Efrosinya A. Alekseeva

The importance of digital literacy research stems from the rapid digital transformation of all aspects of life, requiring individuals not only to possess technical skills but also the ability to critically analyze information, adhere to ethical standards, and adjust to constantly evolving technologies. In the context of globalization and increasing volume of digital data, the development of digital literacy becomes the basis for successful socialization and professional agency. However, the lack of a unified approach to the definition and structure of digital literacy complicates the development of effective pedagogical strategies and methods for its assessment, which makes the systematization of existing concepts an important scientific and practical task. The aim of the article is to analyze existing approaches to defining digital literacy, identifying its structural components and levels of development, as well as substantiating its role as a basis for the development of digital competency. The leading approaches to the study of the problem are theoretical analysis of scientific concepts, a comparative method for identifying common and distinctive features in the structure of digital literacy, as well as a structural and functional approach in identifying its key components. The main results of the study include the author's original definition of digital literacy as an integrative dynamic quality of the individual, revealed as a high level of motivation, readiness and ability to effectively and responsibly use digital technologies to work with information, communicate and solve problems in professional and everyday life based on the acquired knowledge and the ability to determine the achieved level based on reflection. Based on the analysis of domestic and foreign studies, a structure of digital literacy is proposed, consisting of five interrelated components: motivational, information-cognitive, technological, communicative and reflective-evaluative. A three-level system for assessing the development of digital literacy (low, medium, high levels) has been developed, which can serve as a basis for diagnostics and further development of digital competences. The theoretical significance of the article lies in the systematization of modern approaches to understanding digital literacy and clarifying its structural components, which contributes to the development of pedagogical theory. The practical value of the study is related to the possibility of using the obtained results in developing educational programs, methods of developing digital literacy, taking into account the age and professional characteristics of a person. A promising direction for further research seems to be the adaptation of the proposed model to the regional characteristics of educational systems.

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.