User Behavioral Data Enhancement and Vectorization in E-Learning Models

Abstract

The data acquiring mechanism on the criteria of users-interaction to the users-interface has been developed in the initial stage of this applied science research. The input system gets multiple inhomogeneous texts about the interface actions of a specific user, whereas the vector has been demonstrated by the results that describe the user in a consolidated manner. Moreover, the vector collection for various users has been employed as an input of clustering algorithm (i.e. K-means), the outcomes of behaviors of users are among the one of these (k-clusters) that differentiates the users by their behavioral types. Almost, 67.8% of the Interactional data of the interface of the user is accessible to GlobalLab platform users. However, for the electronic diary (i.e.Diary.ru) there is no corresponding data. Although not every user of the GlobalLab system takes the initiative to create the projects, ideas, questionnaire task, and educational resources, the proportion of learners have been 9.7 thousand whose value with all 4 variables varied according to a neutral one.