ALGORITHMS OF HUMAN-MACHINE INTERACTION WITH CHATGPT FOR SOLVING APPLIED TASKS IN THE EDUCATIONAL PROCESS
DOI:
https://doi.org/10.31110/2616-650X-vol14i1-004Keywords:
intelligent system; prompt; information noise; user roleAbstract
The article examines the specifics of human–machine interaction with intelligent chatbots, particularly ChatGPT, in the process of solving applied educational tasks. Based on the analysis of recent studies, it is shown that despite the significant potential of generative artificial intelligence, the scientific literature still lacks algorithms capable of supporting a structured, adaptive, and pedagogically grounded dialogue between a teacher, a student, and an intelligent system. The key challenges are identified, including incorrect interpretation of logical components in task conditions, misunderstanding of user intentions, dependence on the quality of the prompt, and imbalance between the educational goal and the generated responses. It is demonstrated that the effectiveness of interaction depends on accurately defining the user’s role, building a clear prompt structure, and ensuring that both the system and the human user maintain a consistent intellectual model of the task.
A methodological approach to developing human–machine interaction algorithms is proposed. It includes dividing the prompt into meaningful blocks, filtering secondary information, clarifying the user’s intention, and forming a learning sequence structured as “condition – analysis – calculation – explanation.” Using a simple mathematical problem as an example, the article shows how changes in the user’s role and the interaction algorithm lead to different ways of forming the final answer. It is demonstrated that ChatGPT performs several cognitively oriented operations, such as analysis, semantic structuring, and logical transformation. However, the quality of the result fully depends on a properly organised dialogue that considers the roles of teacher-user and student-user.
The findings have practical value for education: they help develop students’ skills in structuring information, critically analysing problem statements, and consciously managing digital tools. The article justifies the prospects for creating a specialised application that would automate teacher interaction with ChatGPT when preparing learning tasks, tests, and instructional materials, ensuring adaptation of the content to the user’s role and the student’s level of preparation.
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