Prédiction des abandons dans un réseau social éducatif

Abstract

During the Covid-19 pandemic, schools/universities, private, urban and economic hospitals were closed for a long period as a precautionary measure against covid-19. After this closure, academic institutions were forced to switch to the use of online teaching. But, several problems were encountered by the students as well as by their teachers, namely the misuse of the platform given the different functionalities offered. For this, several studies have considered social media as an online learning environment for the ease of its use which comes down to its daily use by their users. A social network is a social structure whose components are social identities such as individuals or organizations. These identities are linked together or connected through one or more different relationships, created during social interactions such as friendship, interest or acquaintance. But, the users (teachers and learners) of educational social networks encounter several problems that come down to the huge amount of information available, which leads to the risk of abandonment of learners. To solve the problems mentioned above, we propose to implement an educational social network that aims to predict learners at risk of dropping out based on their learning traces.