Abstract— Fifty years ago there were just a handful of universities across the globe that could provide for specialized educational courses. Today Universities are generating not only graduates but also massive amounts of data from their systems. So the question that arises is how can a higher educational institution harness the power of this didactic data for its strategic use? This review paper will serve to answer this question. To build an Information system that can learn from the data is a difficult task but it has been achieved successfully by using various data mining approaches like clustering, classification, prediction algorithms etc. However the use of these algorithms with educational dataset is quite low. This review paper focuses to consolidate the different types of clustering algorithms as applied in Educational Data Mining context.
Index Terms— Clustering, educational data mining (EDM), learning styles, learning management systems (LMS).
Ashish Dutt, Saeed Aghabozrgi, and Maizatul Akmal Binti Ismailis are with the Faculty of Computer Science and Information Technology, University of Malaya, Malaysia (e-mail: {ashish_dutt, saeed}@siswa.um.edu.my, maizatul@um.edu.my).
Hamidreza Mahroeianis with University of Otago, New Zealand (e-mail: Hamidreza.mahroeian@postgrad.otago.ac.nz).
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Cite: Ashish Dutt, Saeed Aghabozrgi, Maizatul Akmal Binti Ismail, and Hamidreza Mahroeian, " Clustering Algorithms Applied in Educational Data Mining," International Journal of Information and Electronics Engineering vol. 5, no. 2, pp. 112-116, 2015.
