Keyword: «chatgpt»

The development of artificial intelligence (AI) technologies in the educational process of a modern university is one of the most important areas for improving the university's digital educational environment. The authors propose a hypothesis about the desire of students to use AI tools in all possible cases, both in learning and scientific activities. The aim of the study is to express the opinion of students about the use of AI in educational and research activities at the university. In the course of the research, theoretical methods were used, which consisted in analysing and systematizing the provisions of domestic and foreign scientific literature on the research problem. Empirical methods were implemented in the process of conducting an online survey of students at a technical university – Ryazan State Radio Engineering University named after V. F. Utkin. The survey involved 537 respondents aged 18 to 24 years and older, 70% of them were male and 30% were female. It has been revealed that at the moment students actively use ChatGPT in their learning activities, but they do it very carefully and cautiously. There is an understanding that AI can make mistakes, convey subjectivity, bias, and inaccuracy from texts by various authors. It is concluded that the use of neural networks and AI technologies is a strategic direction for the development of the educational process in modern universities. The novelty of the research lies in the fact that, based on the analysis of scientific works by Russian and foreign authors, survey materials of students and their own experience, the authors found out: the didactic importance of more active development of analytical and critical thinking among students; the directions of their training in correct ways of interacting with AI in the educational and scientific activity; the necessity of developing digital didactics in relation to the level of higher education is substantiated. The theoretical significance lies in enriching the theory of vocational education in terms of developing a set of issues to identify students' attitudes to the use of neural networks and AI technologies and in providing the academic community with an analysis of the student survey results. The practical significance lies in the possibility of applying the research results in the process of working with university students, to develop digital didactics in order to deepen and expand the potential of using neural networks and AI technologies, to explain to students the legitimacy of using the newest technologies.

Modern continuing professional education (CPE) is undergoing active transformation under the influence of digitalization and the introduction of artificial intelligence technologies. The study of the capabilities of generative neural networks, such as ChatGPT, is of particular relevance to increase the flexibility, adaptability and personalization of the educational process. At the same time, existing studies mainly focus on higher or general education, while the specifics of CPE remain insufficiently studied. This necessitates scientific understanding of the vectors of integrating generative AI technologies into the CPE system aimed at adult learners with diverse professional contexts. The aim of this study is to identify and scientifically substantiate the key vectors of generative neural networks integration into the CPE system using ChatGPT as an example. The study is based on a combination of methodological approaches - systemic, competence-based and personality-oriented, as well as empirical data obtained from the analysis of educational practices and in-depth interviews with experts involved in the development and implementation of CPE programs. The leading research method used was qualitative analysis: content analysis, SWOT analysis and modeling. As a result of the study, five key vectors of ChatGPT integration into the practice of continuing professional education were identified: personalization and adaptive learning, automation of assessment and feedback, support for research and project-based activities, expanding the accessibility and inclusiveness of education, as well as professional development of teachers. Based on these areas, a systemic model of ChatGPT integration was proposed, including target, content, technological, organizational and pedagogical, assessment and regulatory components. The model also reflects the levels of teachers’ digital maturity in accordance with the UNESCO AI matrix (2024). The theoretical significance of the article lies in clarifying the pedagogical framework for the use of generative AI in the continuing professional education system and conceptualizing the model of its integration. The practical significance is associated with the possibility of using the developed recommendations for strategic planning, methodological support and regulation of the processes of introducing AI into the educational practice of CPE institutions.

The topicality of the article stems from the fact that the sphere of error analysis has not always been regarded as a priority in the field of language teaching, and, therefore, it has failed to receive all the attention that it deserves. The same can be said about lexical inaccuracies in the professional training of pre-service language teachers. Thus, the main aim of the article is to examine and analyze the most frequent errors in the written pedagogical speech of prospective English language teachers. Students of Lomonosov Moscow State University and Herzen State Pedagogical university completed a CELTA-style assignment designed to demonstrate their analytical, pedagogical, and professional language skills. As far as methods and materials are concerned, 78 students’ written contributions were analyzed and assessed both by a specialist in the field of ELT and two AI tools (DeepSeek and ChatGPT). The research findings led to a classification of the most frequent errors. As a result of the analysis made, several types of professionally oriented lexical errors were singled out. The latter were divided into two main categories: professional language use (lexical errors caused by a knowledge gap and the discrepancy between two different terminological systems) and teaching methods (inadequate solutions applied to the given pedagogical problems). In addition, there are several implications regarding the weaknesses of generative AI (specifically, the aforementioned neural networks). The practical findings of the study prove that greater efforts should be concentrated on developing professionally oriented lexical competence concerning the process of training pre-service language teachers. Moreover, it is argued that the use of AI technologies for evaluating students’ written assignments should be handled with extra caution and care on the part of language instructors. The theoretical significance of the study deals with the reconsideration of developing language skills in the sphere of professionally oriented vocabulary while training future language teachers. The practical significance lies in the possibility of using the results described in the article as a means of preventing errors that future language teachers are often prone to make, as well as a source of information that can be used for educational materials and course design to ensure the ongoing development of professional communicative competence of the target audience.