Учебно-методический комплекс дисциплины "Дискретная математика"
In this paper, we report on the results of an experiment in teaching discrete mathematics to students majoring in business informatics. We supplemented our problem-based approach to teaching the course with a set of Likert-scale surveys or questionnaires that helped improve the students’ performance. On the one hand, these surveys gave us feedback and, on the other, encouraged the students to reflect on the subject-matter. The experiment was quite successful, as the grades obtained by the students on the exam were significantly higher than usual. Here, we describe the structure of the surveys and the method of evaluation of the experimental results.
The fourth RuFiDiM conference, Russian-Finnish Symposium on Discrete Mathematics took place in Turku in May, from 16th til 19th, 2017
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.
In this paper, we discuss examples of assignments for a course in discrete mathematics for undergraduate students majoring in business informatics. We consider several problems with computer-based solutions and discuss general strategies for using computers in teaching mathematics and its applications. In order to evaluate the effectiveness of our approach, we conducted an anonymous survey. The results of the survey provide evidence that our approach contributes to high outcomes and aligns with the course aims and objectives.
A form for an unbiased estimate of the coefficient of determination of a linear regression model is obtained. It is calculated by using a sample from a multivariate normal distribution. This estimate is proposed as an alternative criterion for a choice of regression factors.