ABSTRACT

Purpose: To study the possibility of integrating artificial intelligence (AI) technologies in teaching the course “Workshop on solving physical problems" using neural networks in order to increase the effectiveness of the educational process. Method: The sampling methodology includes the analysis of data on the results of students' tasks collected during the workshop, using machine-learning algorithms to classify and predict the results. Methods of statistical data processing and visualization of results were used for the analysis, which allowed not only to identify key problems in learning, but also to offer recommendations for their elimination. Findings: Innovative approaches based on machine learning technologies provide flexibility in adapting course content, improving students' perception of the material and developing teachers' methodological competencies. This is especially important in the context of the increasing complexity of educational programs and the need to take into account the diversity of the level of training of students. Implications for Research and Practice: The results of the study demonstrate a significant improvement in the quality of teaching and the perception of the material by students, as well as an increase in the professional competencies of teachers. However, the methodology has limitations related to the quality of the source data and the need for a long period of technology implementation to assess its effectiveness. It is recommended to further develop data analysis technologies and train teachers to optimize the use of AI in educational processes.