AI-enhanced communicative-situational technologies for developing linguocultural competence in pre-service language teachers

Bibigul B. Utegaliyeva, Galiya Kismetova, Кльжиян Мендыгалиевна Шунайбекова, Saule Kadirgaliyeva, Astra Gabdesheva, Berik Matayev

Frontiers in Education, 2026

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3389/feduc.2026.1910005
Data confidence 70 medium
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Abstract

The increasing internationalization of higher education and the growing cultural diversity of educational environments have highlighted the need to develop linguocultural competence among future language teachers. This study aimed to design, implement, and evaluate an AI-enhanced communicative-situational model for developing linguocultural competence among pre-service language teachers. A quasi-experimental pre-test/post-test design was employed with 280 undergraduate students enrolled in a Foreign Language Teacher Education programme. Participants were assigned to an experimental group ( n = 140) and a control group ( n = 140). The experimental group participated in a 12-week intervention integrating communicative-situational technologies and ChatGPT-5. The control group received traditional foreign language instruction based on reading comprehension, vocabulary and grammar practice, textbook-based discussions, and teacher-centered learning activities. Linguocultural competence was assessed through a rubric-based instrument measuring Cognitive-Conceptual, Pragmatic-Communicative, and Professional Cross-Cultural Competence. Data were analyzed using descriptive statistics, t-tests, mixed-design ANOVA, and Pearson correlation analysis. The findings revealed significant improvements across all dimensions of linguocultural competence, with the experimental group demonstrating substantially greater gains than the control group. Significant Time × Group interaction effects were found for Cognitive-Conceptual Competence, F(1,278) = 40.72, p < .001, η 2 p = .128, Pragmatic-Communicative Competence, F(1,278) = 24.86, p < .001, η 2 p = .082, and Professional Cross-Cultural Competence, F(1,278) = 19.41, p < .001, η 2 p = .065. Strong positive correlations were identified among all competence dimensions (r = .630–.786, p < .001). The results suggest that AI-enhanced communicative-situational technologies effectively support the development of linguocultural competence by fostering authentic intercultural communication, reflection, and professional decision-making. The proposed model offers practical implications for teacher education in multilingual and multicultural contexts.