Today, Massive Open Online Courses (MOOCs) have the potential to enable free online education on an enormous scale. However, a concern often raised about MOOCs is the consistently high drop-out rate of MOOC learners. Although many thousands of learners enroll on these courses, a very small proportion actually complete the course.
This work is at the heart of this issue. It is interested in contributing on multi-agents systems and ontologies to describe the learning preferences and adapt educational resources to learner profile in MOOCs platforms. The primary aim of this work is to exploit the potential of multi-agents systems and ontologies to improve learners’ engagement and motivation in MOOCs platforms and therefore reduce the drop-out rates.
As part of the contribution of this work, the paper proposes a model of Multi-Agent System (MAS), based on ontologies for adapting the learning resources proposed to a learner in a MOOCs platform according to his learning preferences. To model an adequate online course, the determination of learner’s preferences is done through the analysis of learner behavior relying on his indicator MBTI (Myers Briggs Type Indicator). The proposed model integrates the main functionalities of an intelligent tutoring system: profiling, updating of the profile, selection, adaptation and presentation of adequate resources. The architecture of the proposed system is composed on two main agents, four ontologies and a set of modules implemented.

In an e-learning environment, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning contents can be that these contents and learning paths are not adapted to this type of learning. Online courses are constructed in a way that does not stimulate interaction, cooperation and collaborative learning. This is why the e-learning often is seen as individual and lonely. In this sense, one way to reduce these problems and promote collaborative e-learning and interaction learner-learner and learner-teacher is to model these contents in the form of collaborative educational games.
The primary aim of this work is to exploit the potential of educational games to improve students' collaboration in e-learning environments. Thus, this paper presents a framework for designing, implementing and building collaborative educational games targeted to e-learning. The proposed framework is composed of two main phases: game design phase that consists to propose a collaborative design process of educational games; and game development phase that consists to implement, package, describe and deliver the games using the IMS-LD standard. The paper describes the steps followed for modeling games, the framework architecture and adopted technical choices. The final framework supports the creation and the use of such games using one of the most popular tools of learning in the web era: the LMS (Learning Management System).