Structural model of pre-service teacher training based on artificial intelligence technologies

Introduction. Modern artificial intelligence (AI) tools have significant didactic potential, allowing to transfer the learning process to a higher level in terms of solving cognitive tasks. At the same time, the degree and scope of AI implementation in the educational process will largely depend on the ability of teachers to integrate AI tools into the traditional process of teaching disciplines. Natural use of AI in pre-service teacher education programs is possible, on the one hand, by integrating AI into the practice of teaching students specialized disciplines, practical and research work at the university, and on the other hand, by developing students' competence in the field of teaching methods based on AI. The purpose of the study is to develop a structural model of pre-service teacher training based on AI technologies. Materials and methods. The following research methods were applied in the study: analysis of pedagogical and methodological literature on the integration of AI into education in general and teacher training in particular, a students’ survey on their experience in using AI while studying at the university. The materials used included academic papers (Articles and Reviews) from scientific journals indexed in the Web of Science (Core Collection) and Scopus (Q1, Q2). An online survey was conducted to determine in which disciplines and within which types of activities students currently use AI. The participants were 2nd–4th years students (N=245) enrolled in teacher training program at Derzhavin Tambov State University (Russian Federation). KEYWORDS Research results. A structural model of pre-service teacher training based on AI technologies has been developed. It includes five blocks: a) specialized disciplines; b) methodological disciplines; c) psychological and pedagogical disciplines and “Digital department” courses; d) internship at school; e) research. Within a specific discipline of each block, certain AI tools are used to solve educational and research goals. The survey showed the degree of total vs. authorized use of AI by students in the educational process: 73.4% vs. 19.6% of respondents, respectively, use AI tools in the study of specialized disciplines, 22.3% vs. 22.3% – when studying methodological disciplines, 7.5% vs. 0.4% – when studying psychology and pedagogy, 15.2% vs. 15.2% – during internship at schools and 89.4% vs. 4.2% – in research. The level of authorized use of AI in the educational process was very low. Conclusion. The novelty of the study is in the development of a universal structural model of pre-service teacher training based on AI technologies. It can serve as a basis for the development of particular models of pre-service teacher training with one or several training profiles in pedagogical universities.