Data mining in the professional educational environment using machine learning methods
Kabdirova A.A. Kulikova V.P. Kulikov V.P.
31 July 2021Little Lion Scientific
Journal of Theoretical and Applied Information Technology
2021#99Issue 143604 - 3616 pp.
The article deals with the problems of building an intelligent system for organizing course training using machine learning methods. The main idea of the present study is to solve the problem of optimal layout and the presentation rate of the material for the listener to learn the courses by automating the methods of data mining. Machine learning is used to collect and initially process information about the trainees for its structuring, identification of characteristic features, generalization, and sorting. Proper evaluation of this information helps to build a more correct and adequate model of the learning process for subsequent analysis and planning. The authors propose automated mechanisms for organizing a personalized environment in the context of managing the development of professional self-actualization of a specialist based on training models such as the static case, loss of qualifications, lost profits, and a dynamic model. The article describes the possibilities of using multidimensional regression analysis in predicting the behavior of the system under study for making managerial decisions and possible risks. The results of the conducted study will be useful for researchers in the field of software design and mathematical simulation, analysts, as well as vocational education teachers – for integrating information data about listeners.
Advanced training , Automation , Data analysis , Dynamic model , Management
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North Kazakhstan University named after Manash Kozybayev, Petropavlovsk, Kazakhstan
North Kazakhstan University named after Manash Kozybayev
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