TEACHING FUTURE TEACHERS OF MATHEMATICS IN THE FUNDAMENTALS OF MATHEMATICAL PROGRAMMING: THE WAY TO SUSTAINABLE DEVELOPMENT

Introduction. Optimization methods, particularly mathematical programming, constitute a significant branch of mathematics, serving as a powerful tool for facilitating decision-making and resource allocation in thepursuit of sustainable development. Various facets of optimization methods can be applied to address numerous sustainability challenges. An undeniable factor in achieving the objectives of sustainable development is a high- quality mathematics education. The pivotal role in imparting mathematics education is assumed by teachers of mathematics. It is largely upon them that the cultivation of students' awareness regarding the significance of mathematics for sustainable development relies. This involves fostering and developing critical thinking skills and the ability to identify and solve problems. Purpose. To justify the selection of the content in one of the sections of optimization methods - mathematical programming - for future mathematics teachers and to enhance the teaching methodology for students in this section, digital educational resources, especially computer mathematics systems, are essential. Methods. Analysis, synthesis, generalization, comparison, analogy, questionnaire. Results. Attention is focused on the role of optimization methods, particularly mathematical programming, in ensuring sustainable development. The justification for selecting the content of the Mathematical Programming section for future mathematics teachers is provided. The potential of employing digital educational resources during the learning of mathematical programming is explored. The necessity and significance of utilizing computer mathematics systems, specifically MATLAB, for conducting laboratory work are highlighted. The use of GeoGebra as a tool for visualization during the resolution of linear programming problems is examined. Specific examples of program implementation for solving one-dimensional and multi-dimensional unconditional optimization problems, as well as multi-dimensional conditional optimization using the MATLAB system, are presented. Additionally, distinct methodological recommendations are offered. The study also investigates the shift in the attitude of higher education students towards the study of mathematical programming. Originality. The correlation between the content and methods of mathematical programming with the school mathematics course is illustrated. The need for utilizing digital educational resources while teaching the fundamentals of mathematical programming to future mathematics teachers is justified. The perception of learners towards the section on optimization methods, specifically mathematical programming, was investigated. Conclusion. Thus, instructing prospective mathematics teachers on optimization methods, particularly mathematical programming, isn't merely an addition to their curriculum; it's about providing them with the knowledge and skills to empower the next generation of learners. By applying the gained understanding of optimization methods in their future professional endeavors, aspiring mathematics teachers will bridge the gap between theory and practical problem-solving, making mathematics engaging and pertinent for their students. This approach not only prepares students for their future profession but also fosters a love for mathematics. As a next step, prospects for further research include conducting a similar study on justifying the selection of content and teaching methods for prospective mathematics teachers to delve into the basics of the calculus of variations as one of the optimization methods' sections.