Research Communication | Open Access
Volume 2019 | Communication ID 221
Volume 2019 | Communication ID 221
| Student Profile Analysis using Machine Learning: State of Art |
Touria Hamim, Nawal Sael, Faouzia Benabbou
Received |
Accepted |
Published |
Jan 31, 2019 |
Feb 26, 2019 |
Mar 01, 2019 |
Abstract: Profile modeling is an important process that aims to give as complete representation as possible of all the aspects related to the user features[1]. In the educational field, student profile modeling can give important solutions to variant problems. It can mainly offer the most exact description of students in order to: • Be able to act in case of problems such as failure, drop out ....; • To offer students the most appropriate orientation and recommendation[2]; • To define the most adaptive learning resources depending on their profiles…. In this paper, we present an analytical ...