An Architecture for Recommendation of Courses in E-learning

Over the last few years, the face of traditional learning has changed significantly, primarily due to the emergence of the worldwide web. So in order to take advantage of the web various kinds of learning systems have emerged such as computer-based learning, web-based learning and other forms of electronic learning which have been very successful in meeting different kinds of the educational need of the learners and educators thus they are adopted by a large number of universities and institutions worldwide. E-learning systems let educators distribute information, create content material, prepare assignments, engage in discussions, and manage distance classes among others. They accumulate a huge amount of data as a result of learner's interaction with the site, which has the potential to provide useful knowledge to the students, teachers, e-learning system administrators and university management for decision making. However the tools that existed in the past for data mining were inadequate to provide useful insight into the huge data generated consequently, data mining techniques began to facilitate the process of knowledge discovery. In this paper, we propose an architecture for the recommendation of the best combination of courses to the students and apply the apriori algorithm at the preliminary stage.