CLUSTERIZATION OF MOSCOW REGION HIGHER EDUCATION ORGANIZATIONS ACCORDING TO THE RESULTS OF MONITORING THEIR ACTIVITIES

Abstract

Aim. To study the possibility of using methods of cluster analysis of large amounts of data to assess and identify the features of the activities of universities based on the results of their monitoring. Methodology. Clustering was carried out according to key indicators of the efficiency and quality of the activities of universities in Moscow region using the k-means method using the analytical platform «Deductor». Results. The study showed the possibility of using cluster analysis for dividing educational institutions into homogeneous groups. A comparative analysis of each selected cluster is carried out, and on this basis, each cluster is given a meaningful characteristic with the identification of their features. A generalizing assessment of each cluster has been determined, which makes it possible to rank them. Research implications. The obtained results of cluster analysis can become the basis for increasing the validity and quality of management decisions taken by public authorities, founders and management of universities in the field of ensuring the competitiveness, efficiency and quality of Russian higher education, and for employers and applicants to help in the competent choice of a university for training.