In this article considered the solution of the problem of automated exam scheduling using a genetic algorithm. Proposed method takes into account a number of requirements, necessary to solve the exam-scheduling problem. In this work, in the process of creating initial admissible schedule of the examination session, special attention is paid to the sequence of examinations. To improve the quality of the obtained schedule, was used a genetic algorithm to minimize the number of violations of specified requirements.

Keywords: genetic algorithm, timetable, examinations, university, study group

The article discusses approaches to solving the problem of increasing academic performance of students. On the basis of the multiplicative convolution of the underlying factors influencing the examination results, the proposed structure of the regression model. Considers the problems of multicollinearity of the factors and ""gross errors"". The developed mathematical model and method of constructing regression models of study groups. The proposed system of classification groups depending on the classes mapped to them models. Using the proposed method was processed information from the database of assessments portal OOH don state technical University. Analysis of processed data showed that the adequacy of the generated regression models were performed for 99.7% of groups. It is shown that the proposed model and method can be used in support of the educational process.

Keywords: higher education, academic performance, regression analysis, factors, output variable, the adequacy of the model, correlation coefficient

The article discusses approaches to the problem of increasing academic performance of the university students. Academic performance indicates the percentage of positive ratings received by students as a result of the exam sessions, excluding retakes. Analyzing factors affecting the academic performance is seen on basis of information from the assessments database of UMU portal of Don State Technical University. Highlighted basic factors (objects) that affect academic performance: study groups, teachers, subjects, exams timetable. In this paper, application of clustering methods allowed to use variance analysis of averages. Through two-way analysis of variance (ANOVA) established significant impact of object classes "Teacher" and "Subject" on the percentage of positive evaluations received by students as a result of the session. Given an example of group, teachers and subjects classes, on which the examinations timetable has a significant impact on exam results

Keywords: higher education, academic performance, ANOVA, factors, clustering