METHODS OF MODELING PHYSICAL PROCESSES IN MATHCAD

2025

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DOI 10.58805/kazutb.v.4.29-1190
Data confidence 70 medium
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Abstract

In the context of modern educational realities, characterized by strict criteria for assessing students' knowledge, high academic workload, reduced hours of study, as well as outdated and insufficient equipment, the problem of improving the quality of education is becoming particularly acute. In this regard, the training of specialists within the framework of the credit education system highlights the need to develop new conceptual approaches to the organization of educational and methodological activities and the active introduction of modern information and communication technologies into the educational process. This implies the widespread use of information technology and personal computers for modelling a variety of physical phenomena, both in the framework of training and in the implementation of ongoing knowledge control. This paper demonstrates that the use of modern applied software packages in the educational process can significantly transform the methodology of studying certain sections of the physics course, providing visual visualization of the results of solving problems using these applied tools. For a clearer demonstration of physical phenomena, this article presents modelling of complex systems described by second-order differential equations using the MathCad software environment. Using the odesolve function built into Mathcad, a graph of the addition of two harmonic oscillations was obtained. The method of solving differential equations presented in this paper can be used to model various other physical processes considered in the physics course. The main purpose of this work is to master the methods of modelling non-stationary physical processes in the Mathcad environment using the odesolve function, using the example of oscillatory movements. In addition, the article highlights the importance of using physical models in the educational process. This allows not only to visualize complex processes, but also contributes to a deeper understanding of the principles underlying physical phenomena.