Interactive Methods of Teaching Foreign Languages in Technical Higher Education Institutions
Year: 2026
Type: article
Abstract: The aim of the article is to study the theoretical and methodological foundations and empirical substantiation of the feasibility of introducing interactive methods and artificial intelligence tools into the process of teaching foreign languages in technical institutions of higher education, as well as to develop a structural and functional model of their integration into the professionally oriented training of future engineers. Methods: a complex of theoretical (systemic, comparative, content analysis of scientific sources) and empirical methods was applied – analysis of official Eurostat statistical data, OECD and UNESCO reports; calculation of the aggregate index of digital-AI-educational activity; correlation analysis of the relationship between the level of digital competence and academic success; pedagogical modeling. Participants in the empirical study were not involved, since the work is based on the analysis of open statistical data and theoretical modeling. Data collection was carried out through a systematic review of scientific publications (from the Web of Science / Scopus databases) and official statistical products of Eurostat and OECD for the period 2022–2026. Data analysis was performed using thematic coding, comparative analysis, correlation analysis (Pearson coefficient) and structural-functional modeling. As a result, a stable positive dynamics of the use of online learning and generative AI by young people in EU countries was revealed (growth by 5.5 pp for 2022–2024), a direct correlation between the level of education and digital skills was confirmed (correlation coefficient with success r=0.67–0.71). A structural-functional model of the implementation of interactive methods in technical higher education was developed, which covers target, content, procedural, technological and assessment components, ensuring the integration of linguistic, professional and digital competencies.
Institution: Lutsk National Technical University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7219246768