MATHEMATICAL METHODS IN MONITORING THE QUALITY OF STUDENT PERFORMANCE
Rubrics: PEDAGOGICS
Abstract and keywords
Abstract (English):
The article deals with the statistical analysis of the effectiveness of the educational process at university. The research featured factors affecting the quality of training university students. The authors employed quantitative and qualitative indicators and organizational and pedagogical approaches, as well as methods of correlation and variance analysis. The indicators were systematized and generalized in order to identify the extent of their impact on the effectiveness of the factors under consideration. The reliability of the results was checked using the Pearson test. The methodology of the study was based on the identification of factors that affect the students’ achievements. A factor is a condition for good quality education. Based on the principles of general and professional education of the individual, the authors identified two groups of factors: 1) those related to the performance of the general education stage (academic performance, training profile); 2) those related to the results of higher education (academic performance, areas of training, course of study, academics). The academic performance of the first-year students did not depend on the results of the Unified State Exam and school grades. This dependence began to manifest itself during the second year, i.e. after the adaptation period. Statistical processing provided a mathematical model of the dependence of academic performance on the identified factors. The model can be used to predict the results of academic performance, as well as to adjust the learning process in order to improve the quality of university graduates' training, e.g. additional consultations, new information technologies, changes in the curriculum, level-based differentiation of content, tasks, individualized tasks, etc. The results are of interest for organizers of psychological and pedagogical support of professional self-determination for university students and their socio-psychological adaptation.

Keywords:
mathematical data processing, educational process, quality of student training, information system, monitoring
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