Enhancing Cross-Cultural Collaboration through Real-Time AI Adaptation in Global Virtual Learning - Sheik Mohamed S H; Usman M; Hasan Hasan; Nurdianah Nurdianah (Journal of Paddisengeng Technology, 2026)
Background. Global virtual collaboration is increasingly used in higher education to develop collaborative skills and intercultural competence, but language differences, cultural norms, and technical issues can hinder effectiveness. Adaptive AI platforms with real-time cultural and linguistic support may help overcome these challenges. Purpose. This study examined the impact of AI-supported global virtual collaboration on students’ collaborative skills, engagement, project output quality, and intercultural competence among university students from Indonesia and India. Method. A total of 127 students (64 Indonesia, 63 India) were organized into 32 cross-cultural teams. Quantitative data were collected through collaboration rubrics, intercultural competence questionnaires, and platform activity logs, analyzed using descriptive statistics, t-tests, and correlation analysis. Qualitative data were gathered via interviews, observations, and project documentation, analyzed through thematic coding. novelty. This study introduces a real-time culturally and linguistically adaptive AI model integrating engagement, output quality, and intercultural competence across countries. Results. I-adaptive platforms significantly improved collaborative skills, engagement, and project quality. Indonesian students scored slightly higher than Indian students, but strategies such as manual clarifications and reflection sessions reduced gaps. Conclusion. The study provides a practical model for inclusive, adaptive international learning and highlights the complementary role of AI and human facilitation.