| Article | |
|---|---|
| Article name | SIMULATION OF HIGHER EDUCATION (UNIVERSITIES) SYSTEM PERFORMANCE IN THE VOLGA FEDERAL DISTRICT |
| Authors | Bakumenko, L.. , |
| Bibliographic description | |
| Category | Economics |
| DOI | 519.237, 378.1 |
| DOI | 10.21209/2227-9245-2021-27-10-85-93 |
| Article type | |
| Annotation | The article is devoted to the multidimensional classification method application - a generalized discriminant analysis for the classification of universities in the Volga Federal District by the level of efficiency. The subject of the research is the possibility of classifying universities according to the effectiveness and results of their activities. The purpose of the work is to determine the real situation and positions of 90 universities in the Volga Federal District according to three levels of efficiency: high, medium, low. Discriminant analysis was used as a research method. With the help of discriminant analysis, a predictive model is created (the formation of classification functions), which makes it possible to classify other universities according to the selected system of indicators to check the possible assignment of them to one of the groups according to the level of their effectiveness. To carry out the classification, the variable \"Expert assessment\", categorical predictors have been determined as a dependent variable: \"Type of university\", \"Accreditation\", \"Dormitory\", continuous predictors (these are the numerical variables \"Number of students\", \"Average score of the Exam\", \"Number of training areas\" and \"Number of publications of the RSCI\"). Thus, according to the results of the analysis, an automatic classification has been created, which allows it to be used in the future to more accurately determining of a particular university class without contacting with experts. To improve the accuracy of the classification, it has been determined which of the observations are classified incorrectly and the relevant expert assessments have been corrected. To do this, the values of the squares of mahalanobis distances and a posteriori probabilities have been analyzed. Thus, using classification methods with training, it is possible to build models that can be used for the purposes of preliminary analysis and forecasting of the activities of both higher education institutions based on the results of their activities, and other enterprises and firms |
| Key words | Key words: monitoring; universities; discriminant analysis; classification functions; efficiency; expert assessments; predictive model; Volga Federal District; modeling; Russia |
| Article information | Bakumenko L., Simulation of higher education (universities) system performance in the Volga Federal District // Transbaikal State University Journal, 2021, vol. 27, no. 10, pp. 85-93. DOI: 10.21209/2227-9245-2021-27-10-85-93. |
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| Full article | SIMULATION OF HIGHER EDUCATION (UNIVERSITIES) SYSTEM PERFORMANCE IN THE VOLGA FEDERAL DISTRICT |
