Keyword: «professional development of teachers»

The article discusses a model of advanced training of teachers in a secondary vocational education institution based on a system-process approach. From the standpoint of a systems approach, the management model includes: system-forming factors (goals, performance results); functioning conditions (social and pedagogical, temporary); structural and functional components (departments and subdivisions of a medical college, managing and controlled subsystems of the educational process).

The relevance of the study is due to the rapid introduction of artificial intelligence (AI) technologies in the educational sphere. At the same time, the issue of using AI in rural schools remains insufficiently studied. This problem is of particular importance in the context of the Republic of Sakha (Yakutia), where geographical remoteness and digital inequality create additional barriers to technological modernization of education. The issue of rural teachers' readiness to use these technologies remains unresolved despite the recognized potential of AI for personalizing learning and automating routine tasks. The aim of the study is to identify the level of readiness of teachers in rural schools of the Republic of Sakha (Yakutia) to use AI technologies in their professional activities. The work uses a combination of methods: analysis of theoretical sources, a survey of 345 teachers from 52 rural schools, testing the level of knowledge about neural networks, as well as methods of mathematical statistics for data processing. The main results of the study revealed a contradictory situation: 78% of teachers do not use AI in their work, while 36% express their interest in courses on neural networks. The survey results show a split in opinion about the usefulness of AI, with 47% in favor and 53% opposed. Additionally, there is a cautious attitude towards its use by students (40% strongly against). At the same time, teachers see the practical benefits of AI for drawing up lesson plans (32%), creating assignments (27%) and assessing (18%). Testing revealed a knowledge deficit: 89% of teachers are not familiar enough with neural network technologies. Based on the data obtained, a four-module advanced training program was developed, including: 1) AI basics, 2) application for lesson preparation, 3) assessment tools, 4) professional development of teachers. The program is implemented remotely with a practice-oriented approach and provides for the creation of a bank of methodological recommendations. The theoretical significance of the work lies in the systematization of knowledge about the capabilities and limitations of AI use in rural schools, as well as in the development of conceptual approaches to teacher training. The practical value of the study is manifested in the creation of an adapted advanced training program that can be adapted and expanded to other regions, taking into account local specifics. Prospects for further research include monitoring the effectiveness of the program implementation, studying the long-term impact of AI on the quality of education, and developing methodological recommendations for the use of AI technologies in the teaching practice of rural teachers.