NETWORK-BASED SIMULATION OF THE RESULTS MONITORING EVALUATION OF ACTIVITY OF UNIVERSITIES

The article presents the results of neural network modeling of the interrelation between the indicators of monitoring the effectiveness of the activity of universities and monitoring of the employment of graduates. The proposed models provide an opportunity to predict the impact of certain indicators of the effectiveness of the university on changing conditions for the success of graduates and identify indicators that have the strongest impact on the effectiveness of the employment process. Since the employment of graduates is the resultant indicator of the educational activity of the university and one of the key indicators of its relevance, the problem solved in the article seems to be relevant. In the course of the study it was possible to build neural network models with a sufficiently high degree of reliability. At the same time, it was found that 57 indicators of monitoring the performance of HEIs are significant for forecasting the proportion of graduates who have found employment during the calendar year following the year of release, and only 3 monitoring indicators are significant for forecasting the average amount of monthly payments to graduates in the first year after graduation from the university effectiveness. Based on the results of the study, a conclusion was made about the impact of modeling results on the relationship between the indicators of employment monitoring and performance monitoring on adjusting management decisions and improving the educational activity of the university.

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