International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 9, No. 4, 8 Apr. 2017
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An Architecture for Recommendation of Courses in E-learning System
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Author(s)
Index Terms
Data mining, Weka, Moodle, Data preprocessing, E-learning, Educational data mining
Abstract
Over the last few years, the face of traditional learning has changed significantly, due to the emergence of the web. Consequently several learning systems have emerged such as computer-based learning, web-based learning among others, meeting different kinds of educational needs of the learners and educators as well. E-learning systems allow educators, distribute information, create content material, prepare assignments, engage in discussions, and manage distance classes among others. They accumulate a huge amount of data as a result of learner’s interaction with the site. This data can be used to find students’ learning pattern based on which appropriate courses could be recommended to them. However existing approaches of recommending courses to learner offer the same course to all the learners irrespective of their knowledge and skill level which results in decreasing their academic performance. This paper proposes an architecture for the recommendation of courses to a learner based on his/her profile. The profile of a learner is created by applying k-means algorithm to learner’s interaction data in moodle. The results show that the non active learners should not be recommended advanced courses if they have obtained poor marks and are not active in the concern course. In the initial stage we discover learners’ performance in data mining course which will further be extended to other courses as well.
Cite This Paper
Bhupesh Rawat, Sanjay K. Dwivedi, "An Architecture for Recommendation of Courses in E-learning System", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.4, pp.39-47, 2017. DOI:10.5815/ijitcs.2017.04.06
Reference
[1]C.Romero,S.Ventura, and E.Garcia,“Data mining in course management system: moodle case study and tutorial”,Comput.Educ, pp368-384,2008.
[2]V.Kumar, “An Empirical study of the applications of data mining techniques in higher education”, International journal of advanced computer science and application, Vol. 2, No.3,pp. 80-84,2011.
[3]Thaiklang,S., Archint,N.,Archint,S., “Learning resource recommendation framework using rule based reasoning approach”, Journal of Theoretical and Applied information technology,Vol.69,No.1,2014.
[4]Romero,C., Ventura,S., Delgado, A,J., Bra, P., “Personalized links recommendations based on data mining in adaptive educational hypermedia systems”, European Conference on Technology Enhanced Learning,Springer,pp.292-306,2007.
[5]Leony,D.,Pardo,A.,Parada,H., kloos,G. G., “a cloud based architecture for an affective recommender system of e learning resources”,1st international workshop on cloud education environment,2012.
[6]M-S.Chen,., Han,J.,Yu,P.S, “Data mining: An overview from a database perspective”, IEEE Transaction on Knowledge and Data Engineering,Vol. 8, pp 866-833,1996.
[7]Poorni,G.,Balaji,K.,Deeptinivetha,C., “A Personalized E-Learning Recommender System using the concept of Fuzzy tree matching”,International journal of advanced research in computer engineering and technology,vol.4,no.11,2015.
[8]Daomin,X.,Mingchui,D., “Appropriate learning resource recommendation in intelligent web-based educational system”, in proceedings of Intelligent system design and engineering applications,IEEE,2014.
[9]Lopez, B. M., Ramirez, V. R., Hernendez, A, G., “An architecture for developing Educational Recommender Systems”, Research in Computing Science,pp.17-26,2015.
[10]Li,X.,Chang,K,S., “A personalized E-learning system based on user profile constructed using information fusion”, In Proceeding of the 11th International Conference on Distributed Multimedia Systems, pp. 109-114, Banff, Canada, Sep. 2005.
[11]Ivanovic, M., Budimac,Z., “Applying recommender system and adaptive hypermedia for E-Learning Personalization”, computing and infomatics, vol.32,pp.629-659,2013.
[12]T.Sivakumar., “Learning resources recommendation framework for moodle based on analysis of mostly accessed resources by good students”(Master thesis),retrieved from Digital library university of moratuwa.(http://dl.lib.mrt.ac.lk/handle/123/12347),2014
[13]F.Castro,A.Vellido,A. Nebot, and F.Mugica, “Applying data mining techniques to e-learning problems”, Studies in Computational Intelligence,Vol. 62, pp 183-221,2007.
[14]Todtli,B., Laner,M., Semenov,J., Paoli,B., “Recommending Physics Exercise in Moodle Based on Hierarchical Competence Profile”, In: Verbert K., Sharples M., Klobučar T. (eds) Adaptive and Adaptable Learning. EC-TEL 2016. Lecture Notes in Computer Science, vol 9891. Springer, Cham.
[15]Ray,S.,Sharma,A., “A collaborative filtering based approach for recommending elective courses”, In Proceedings of the 5th International Conference on Information Intelligence, Systems, Technology and Management (ICISTM), S. Dua, S. Sahni, and D. Goyal, Eds. Springer-Verlag, 330–339,2011.
[16]Tang,Y,T., McCalla,G., “smart recommendation for an evolving e-learning system”, Workshop on Technologies for Electronic Documents for Supporting Learning, International Conference on Artificial Intelligence in Education,pp.699-710,2003.
[17]Pallavi,S., Chavan,A., “Open-source learning management system with moodle”,2004.
[18]Al-Radaideh,E.AI-Shawakfa, & AI-Najjar, “ Mining students data using decision tree”, In proceedings of the international Arab conference on information technology,2006.
[19]Lu,J., “A personalized e-learning material recommender system”, International Conference on Information Technology, Macquarie Scientific Publishing,2004.
[20]Carmona,C.,Castillo,G.,Millan,E., “Discovering Student Preferences in E-learning”, Proceedings of the International Workshop on Applying Data Mining in e-Learning,pp.33-42,2007.
[21]Salehi,M.,Kamalabadi,N,I.,Ghoushchi,G, B,M., “Personalized recommendation of learning material using sequential pattern mining and attribute based collaborative filtering”, Education and information technology,vol.19,no.4,pp.713-735,2014.
[22]Sin,K.,Muthu,L., “Application of big data in education data mining and learning analytics-A literature review”,ITACT journal on soft computing,vol.5,no.4,2015.
[23]Baker, R.S.J.d. (in press) Data Mining for Education. To appear in McGaw, B., Peterson, P.,Baker, E. (Eds.) International Encyclopedia of Education (3rd edition). Oxford, UK: Elsevier.
[24]Algarni,A., “Data mining in Education”, International journal of Advanced Computer Science and Applications,Vol.7,No.6,2016.
[25]Romero,C.,Ventura,S., “Data mining in education”, WIREs Data Mining Knowl Discovery, Vol.3,pp. 12–27,2013.
[26]Namratha,B., “Educational Data Mining-Applications and Techniques”, International journal of latest trends in Engineering and Technology,Vol.7,No.2,2016.
[27]Koedinger, K. R., D'Mello, S., McLaughlin, E. A., Pardos, Z. A.,Rosé, C. P.,. “Data mining and education”, Wiley Interdisciplinary Reviews: Cognitive Science. Vol.6,No. 4, pp. 333-353 ,2015.
[28]Feng,M.,Bienkowski,M., Means,B.,“Enhancing Teaching and Learning through EducationalData Mining and Learning Analytics: An Issue Brief”,U.S. Department of Education, 2012.
[29]Merceron,A.,Yacef,K., “Educational data mining: A case study”, In proceedings of AIED,pp.467-474,,2005.
[30]Tzouveli, P., Mylonas, P.,Kollias, S., “An Intelligent E-Learning System Based on Learner Profiling and Learning Resources Adaptation”, Computers & Education,Vol.51,No.1, pp.224-238,2008.
[31]Romero, C., Ventura, S., Delgado, J. A., Bra, P. D. (in press). Personalized links recommendation based on data mining in adaptive educational hypermedia systems, In Second European Conference on technology enhanced learning. Crete, Greece.
[32]E.Frank, A.Mark A. Hall, H.Ian,and H-I Witten, "Data Mining: Practical Machine Learning Tools and Techniques", Morgan Kaufmann, Fourth Edition,2016.
[33]C.Romero,S.Ventura,P. G, Espejo,C. Hervas, “Data mining algorithms to classify students”,In: Education Data Mining conference,2008.
[34]Aher,S.B.,Lobo,L., “Combination of machine learning algorithms for recommendation of courses in E-learning system based” on historical data.”, Knowledge-Based System, Elsevier,Vol.51, pp.1-14,2013.
[35]Mueen,A.,Zafar,B.,Manzoor,U., “Modeling and ”Predicting Students’ Academic Performance Using Data Mining Techniques”, International Journal of Modern Education and Computer Science, MECS, Vol.8,No.11,pp.36-42,2016.
[36]Da,M.,Wei,W.,Hai-gauan,H.,Jian-he,G., “The Application of Bayesian Classification Theories in Distance Education System”, Internationl Journal of Modern Education and Computer Science,MECS,Vol.4,pp.9-16,2011.