Use of artificial intelligence to improve distance learning methods in technical institutions of Ukraine

Abstract

In distance learning of technical specialities, the need for tools capable of maintaining the stability of the educational process and providing operational data analysis is becoming increasingly acute. In this context, the use of artificial intelligence enables improved interaction between teachers and students, optimised educational materials, and enhanced evaluation quality. Given the growth of digital resources and the complexity of technical disciplines, the use of intelligent solutions is an essential factor for effectively supporting educational activities and enhancing the effectiveness of specialist training. The purpose of the article is to justify the feasibility of using AI technologies for remote training of applicants for technical specialities and to determine directions for their practical use to increase the effectiveness of training. Methods. The research uses methods of structural analysis, modelling of educational processes, content analysis of the functionality of modern digital platforms, expert evaluation of the effectiveness of intelligent services, and the generalisation of data on their use in the activities of technical educational institutions. Results. It was found that integrating machine learning algorithms, chat support systems, and intelligent analytics increases the accuracy of didactic solutions, improves the structuring of educational materials, and enables more flexible assignment of individual tasks. The results show that the use of intelligent recommender mechanisms contributes to faster development of professional skills, increased motivation, and reduced typical student errors when working on complex technical topics. Experimental data demonstrate increased student success and activity, as well as improved communication in an electronic learning environment. Conclusions. Artificial intelligence technologies can be a key element in modernising distance training in technical educational institutions. Their use ensures the adaptability of educational trajectories, supports teacher decision-making, enhances the quality of digital resources, and lays the groundwork for the further development of the innovative infrastructure of technical education.