Pedagogical interaction as “polylogue” of meaning perspectives: revisiting the problem of personal agency in dealing with intelligent systems

Importance. In the context of the new educational reality mediated by artificial intelligence tools, the key pedagogical category, that of pedagogical interaction, proves to be less and less in demand as focus of research, which makes it difficult to consider current educational practices and develop theory, particularly in fields connected with language, meaning-making, and verbal communication. The article aims to consider the specific features of modern educational process, pedagogical interaction in particular, mediated by artificial intelligence (AI) tools.

Materials and Methods. The research methods embrace a complex of instruments, namely: analysis of pedagogical science discourse, products of teaching and learning activities; comparison, synthesis, systematization, and interpretation of data obtained; monitoring the educational process, survey of participants in the pilot research, expert evaluation of the analysis results.

Results and Discussion. The study contributed to determining the functional capacity of the main agents of the AI-mediated educational process and discovering problem areas of pedagogical interaction as a meaning-making factor. Agency potentials in AI-mediated meaning-making interaction were assessed, with the theoretical findings checked in pilot teaching aimed at testing a “polylogue” of meaning perspectives scenario as meaning-making interaction. Two stable indicators were established: the number of participants who prefer the AI-mediated format of FL learning and believe AI can completely replace a FL professor at a university (20 %), and the number of those who exclude this possibility for themselves (36 %). The group of participants who initially could not make their choice (44 %) decreased by 24 % (to 20 %) during the pilot training – due to an increase in the number of those who do not consider the format of interaction with AI to be preferable for themselves.

Conclusion. Pedagogical “risks” for agents of AI-mediated meaning-making interaction are grouped around such areas as data unreliability, content bias in AI-generated products, and devaluation of pedagogical meanings. At the same time, the results of the study show that language pedagogy has a unique potential in producing multi-agent meaning-making interaction in the scope of AI, encouraging the “polylogue” of meaning perspectives, integrating and multiplying socially and personally relevant meanings on a broad interdisciplinary basis, which may be the focus of further research.