@article{romero07, author = {Romero, C. and Ventura, S.}, title = {Educational data mining: A survey from 1995 to 2005}, journal = {Expert Syst. Appl.}, publisher = {Pergamon Press, Inc.}, address = {Tarrytown, NY, USA}, year = {2007}, volume = {33}, number = {1}, pages = {135--146}, url = {http://portal.acm.org/citation.cfm?id=1223659}, doi = {http://dx.doi.org/10.1016/j.eswa.2006.04.005}, keywords = {data, dm, e-learning, mining, survey, webzu}, abstract = {Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing research community. This paper surveys the application of data mining to traditional educational systems, particular web-based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems. Each of these systems has different data source and objectives for knowledge discovering. After preprocessing the available data in each case, data mining techniques can be applied: statistics and visualization; clustering, classification and outlier detection; association rule mining and pattern mining; and text mining. The success of the plentiful work needs much more specialized work in order for educational data mining to become a mature area.} }