Kabzhalelov K.R., Akkazin E.A., Sarsekova K.A.
THE POTENTIAL OF ARTIFICIAL INTELLIGENCE AS AN AUXILIARY TOOL IN TEACHING CHEMISTRY *
Аннотация:
in modern education, artificial intelligence (AI) is becoming an important tool that can improve the effectiveness of learning. This article discusses various ways of using AI and chatbots based on neural networks in teaching chemistry at school. An analysis of the literature on this topic is conducted, and examples of practical implementation are presented: programming useful code in Python using ChatGPT, introducing elements of green chemistry through interactive simulations and modifying standard tasks with an ecological context. The advantages and limitations of neural networks in chemistry education are considered.
Ключевые слова:
artificial intelligence, chemistry education, green chemistry elements, ChatGPT, chatbots, python
DOI 10.24412/2712-8849-2025-283-226-232
Introduction. In modern realities, artificial intelligence (AI) is exerting an increasing influence on many areas of human activity. Artificial intelligence is "a computer model of human intellectual capabilities in targeted search, analysis and synthesis of current information about the surrounding reality in order to obtain new knowledge about it and solve various vital problems on this basis" [1, p. 9]. The creation of neural networks is a response to existing problems in the world society, while this technology itself causes a huge amount of discussion. A.V. Ostroukh in his monograph emphasizes that a distinctive feature of intelligent information systems (representatives of which today can be called: many neural networks and chat bots) is the solution of complex and poorly formalized problems [1, p. 11]. Of course, this type of phenomena that are not subject to formalization includes the field of education. Part of the developments in the field of AI are Large Language Models (LLM). This type of technology can process and analyze a huge amount of natural language. This article presents various ways of using AI elements and chatbots based on it in teaching chemistry at school. An analysis of the literature on the topic is conducted, and examples of the implementation of green chemistry elements and studies using ChatGPT are demonstrated. The importance of such studies lies in the gradual development of a new direction of artificial intelligence in the chemical educational process. Other ways of using neural networks as an auxiliary tool to help the teacher are also presented (modification of tasks in a contextual manner and useful programs in Python).Research methods: study of methodological literature on the research problem. Analysis, synthesis and comparison of the obtained data. «Prompt engineering» ChatGPT (4.0 mini).Results and discussion. After the presentation of ChatGPT, a huge number of AI-based tools with various functionality emerged. This technology aroused the interest of workers in the field of education almost immediately. Many works were carried out to evaluate the capabilities of such chatbots as: ChatGPT, Bing AI, Bard, Gemini in the field of natural sciences [2, 3]. According to the results obtained, chatbots still make mistakes and even blunders. This is especially true for the subjects: chemistry, biology and physics, while in the humanities, chatbots always show good results [4]. In the case of chemistry, neural networks are not able to solve critical thinking problems, or difficult problems in several steps. However, such results do not mean that AI cannot become a useful tool in teaching chemistry. For example, in a review article [5], the authors analyzed English-language articles from 2018-2024 related to the use of artificial intelligence and / or machine learning in chemistry education. According to their findings, the integration of these technologies can lead to: improved personalized learning, easier lesson planning for teachers and a reduction in routine work, increased availability of educational materials. It is also worth noting that at the moment, most of the articles are devoted to the implementation of AI tools in higher education (61.60%), while for secondary school this figure is (38.40%). Another interesting indicator that the authors cited in the article reveals how effectively research is carried out on the impact of neural networks in education among developed, developing and underdeveloped countries. Unfortunately, underdeveloped countries account for only 12.12% of publications, while developed countries account for 61.61%. Summarizing their work, the authors noted: «the integration of artificial intelligence and machine learning in chemistry education requires the collective efforts of researchers, teachers (practitioners) and other stakeholders. At the same time, courses are already needed that will prepare future specialists to work with AI tools».The direct “abilities” of ChatGPT in chemistry were highlighted in the work of Daher et al. [6]. The authors tried to assess the difficulties of conceptual understanding of ChatGPT. A set of thirty chemistry problems in the area of “Introduction to Materials Science” were presented. The results showed that ChatGPT faced significant difficulties in conceptual knowledge in various categories. Also, the neural network could not always explain its solution correctly, allowing for a basic misunderstanding of the main rules and difficulties in interpreting the chemical language.Nguyen [7] notes the limitations and potential of using ChatGPT as a tool for improving chemistry education. Three main obstacles that currently exist in the application of this technology are: lack of deep understanding of chemical concepts, inability to interpret and respond to visual information, insufficient trained data in the field of chemistry on which the machine training of this neural network was carried out.Thus, AI and modern chatbots leave behind a lot of discussion in the field of their application in education. However, it is impossible to ignore such a strong phenomenon as artificial intelligence. This work presents three directions in which AI can be used in chemistry education at school. The first is the use of ChatGPT for programming useful code in Python. The second is the introduction of green chemistry elements using the simulation «Ammonia production and Le Chatalliers principle», as well as modified standard chemistry tasks with the introduction of the ecological aspect. The python language and code generation using ChatGPT is justified by the simplicity of this programming language, and the fact that this chatbot is able to effectively generate code in this language. There are already works that show the convenience of using python to create small programs when solving problems in chemistry [8, 9] and the importance of this language in science [10].To demonstrate how to use ChatGPT to create useful Python code, here are two working programs: https://colab.research.google.com/drive/1JBAfd-blINoAC1fz4rgFRXdAJpoxBGhM, https://colab.research.google.com/drive/1JH_g3VcOfmisFG8EXmWFEnc_giewQ8x. In the first code, the user can plot graphs based on the results of an experiment or other data. He can select the function type (sin, cos, exp, custom) and then get a graph. It is also possible to sign the graph axes and its name. The second code helps to quickly calculate the pH of acid and base solutions based on a known concentration. The user has the option to select strong or weak (acids and bases) he needs for the calculation. Such small programs are standard examples of how you can create lightweight code using a neural network to facilitate routine tasks in chemistry. Thus, artificial intelligence can benefit both teachers and workers in the scientific field of chemistry in their daily professional activities.ChatGPT is a universal assistant for creating program codes. Therefore, this tool is especially useful for teachers who do not have programming skills, but want to create their own simple simulations for interactive learning. Therefore, as an example, a program code was developed – a Python-based simulation on the topic of «Ammonia Production» using ChatGPT. The functionality of this simulation is shown in figure 1. The program code is freely available at the link: https://colab.research.google.com/drive/1zFBkvQIK1qXVbd6y9bJsE-nqDVq9qRGe.Figure 1. Simulation on the topic "Ammonia production".In this simulation, students must find the best conditions for ammonia synthesis (optimal temperatures and pressures) according to Le Chateliers principle. Students can move widgets and see the product yield as a percentage on the graphs. To introduce elements of green chemistry, a second graph was added to the simulation – a change in the carbon footprint depending on the increase in temperature. With this addition, students must come to an important conclusion: an increase in temperature not only begins to reduce the yield of ammonia, but also increases energy costs, which in turn increases the carbon footprint. The second addition is that when students begin to increase the pressure too much, two warnings are displayed on the screen. The first (after 500 atm): «High pressure, too expensive equipment to support the process.» The second (after 1000 atm): «Too high pressure, an accident at work.» Thus, students should come to another important conclusion: despite the fact that with increasing pressure the ammonia yield always increases, this indicator in a real process cannot be exceeded above reasonable limits due to the danger of production and rapid wear of equipment. Thus, students learn not only the chemistry of ammonia production, the Le Chatalier principle, but also gain an understanding that any production has its own characteristics and should strive for optimal conditions. And today this is a combination of optimal conditions with the principles of green chemistry.ChatGPT can be used to modify standard chemistry calculation problems. One example is shown in table 1.Table 1. Modification of standard calculation problems in chemistry.Conclusions. This article demonstrated three practical applications of AI in chemistry education: Python-based programming for automating calculations and visualizing data, simulations incorporating green chemistry principles, and the contextual modification of chemistry problems to enhance environmental awareness. These examples illustrate how AI can support both teachers and students, making chemistry more interactive, engaging, and aligned with modern scientific and environmental challenges.
Номер журнала Вестник науки №2 (83) том 3
Ссылка для цитирования:
Kabzhalelov K.R., Akkazin E.A., Sarsekova K.A. THE POTENTIAL OF ARTIFICIAL INTELLIGENCE AS AN AUXILIARY TOOL IN TEACHING CHEMISTRY // Вестник науки №2 (83) том 3. С. 226 - 232. 2025 г. ISSN 2712-8849 // Электронный ресурс: https://www.вестник-науки.рф/article/21496 (дата обращения: 13.12.2025 г.)
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