Antonina А. Andreeva

The article addresses a methodological problem related to the use of generative artificial intelligence (GAI) in the system of continuing professional education (CPE), which has become particularly acute under conditions of hybrid learning and in the context of foreign language teaching. The expansion of GAI-based practices in education is accompanied by growing methodological fragmentation, when digital tools are applied without reliance on a coherent logic of pedagogical design. As a result, GAI is used primarily as a means of generating instructional content, leading to the substitution of pedagogical thinking with technical operations and to a loss of coherence in learning activities. The aim of the study is to develop and empirically validate a model of pedagogical task design involving GAI that ensures alignment between educational goals, learning actions, and learning outcomes within CPE. The methodological framework of the study is based on systemic and activity-based approaches, principles of andragogy, and UNESCO framework documents on AI competences for teachers and learners. The empirical basis includes data from pre- and post-course surveys of foreign language teachers, as well as a content analysis of instructional tasks developed by participants during an author-designed professional development program implemented in a hybrid format. The analysis revealed persistent methodological contradictions in the integration of GAI and substantiated the need for a structural model of pedagogical design. As a result, the CROPS model (Concept of the goal, Resource, Operation, Proof, Scenario) is proposed as a reproducible structure for designing learning tasks with the involvement of generative AI. The findings demonstrate that the application of the model reduces methodological fragmentation, restores the pedagogical logic of learning activities, and preserves the teacher’s subject role in an AI-enriched educational environment. The theoretical significance of the study lies in clarifying the role of structural pedagogical design models under conditions of digital transformation in CPE. The practical significance is determined by the applicability of the CROPS model in professional development and professionally oriented training programs, including hybrid and online formats.

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.