Developing Demonstrated Intercultural Communicative Competence through GenAI-Supported Sociolinguistics Instruction

Generative AI (GenAI) offers opportunities for contextualised and reflective language learning, yet its contribution to demonstrated intercultural communicative competence (ICC) remains underexplored, particularly in language teacher education in Indonesia. This study examined changes in Indonesian pre-service language teachers’ demonstrated ICC following GenAI-supported Sociolinguistics instruction, compared posttest performance with conventional instruction after baseline adjustment, and explored learning processes associated with different performance gains. An explanatory sequential mixed-methods design involved 100 students from two intact classes, with 50 students in each instructional condition. Demonstrated ICC was assessed using an adapted Performance-Based Intercultural Situational Judgment and Response Test covering sociocultural knowledge, cultural awareness and perspective-taking, observable intercultural stance, and interactional and mediation skills. Qualitative data were obtained from interaction logs, initial and revised responses, reflection sheets, and stimulated-recall interviews with 15 experimental-group students. Paired-samples t-tests, ANCOVA, and deductive–inductive thematic analysis were employed. The experimental group showed a mean overall gain of 14.72 points (dz = 1.21). After controlling for pretest scores and assessment-form order, its adjusted posttest score was 8.72 points higher than that of the control group (partial η² = .121). High-gain participants showed more critical evaluation, perspective-taking, substantive revision, and transferable reflection, whereas low-gain participants more often relied on direct acceptance and surface-level revision. These findings indicate that structured GenAI-supported Sociolinguistics activities were associated with stronger demonstrated ICC within the two classes examined.