Formation of an individual trajectory of online learning on the basis of cluster analysis

Justification for the relevance of developing an individual learning path in the field of online learning. The problems of forming an individual learning trajectory are analyzed. The main problem of personalization of learning from the point of view of the student is highlighted – the difficulty in finding the most appropriate sequence of studying educational objects that best suit their skills and preferences. It is concluded that the existing practices and methods of organizing a personalized educational process of courses in online learning are focused on the statistical characteristics of students that do not change during the study of an online course. Therefore, there is a need to develop a methodology for the formation of an individual learning path. The proposed approach allows us to consider the formation of recommendations as a dynamic process. An algorithm for the formation of an individual learning trajectory has been developed, which consists of a multi-criteria choice of a sequence of online courses at each moment of decision-making according to a given set of criteria and sequential mastering of skills. The choice of online courses is carried out using the cluster analysis method – k-means. Groups of clusters that meet the criteria of online courses have been identified. Each cluster consists of the closest objects – online courses. Based on these results, a sequential selection of online courses is made, using the available information about the user»s requirements and the skills that the learner needs to acquire. The purpose of developing for the formation of an individual learning trajectory is to provide students with the most appropriate sequence of learning objects in accordance with their skills and preferences.