AI Empowered Innovation in Cross-Cultural Education in Universities Construction of a Multimodal Data-Driven Cultural Comparison Teaching System and Research on its International Communication Effectiveness
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Abstract
Under the dual drive of globalization and digital education strategies, cross-cultural education in universities is shifting toward integrated cultivation of knowledge construction and international communication ability. To address problems such as single cultural samples, insufficient interaction, neglected individual differences, vague effectiveness evaluation, and weak international communication outcomes, this study integrates artificial intelligence, multimodal data perception, and cultural comparison teaching to construct an AI-empowered cross-cultural education system. The system includes a cultural knowledge graph module, multimodal emotion and behavior perception module, adaptive learning path module, cross-cultural scenario simulation and dialogue module, and international communication effectiveness evaluation module. It forms a closed-loop process of precise perception, adaptive teaching, immersive simulation, and quantitative evaluation. Empirical results show that the system improves students’ comprehensive international communication effectiveness score by 28.3% and increases teaching satisfaction by 32.7%. The study provides a replicable framework for cross-cultural education reform and supports the transformation from teaching cultivation to communication competence generation.
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