Integration of computational thinking into the mathematical education of students of natural sciences

Introduction. Computational thinking of the younger generation is becoming important in the modern information society, as it provides young people with an understanding of the computational nature of the problem-solving process using digital technologies. Research issues related to the topic of computational thinking to university students of certain profiles in the process of teaching mathematics are insufficiently studied. The purpose of the study is to clarify mathematical topics, pedagogical approaches and the degree of integration of computational thinking into the mathematical education of students of natural sciences with the help of specific examples. Materials and methods. 68 students of the Vyatka State University majoring in 06.03.01 Biology took part in the study, covering 2023–2024. Mathematical content is selected according to the Computational Thinking in Mathematics and Science Practices Taxonomy by Weintrop et al. The main method for measuring computational thinking, presented by the Computational Thinking Scales (CTS), was supplemented with case studies reflecting the mathematical foundations of epidemiology. Statistical analysis of the obtained results was performed using the Mann-Whitney U test. conditions and formulated mathematical topics. KEYWORDS Results. It is substantiated that problem-oriented, research and project-based learning, group forms of work make it possible to significantly combine the process of teaching mathematics at a university with the development of students’ computational thinking. Almost all branches of higher mathematics have educational and applied potential for such development. To implement it, it is advisable to combine the study of mathematical topics with the solution of real problems in which computational skills are formed, while computational thinking itself can act as a means and goal of modern mathematical education for students in the natural sciences. A quantitative analysis confirmed the significance of the differences (Uemp = 5 < Ucr = 6; р < 0,01), which indicates the effectiveness of the intervention based on the proposed pedagogical Conclusion. The practical significance of the study is determined by the possibilities of using its results in improving the computational thinking skills of students in the process of teaching mathematics.