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International audience; E-learning has gained tremendous popularity. In recent decades, major universities all over the world offer online courses aiming to support student learning performance, yet often exhibit low completion rates. Faced with the challenge of decreasing learners' dropout rates, e-learning communities are increasingly in need to improve trainings. Machine learning and data analysis have emerged as powerful methods to analyze educational data. They can therefore empower the Technology Enhanced Learning Environments (TELEs). Many research projects have interest in understanding dropout factors related to learners, but few works are committed to refine pedagogical content quality. To address this problem, this paper proposes descriptive statistics analysis to evaluate e-course factors contributing to its success. We take up, at first, the task of analyzing a sample of successful online courses. Then, we manage to identify features that are able to attract a large number of learners, meet their needs and improve their satisfaction. We report findings of an exploratory study that investigates the relationship between course success and the strategy of pedagogical content creation .

International audience; Distance education or distance learning has existed for centuries. The way of practicing has evolved with the development of technologies (mail, broadcasted courses, telephone and television) . Since 1990, e-learning has emerged in the United States and Canada with the development of the Internet as the new form of distance education. Nowadays, many educational organizations have implemented Technology Enhanced Learning Environments (TELE) to inhance student learning performance. Artificial intelligence is one of the promising subjects having a major impact on e-learning researchs. Specially the machine learning based methods can be implemented to improve TELE. It is with a view to examine the state of the art of emergent approaches related to the use of machine learning approaches to improve TELE, that this chapter has been prepared. At first, we introduce the key concepts related to machine learning. Then, we present some recent works using machine learning in e-learning context.

International audience; E-learning has been receiving increasing attention in recent years. Many educational organizations have implemented Computing Environments for Human Learning (CEHL) to improve student learning performance. This paper presents an overview of e-learning area, with a goal of providing references to fundamental concepts and identifying challenges for the broad community of e-learning practitioners. Until now, pedagogical content has been considered as a critical issue. Thus, we discuss recent content personalization's studies and the most important approaches.

This thesis is situated in the e-learning domain and in the context of the authoring of educative content (composed learning objects) by reuse of learning objects. This approach is supported by many models like SCORM or SIMBAD. Using such as approach by authors still difficult due to the complexity of the composition process influencing the quality of the content especially from a pedagogical point of view. We propose in our research works an author assistance approach with a set of analysis tools which offer best understanding of the true nature of the composed learning object and its degree of conformity to the author, the model and the use context requirements. Analyses are applied to the learning object’s content, educative metadata and composition structure. The goal is to generate a learning object’s detailed cartography. Automatic generated indicators reveal details about the different facets of the composed learning object especially the system view and the learner view. If the analysis is satisfactory additional metadata are then automatically calculated by the tools based on the reused learning objects’ metadata. The learning object’s composition can be guided by some conformity rules. Those rules can cover intended structural and semantic criterion. Our approach offers a support to promote the reuse of learning objects in an effective manner. It provides theoretical and practical elements allowing authors to control the “authoring by reuse” process. Consequently our approach allows authors to produce high quality composed learning objects., Cette thèse se situe dans le domaine de la création de contenus pédagogiques par une approche basée sur une structuration à base d’objets d’apprentissage et leur réutilisation au sein d’objets plus complexes. Les modèles récents d’objets pédagogiques comme SCORM ou SIMBAD permettent aux auteurs de construire de nouveaux objets par assemblage d’objets existants. La difficulté pour les auteurs est de concevoir de tels objets en maitrisant la complexité de la composition et en pouvant garantir un haut niveau de qualité, y compris pédagogique. Nous proposons dans ce travail une approche d’assistance aux auteurs basée sur un ensemble d’outils d’analyse permettant de mieux qualifier l’objet composé et d’en vérifier la conformité. Ces analyses portent tant sur le contenu de l’objet, ses métadonnées notamment celles issues de la norme LOM, que sur la structure de composition elle-même. L’objectif est de générer une cartographie détaillée sur l’objet en question. Il s’agit d’offrir à l’auteur des indicateurs divers et variés qui vont lui permettre d’avoir une meilleur vue sur les différentes facettes de l’objet d’apprentissage en cours de conception. En particulier, il aura une analyse de la vue système et de la vue apprenant. Une fois que l’analyse est satisfaisante, des métadonnées complémentaires sont calculées automatiquement par notre environnement en se basant sur les métadonnées éducatives des objets utilisés dans la composition de l’objet. La composition d’un objet peut être guidée par des règles de conformité. Celles-ci permettent de décrire certains critères structurels et sémantiques recherchés. Cette approche offre ainsi un moyen pour la promotion de la réutilisation des objets d’apprentissage. Elle offre le support théorique et les éléments pratiques permettent de rendre la composition par réutilisation pleinement sous contrôle de l’auteur et capable de produire par conséquence des objets d’apprentissage respectant des critères de qualité.