Abstract:

This article focuses on how to support the education of mathematics and computer science students in higher education. At our university, these students are required to complete courses in modelling and simulation, and probability and statistics. The former covers topics such as random number generation and its applications. The subject includes several procedures, of which the simplest way of illustrating is to look at different distributions. Among others, the course will introduce students to the possibilities of generating random numbers with uniform, normal and exponential distributions. These types of distributions are not only covered in the modelling and simulation course for computer science students, but also in the probability and statistics course for mathematics students.

The aim of our study was to create a software that could be used as a tool to help students of both courses to learn and understand the given topic. We focused on the possibilities of uniform distribution of the cases listed above. Two main perspectives were taken into account when designing the project. The first is the creation of a visualisation-focused tool that makes the learning material clearer and more tangible for mathematics students through different simulation options and testing. The second perspective presents random number generation algorithms with uniform distribution for computer science students. The software allows students to test and compare different uniformly distributed algorithms using different parameterisation options.

In this article, we will describe the architecture of our software, the working principle of the processed algorithms, its practical potential, and future research and development possibilities.

Keywords:

Simulation, random number generation, uniform distribution, STEM, statistics, algorithms, educational software.