Nowadays, teaching involves more and more the usage of digital tools to accompany face-to-face learning. Such a system is being referred to as hybrid teaching. These digital tools include mainly  distance learning platforms based on LMS (Learning management systems). LMS help to create on-line digital spaces to store and organize teaching material while providing a pedagogical learning process to connect educational communities. Despite the many forms of content that can be implemented on these platforms, from traditional file-based to interactive and animated content, these systems remain both passive and generic. They lack the ability to adapt to the learner in terms of learning skills, preferences, languages, intellectual abilities, learning patterns and rhythms. This paper proposes a design and modeling of an intelligent and dynamic adaptive learning system based on artificial intelligence with the main objective of identifying and providing personalized learning environments adapted to the learner needs.

This research presents an investigation of the problems faced by Moroccan higher education students after the face-to-face learning was reinstated following the COVID-19 pandemic crisis. The proposed methodology is based on an exploratory descriptive analysis through a survey that involved students from different higher education institutions and residing in various regions of Morocco. The collected results revealed that students face pedagogical, technical and organizational constraints that prevent them from making a successful transition to distance learning, even if only partially. Indeed, many students are not motivated by the use of information and communication technology (ICT). The study finally provides recommendations for understanding and overcoming these problems.