Integration of artificial intelligence systems into physics laboratory practice: experience and prospects

the article considers the actual problem of integrating artificial intelligence systems into laboratory practice in physics in the higher education system. An experimental study conducted at the Department of Physics and Chemistry of Almetyevsk Technological University Higher School of Petroleum with the participation of 150 first-year students in the fields of Oil and Gas Engineering, Automation of Technological Processes and Production, Management in Technical Systems, and Software Engineering, divided into experimental and control groups, is presented. The efficiency of using the PhysicsLab AI virtual laboratory environment with an integrated machine learning module has been determined. A significant increase in the effectiveness of the educational process using AI systems has been revealed. Statistically significant results were found showing an improvement in academic performance (average score of 4.6 versus 4.1 in the control group), a reduction in work completion time (73 minutes versus 100) and a significant decrease in the number of visits to the teacher (by 56%). A high degree of student satisfaction with the new format of the workshop was determined (89% of positive reviews). The advantages of intelligent virtual laboratories are considered, including the personalization of training, the provision of instant feedback and the possibility of adaptive support during experiments. A significant increase in the quality of understanding of the material (by 34%) and the formation of practically significant skills in working with modern digital tools were revealed. A conclusion is made about the need for a systematic approach to the implementation of AI in the educational process, including both the technical equipment of educational institutions and the training of teaching staff. It is determined that the results of the study can be used in developing strategies for the digital transformation of educational institutions and the modernization of laboratory workshops in natural sciences.

artificial intelligence, laboratory practical training, physics, higher education, digital transformation, virtual laboratories, personalization of learning