Agent-based algorithm dedicated to personalization of e-learning courses

The optimization of e-learning process, with respect to the diversified learner’s abilities, plays an important role in the modern models of studies. Every learner is characterized by personal adeptness, skills, possessed knowledge, etc. Thus, each learner needs to receive different e-learning content, which optimizes the process of learning. Such optimization can be obtained in various ways, among which the personalization of e-learning courses is investigated. However, it requires the knowledge of the learner’s progress tracking, passed exams, taken courses, etc. Gathering of that information can be assured due to the dynamic development of programming techniques, tools and most of popular e-learning platforms. It is possible not only to store such data, but also to perform the advanced processing of that information. The main objective of the work was to design and implement the personalization algorithm inside the virtual learning environment, which would be able to create automatically individualized path of learning by combining various accessible courses. The proposed algorithm is based on the agent-system approach, which maps the set of agents onto the structure of available courses. Then, the communication between agents, weights of connections and the parameters determining learner’s abilities allow the proper selection of courses and facilitate development of personalized learning path. The paper presents detailed description of created approach on the example of Moodle e-learning platform. The performed tests and obtained results are presented as well.