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Pathology and Prediction of Performance of Virtual Students by Using Regression Techniques


Hossein Fathi, Reza Samizadeh


Vol. 16  No. 7  pp. 142-149


E-learning (virtual learning) has become a very useful way to educate people around the world. Due to various reasons, people are unable to attend classes in person and take advantage of face to face training. Because in today's world, one of the very basic human needs is the education and scientific and non-scientific understanding of science, for residents of remote areas, employed people and all people who are able use lectures and versed professors in urban and rural areas or due to work cannot attend regular in-person meetings, remote or so-called virtual learning program is very important. One of the major challenges in e-learning is checking the rate of progress and finally the evaluation of performance of virtual students who were trained in virtual systems. In this study, using data mining techniques (regression) method, it is tried offer a method to predict academic performance of students in virtual training are learning.


E-Learning, Distance Learning, Academic Performance, Data Mining Techniques, Regression, Neural network