Improving student learning efficiency using an online simulator for solving unconditional optimization problems

Abstract

The article describes the process of developing an online simulator for solving uconditional optimization problems using the Python programming language and the Flask framework. The functional requirements for the simulator as an information system are considered. In the course of the research models describing the system were created and algorithms of its operation were built. The simulator reproduces the process of step-by-step training of two methods for finding the extremum of a function of two variables — the method of finding a stationary point and the Newton’s method. The article considers the process of developing and testing an online simulator.Testing of the online simulator was carried out on the basis of Murom Institute (branch) of the Vladimir State University within the discipline “Decision Theory”. The test confirmed that the simulator allows to consolidate the studied material, to acquire skills in solving problems on finding the extremum of a function of two variables, to track errors in the course of solving and to see the results of checking the solution of problems. The simulator generates equations by templates, which leads to a high variability of tasks for students. At the same time, the program can automatically step by step check the solution of the problem by the student, which leads to a decrease in the routine workload on the teacher in terms of checking solutions.