Une nouvelle approche de recommandation pour l’amélioration des engagements des apprenants

Abstract

During the period of the COVID-19 pandemic, academic institutions considered a new teaching method that aims to reduce the number of students in order to limit contact between them and as a precautionary measure. This system is based on the reduction of the teaching load for each module, which has influenced the cognitive state of the students. For this, the institutions have considered online teaching to strengthen the learning process. But, these environments lack the social and collaborative aspect. To solve this problem, social networks have been used as an online learning tool. These aim to help students to strengthen their cognitive profiles. Several problems have been encountered by users: (1) a huge amount of data and a large number of experts or teachers available on these environments. For this, we propose to implement an educational social network that aims to propose a new trace-based recommendation method for improving learners' engagements to enhance the learning process.