CD-MOOC Context-Driven Massive Open Online Courses

Abstract

The success of MOOC, massive open online courses, rapidly increasing day by day, most schools and universities are very concerned with this issue strongly linked to education. But many limitations decreases the result of the learner in MOOC, such as (the diversity of learners, cheating and abandoned,...), so multiple solutions and tools are present on MOOC platforms to solve those problem each in his way, but found a solution for all those problems is di cult and very complex to develop view that changeable human nature. In our work, we propose a solution, CD-MOOC, allowing the establishment of customization within the MOOC. Our solution is based on the problem of abandonment, helps learners to nd their learning needs on MOOC platforms, and this based on an approach of EIAH (Environment Computing Human Learning) based on learners. We follow two ways ; the rst concerns of the long-term data such as the level of learner..., other concerns that shortterm information that changes with each connection (information according to the user context). Customization is fed from traces of learner interaction with the MOOC platform. An application has been made from this model. Although the impact of MOOC on online training is still uncertain, but what is certain is that, through these online training, knowledge becomes accessible to everyone.