Title of article :
Theoretical, Methodological, Communication and Information Technologies Approaches to Modeling and Forecasting Personnel Education in Covid-19 Conditions
Author/Authors :
Pozdnyakova, Lubov Ukrainian state University of Railway Transport - Faculty of Economic on the railway transport, MSN of Ukrainenam, Kharkov, Kharkov region, Ukrain , Abed Hussein, Rasha Al-Manara College for Medical Sciences, Maysan, 62001, Iraq , Zaida, Doaa Talib Department of Laser and Optoelectronics Engineering - Kut University College, Al-Kut, Wasit, Iraq , Khalid AlAzzawi, Waleed Department of Medical Instruments - Medical Technical College - Al-Farahidi University, Baghdad, Iraq , Kotik, Vitaliy Ukrainian state University of Railway Transport - Faculty of Economic on the railway transport, MSN of Ukrainenam, Kharkov, Kharkov region, Ukrain , Hulai, Olena Ukrainian state University of Railway Transport - Faculty of Economic on the railway transport, MSN of Ukrainenam, Kharkov, Kharkov region, Ukrain , Rybina, Olena Ukrainian state University of Railway Transport - Faculty of Economic on the railway transport, MSN of Ukrainenam, Kharkov, Kharkov region, Ukrain
Abstract :
The article is devoted to solving the problems of predicting the education of Ukrainian staff in the current COVID-2019 conditions in order to improve the efficiency of their work. Theoretical approaches regarding the characteristics of modeling and prediction of education have been studied, systematic and summarized. Factors that significantly complement the theory and methodology of the scientific provisions of the economy have been identified, taking into account the peculiarities of their work in the modern economic environment, structural changes, and new changes. The pros and cons of studying modeling approaches have been identified. The main features of structural change have been studied and it has been established that the modeling and forecasting of staff education has significant features.
Keywords :
Educational programs , personnel , planning , training model , COVID-2019
