.135-144 ISBN: 84-9732-449-8 ,2005.
[10] W. West, B.R.S. Rosser, S. Monani, and L. Gurak, " How Learning
Styles Impact ELearning:a Case Comparative Study Of Undergraduate
Students Who Excelled, Passed Or Failed An Online Course", In
Scientific/Technical Writing. E-learning, pp. 534-543, 2006.
[11] N. Kerdprasop, N. Muenrat, and K. Kerdprasop, "Decision Rule
Induction in a Learning Content Management System" Proceedings of
World Academy of Science, Engineering and Technology, pp.77-81,
2008.
[12] U. M. Fayyad, G. Pitatesky-Shapiro, P. Smyth, and R. Uthurasamy,
"Advances in Knowledge Discovery and Data Mining", AAAI/MIT
Press, 1996.
[13] W. Frawley, G. Piatetsky-Shapiro, and C. Matheus, "Knowledge
Discovery in Databases: An Overview". AI Magazine, Fall 1992, pp.
213-228.
[14] R. Agrawal, T. Imielinski, and A.N. Swami, A. N., "Mining association
rules between sets of items in large databases", In Proceedings of the
1993 ACM SIGMOD International Conference on Management of Data,
pp. 207-216,1993.
[15] Z. Qiankun, "Association Rule Mining:A Survey, Technical
Report",CAIS, Nanyang Technological University, Singapore , 2003
[16] R. Agrawal, and R. Srikant, "Fast algorithms for mining association
rules", In Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp. 487-
499, 1994.
[17] H. Edelstein, "Introduction to Data Mining and Knowledge Discovery",
Third Edition. Two Crows Corporation, Potomac, MD, USA, 1999.
[18] Parr Rud, O. "Data Mining Cookbook. Modeling Data for Marketing,
Risk, and Customer Relationship Management". John Wiley & Sons,
Inc.; 2001.
[19] S. Mitra, and T. Acharya., "Data Mining. Multimedia, Soft Computing,
and Bioinformatics". John Wiley & Sons, Inc. Hoboken, New Jersey;
2003.
[20] J. R. Quinlan, "Introduction of decision tree", Journal of Machine
learning", pp. 81-106, 1986.
[21] L. Hyafil, and RL. Rivest, "Constructing Optimal Binary Decision Trees
is NP-complete" , Information Processing Letters, Vol. 5, No. 1. (1976),
pp. 15-1 R. Kohavi and J. R. Quinlan. Decision-tree discovery.
[22] A. Kumar Sharma and S. Suruchi, "A Comparative Study of
Classification Algorithms for Spam Email Data Analysis", International
Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 5,
pp. 1891-1895. May 2011
[23] http://www.cs.waikato.ac.nz/ml/weka/
[24] E. García, C. Romero, S. Ventura, C. Castro, and T. Calders, "Chapter
7: Association Rule Mining in Learning Management Systems." In:
Hadebook of Educational Data Mining, Taylor&Francis Group, 2010.
[1] J. Mostow, J. Beck, H. Cen, A. Cuneo, E. Gouvea, and C. Heiner, "An
educational data mining tool to browse tutor-student interactions: Time
will tell", In Proceedings of the Workshop on Educational Data Mining,
Pittsburgh, USA (pp. 15-22), 2005.
[2] E. García, C. Romero, S. Ventura, and C. Castro, "Using Rules
Discovery for the Continuous Improvement of e-Learning Courses,"
Lecture Notes in Computer Science, 2006, Volume 4224/2006, 887-895.
[3] M. E. Zorrilla, E. Menasalvas, D. Marin, E. Mora, and J.Segovia, "Web
usage mining project for improving web-based learning sites" , In Web
Mining Workshop. Cataluna pp. 1-22, 2005.
[4] C. Romero, S. Ventura, E. García, "Data mining in course management
systems: Moodle case study and tutorial" Computers & Education,
Volume 51, Issue 1, August 2008, pp. 368-384.
[5] Waiyamai,K "Improving Quality Graduate Student by Data
Mining".Departement of Computer engineering. Faculty of Engineering.
Kasetsart University, Bangkok Thailand. 2003.
[6] B. Minaei-Bidgoli, D. A. Kashy, G. Kortemeyer and, W. F.
Punch."Predicting student performance: an application of data mining
methods with the educational web-based system LON-CAPA" In
Proceedings of ASEE/IEEE Frontiers in Education Conference, Boulder,
CO: IEEE, 2003.
[7] H.H. Hsu, C.H. Chen, and W.P. Tai, "Towards Error-Free and
Personalized Web-Based Courses", In: The 17th International
Conference on Advanced Information Networking and Applications,
AINA-03. March 27-29, Xian,China, pp. 99-104, 2003.
[8] A. Kumar, "Rule-Based Adaptive Problem Generation in Programming
Tutors and its Evaluation", In: The 12th International Conference on
Artificial Intelligence in Education. July 18-22, Amsterdam, pp. 36-
44,2006.
[9] F. Berzal, J.C. Cubero, N. M. Sánchez, J.M. Serrano, and A. Vila,
"Association rule evaluation for classification purposes" Actas del III
Taller Nacional de Minería de Datos y Aprendizaje, TAMIDA2005,
pp.135-144 ISBN: 84-9732-449-8 ,2005.
[10] W. West, B.R.S. Rosser, S. Monani, and L. Gurak, " How Learning
Styles Impact ELearning:a Case Comparative Study Of Undergraduate
Students Who Excelled, Passed Or Failed An Online Course", In
Scientific/Technical Writing. E-learning, pp. 534-543, 2006.
[11] N. Kerdprasop, N. Muenrat, and K. Kerdprasop, "Decision Rule
Induction in a Learning Content Management System" Proceedings of
World Academy of Science, Engineering and Technology, pp.77-81,
2008.
[12] U. M. Fayyad, G. Pitatesky-Shapiro, P. Smyth, and R. Uthurasamy,
"Advances in Knowledge Discovery and Data Mining", AAAI/MIT
Press, 1996.
[13] W. Frawley, G. Piatetsky-Shapiro, and C. Matheus, "Knowledge
Discovery in Databases: An Overview". AI Magazine, Fall 1992, pp.
213-228.
[14] R. Agrawal, T. Imielinski, and A.N. Swami, A. N., "Mining association
rules between sets of items in large databases", In Proceedings of the
1993 ACM SIGMOD International Conference on Management of Data,
pp. 207-216,1993.
[15] Z. Qiankun, "Association Rule Mining:A Survey, Technical
Report",CAIS, Nanyang Technological University, Singapore , 2003
[16] R. Agrawal, and R. Srikant, "Fast algorithms for mining association
rules", In Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp. 487-
499, 1994.
[17] H. Edelstein, "Introduction to Data Mining and Knowledge Discovery",
Third Edition. Two Crows Corporation, Potomac, MD, USA, 1999.
[18] Parr Rud, O. "Data Mining Cookbook. Modeling Data for Marketing,
Risk, and Customer Relationship Management". John Wiley & Sons,
Inc.; 2001.
[19] S. Mitra, and T. Acharya., "Data Mining. Multimedia, Soft Computing,
and Bioinformatics". John Wiley & Sons, Inc. Hoboken, New Jersey;
2003.
[20] J. R. Quinlan, "Introduction of decision tree", Journal of Machine
learning", pp. 81-106, 1986.
[21] L. Hyafil, and RL. Rivest, "Constructing Optimal Binary Decision Trees
is NP-complete" , Information Processing Letters, Vol. 5, No. 1. (1976),
pp. 15-1 R. Kohavi and J. R. Quinlan. Decision-tree discovery.
[22] A. Kumar Sharma and S. Suruchi, "A Comparative Study of
Classification Algorithms for Spam Email Data Analysis", International
Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 5,
pp. 1891-1895. May 2011
[23] http://www.cs.waikato.ac.nz/ml/weka/
[24] E. García, C. Romero, S. Ventura, C. Castro, and T. Calders, "Chapter
7: Association Rule Mining in Learning Management Systems." In:
Hadebook of Educational Data Mining, Taylor&Francis Group, 2010.
@article{"International Journal of Information, Control and Computer Sciences:61819", author = "Kunyanuth Kularbphettong and Cholticha Tongsiri", title = "Mining Educational Data to Analyze the Student Motivation Behavior", abstract = "The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.", keywords = "association rule mining, classification techniques, e-
Learning, Moodle log Motivation Behavior", volume = "6", number = "8", pages = "1040-5", }
