Currently, the active use of artificial intelligence has also affected the process of conducting physics lessons. Mastering the physics requires an understanding of abstract concepts and an understanding of the complex laws of nature through imagination. Having reviewed domestic and foreign studies on the topic "Methods of teaching physics", we came to the conclusion that the problems in teaching physics are relevant all countries. For example, the author of the study (Dian Toar Y. G. Sumakula, 2022) identifies two main reasons why physics seems to be an abstract science. First, many objects of the study in physics are inaccessible to direct observation. Concept such as atom, energy levels, force, and others make physics incomprehensible to people who are far from this science. Secondly, terminology in physics often has a specific meaning, different from everyday use. For example, the concept of "work" in physics means the product of force and displacement, and for many students it may be difficult to understand why, if you apply force, the body does not move, and work is not done. That is, the abstract and mathematical nature of physics complicates the perception of the subject and reduces the interest of students in it. To solve these problems, it is necessary to introduce new methods and technologies, increase the number of practical classes and improve the quality of educational materials - this opinion is shared by physicists all over the world. One of the promising directions is the use of artificial intelligence. A number of teachers who have successfully tested these technologies are already using them in their practice. For example, Alain John, a professor of physics at the University of Texas in the USA, equipped a classroom in mechanics, integrating into it a simulation based on the PhET Colorado platform. According to Professor John, the demonstration of the laws of motion with the help of simulations during physics lessons, as well as conducting virtual laboratory work, had a positive effect on the students' conceptual understanding of physical laws. Our research team conducted a survey among 10th grade students. The results of the survey confirmed that our teaching practice has similar problems: 40% of the 24 students surveyed indicated difficulties in understanding physical phenomena, applying formulas to solve problems, and establishing connections between theory and practice. When asked in the survey about the most effective tools for mastering new topics, 60% of students spoke in favor of increasing the number of demonstrations in lessons.

the aim of our study as: to investigate the influence of the use of artificial intelligence on the formation of students' conceptual understanding of physical phenomena.

Our research questions:

1. What impact does the use of animations based on PhET simulations have on students' ability to understand and represent the relationships between objects in 3D space?

2. How do assignments based on PhET animations and virtual labs affect students' learning?

3. What impact does the PhET web-based simulation platform have on students' satisfaction with their learning after interacting with it?

The study was conducted at the Nazarbayev Intellectual School of Chemistry and Biology in Almaty. The experiment involved two tenth grade classes, each with 12 students. One class was defined as the experimental group, and the other as the control group. The experimental group was selected randomly. Variables In the study, the independent varible was the teaching method , for control group the teacher use presentations and traditional tasks were used and for experimental group use PhET virtual lab demonstrations. Interactive models available on the PhET platform (https://phet.colorado.edu/) were used to conduct the experiment. These models allowed visualization and exploration of various physical phenomena, which made the learning process more visual and interesting. The dependent variables were the students’ conceptual understanding of the electric field lines, the superposition principle, direct current, series and parallel connections, and Kirchhoff's rules. The second dependent variables were the students’ attitude towards physics using virtual lab.

1.The results of the experiment indicate a deeper understanding of the concept of electric field lines by the students in the experimental group, which is confirmed by their creation of a three-dimensional model. The result of this task: in the experimental group, 70% of students were able to complete the task correctly, while in the control group only 30%. This suggests that when explaining a physical phenomenon, it is not enough to just verbally describe the phenomenon or show an image in a presentation; it is more effective to show a model of the phenomenon in space and its movement, which contributes to a deeper understanding of the material being studied. 2.two different lesson plans were developed on the topics “The principle of electric field superposition”, “Direct electric current”, “Series and parallel connections”, “Kirchhoff’s rules”. In the experimental group, tasks were based on PhET Colorado simulations, while in the control group, presentations and traditional tasks were used. To quantify changes in students’ cognitive abilities and knowledge after the experiment, test tasks created in the Plickers application were used. Statistical methods such as mode, median and Achievement percentage were used to analyze the test results. 3.In response to the open-ended question “What are the benefits of PhET simulations in learning new material?”, the experimental group students most often indicated the following aspects: understanding the flow of various processes, visualization of tasks and laboratory methods, and a deeper understanding of the processes in the studied chain. The results obtained during the survey confirm that the use of PhET simulations in teaching contributed to an improvement in the quality of knowledge of the experimental group students.

Dian Toar Y. G. Sumakula, Fuad Abdul Hamiedb & Didi Sukyadic.( January – June 2022). Ilkka, T. (2018). The impact of artificial intelligence on learning, teaching, and education. European Union. Language Education and Acquisition Research Network. LEARN Journal. Volume: 15, No: 1 McCarthy, J. (2007). What is artificial intelligence. Ukoh, E. E., & Nicholas, J. (2022). AI adoption for teaching and learning of physics. International Journal for Infonomics (IJI), 15(1), 2121-2131. Zhumataeva, Z. N., Mametkarim, Zh. M., & Dosanova, A. M. (2024). THE THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE FORMATION OF COMMUNICATIVE COMPETENCE IN FOREIGN LANGUAGE LESSONS. «Вестник НАН РК», 412(6), 119-130.