Experience of Quantitative Analysis of Students Questionnaires on Education Quality Problems: Methodology, Models and Perspectives
Introduction. The relevance of the article is determined by the lack of scientific substantiation of existing methods of quantitative analysis of mass student questionnaires that can lead to erroneous conclusions about the quality of educational services they receive. Authors first applied the in-house probabilistic approach to the preparation of data for mass questioning of students to develop regression and factor models that adequately reflect their subjective judgments about learning quality. Our goal was to estimate the efficiency and possibility of the practical application of the authors' approach to the analysis of student questionnaire results by means of multivariate statistics by the example of the development of the quantitative estimation model of education quality and subjective well-being of students of Orel State Agrarian University. Materials and Methods. The suggested approach is based on the methods of parametrical multivariate statistics. The empiric basis of modeling consists of the results of questioning students of the 2<sup>nd</sup>-4<sup>th</sup> years of learning. The analytic software SPSS Base was used. Results. At the example of the development of correlation-regressive and factor models of the subjective well-being of the students, we proved the efficiency of the suggested approach to the quantitative modeling of questionnaire results by means of multivariate statistical methods. It is shown that all the obtained correlation-regression models have high statistical characteristics of quality and adequately reflect the simulated phenomena. Of particular interest is the model structure of factors of subjective well-being of students, reflecting the process of their professional and cultural development and adaptation to the current socio-political environment. Discussion and Conclusion. The completed study expanded the understanding of possibilities of quantitative analysis of the results of mass student questioning by simulating various aspects of their subjective well-being. The advantage of this method is that at modeling it allows considering the status features influence on the degree of the higher educational institution satisfaction and the obtainable education quality. The approach suggested by the authors will be useful in quality education monitoring at higher schools as well as in the educational sphere in general and for various social and economic studies.