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Approaches to the Transformation of the Statistical Education System in the Context of Lifelong Learning and Industry 4.0 (Оn the Example of the Republic of Uzbekistan)

https://doi.org/10.34023/2313-6383-2024-31-1-104-112

Abstract

The article is devoted to the problems of transformation of the educational system in the context of lifelong learning and Industry 4.0 in government decision-making for the development of the investment ecosystem of the Republic of Uzbekistan.

The article outlines characteristics of information and statistical resources used in the public administration system in modern conditions on the basis of analysis, and presents directions of transformation of the system of statistical training and retraining of statisticians.

The issues of introducing digital competencies in the field of statistics into training programs and the need to develop modern knowledge and skills related to the introduction of digital technologies were highlighted.

The author emphasizes the relevance of adapting the educational system in the field of statistics to the evolving requirements of the modern world and concludes that the development of professional competencies of statisticians should be continuous and start with secondary education, followed by retraining, and advanced training received throughout their professional careers.

The recommendations presented in the author’s studycan be used by the authorities and other interested organizations to improve the educational system in the field of statistics.

About the Author

U. М. Kamaletdinov
Tashkent State University of Economics (TSUE)
Uzbekistan

Ulugbek M. Kamaletdinov – Senior Lecturer, Department of Statistics

49, Islam Karimov Str., Tashkent, 100066,



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Review

For citations:


Kamaletdinov U.М. Approaches to the Transformation of the Statistical Education System in the Context of Lifelong Learning and Industry 4.0 (Оn the Example of the Republic of Uzbekistan). Voprosy statistiki. 2024;31(1):104-112. (In Russ.) https://doi.org/10.34023/2313-6383-2024-31-1-104-112

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ISSN 2313-6383 (Print)
ISSN 2658-5499 (Online)