THE PROBLEM OF CLASSIFICATION OF STUDENTS USING THE METHODS OF INTELLECTUAL DATA ANALYSIS

Technologically supported learning environments generate a large amount of data that can be collected and analyzed using relevant algorithms. Learning analytics functions are necessary for planning and introducing changes in the organization of learning processes, providing adaptive recommendations and personalized analysis of learning activities. There are several different classification methods used in knowledge discovery and data mining (Knowledge Discovery and Data Mining). Each method or technique has its advantages. Data analysis methods are applied to the task of classifying students. One of the questions is the definition of signs of differentiation of students. The signs of differentiation, characterizing the individual parameters of the cognitive sphere, and components of the model of the cognitive-style potential of students are proposed. These methods are integrated into the web environment of intellectual support of learning processes. The results obtained with the help of several classifiers are analyzed. The classification according to the method proposed in the article gives more accurate results than those obtained in other studies and published in the available sources.

Authors: E. E. Kotova, A. S. Pisarev

Direction: Informatics, Computer Technologies And Control

Keywords: Data analysis, student classification, cognitive-style potential, intellectual support web environment

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