Intellectual learning systems (ITS) are integrate subsystems of users, learning content, learning strategies, communication, processing of heterogeneous data and information in their architecture. ITS are developed as part of a blended/hybrid design initiative to support learning processes. The concept of blended learning has been actively developing recently. Efforts in the field of development of ITS today represent a variety of approaches. At present, there is a growing interest in the intellectual analysis of data in educational systems. The purpose of the work is the development of software tools for data mining, obtained during the educational process. An agent approach is used to implement the toolkit. This article explores the methods of data analysis for the task of identifying the parameters of the learner model.
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Elena E. Kotova (2017) studied this question.