AI-Powered International Marketing Education Reform: A Conceptual Framework of Intelligent Recommendation, Assessment, and Immersive Experimentation

Abstract

This study conducts a systematic analysis of the pathways and effectiveness of applying artificial intelligence (AI) to the teaching of International Marketing courses, in response to the growing trend of digitalization and internationalization in education. Based on a teaching reform project at Liaoning University of Science and Technology, the research adopts a case-driven and modular design approach to construct a triadic teaching model integrating intelligent recommendation, AI-driven assessment, and immersive simulation. This model is expected to address common issues in traditional instruction, such as fragmented content, low student engagement, and delayed feedback, while enhancing personalization, interactivity, and practical relevance in teaching. The study offers a replicable framework for integrating AI technologies into business education and provides theoretical support and practical strategies for advancing intelligent curriculum reform in Chinese universities.