Peer Learning Through stace-Taking: How Students Engage with AI-Generated Images in Intercultural Virtual Exchanges

The increasing use of artificial intelligence (AI) raises questions about how future professionals engage with AI-generated content, which may reproduce stereotypes and cultural biases. This study examines how university students in virtual exchanges engage with AI-generated images, offering an interactional perspective on peer learning, which is achieved by deploying practices through which students negotiate interpretations and take stances as part of intercultural competence. Drawing on video-recorded interactions from six student groups participating in two international virtual exchanges involving universities in Austria, Czechia, and Finland, the study analyzes how students collaboratively produce assessments, epistemic accounts, and (dis)align with their peers, taking stances toward AI-generated visual content depicting everyday situations in their university cities. The analysis demonstrates how students reject or problematize AI-generated representations by treating them as laughable and ridiculing them, or by producing downgraded assessments and detailed epistemic accounts. The detailed description of these interactional practices contributes to the emerging body of research that calls for critical engagement with AI-generated content and highlights how peer learning in the area of intercultural competence unfolds through stance-taking in virtual exchanges.