e-Learning emerged as a way for enhancing the quality of education and providing accessible distance learning to allow learners to study beyond regular class time, transcending the mandatory presence of teachers and the availability of classrooms by providing the necessary resources and services. One of the main issues of e-learning, especially in engineering education, is the lack of online educational laboratories. Practical work remains a considerable burden as engineering educational programs focus on handling real equipment. These last are only accessible within a restrictive schedule and might be unaffordable for low budget institutions. The need is clear for interactive platforms that enhance the motivation and controls the regulation of workload for each student. In this paper, an overview about online laboratories is given and a simple approach of remote lab is suggested. The proposal of our research team (Team SEITI) can be used for carrying-out experiments that require neither assembly nor physical changes until the results are obtained unless a technician, that must be present in the laboratory, acts on equipment. The idea is to set up a real-time measurement retrieval laboratory that requires the involvement of a technician to act on instruments and will grant access to a large scale of students.

E-learning has evolved from traditional content delivery approaches to a personalized, adaptive and learnercentered knowledge transfer. In the way of customizing the learning experience learning styles represent key features that cannot be neglected. Learning style designates any representative characteristic of an individual while learning, i.e. a particular way of dealing with a given learning task, the preferred media, or the learning strategies adopted in order to achieve a task. Despite the fact that the use of learning styles in adaptive educational environments has become controversial, but there is no empirical evidence of its usefulness. The main objective of our paper is to respond to the question "What learning style model is most appropriate for use in adaptive educational environments?"

It has been proven that adopting the “one size fits one” approach has better learning outcomes than the “one size fits all” one. A customized learning experience is attainable with the use of learner models, the main source of variability, in adaptive educational hypermedia systems or any intelligent learning environment. While such a model includes a large number of characteristics which can be difficult to incorporate and use, several standards that were developed to overcome these complexities. In this paper, the proposed work intents to improve learner’s model representation to meet the requirements and needs of adaptation. We took IMS-LIP, IMS-ACCLIP and IMS-RDCEO standards into consideration and incorporated their characteristics to our proposed learner model so that it conforms to international standards. Moreover, the suggested learner model takes advantage of the semantic web technologies that offer a better data organization, indexing and management and ensures the reusability, the interoperability and the extensibility of this model. Furthermore, due to the use of ontologies, the metadata about a learner can be used by a wide range of personalization techniques to provide more accurate customization.