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The International Freight Forwarding industry has developed rapidly and this has created a widening gap between education and real-world practice. The course of International Freight Forwarding is facing three challenges: industry cases are updated too frequently, teachers are burdened by repetitive teaching preparations and resource production and large class size makes it difficult to implement personalized tutoring. The paper proposes an International Freight Forwarding teaching framework of Teacher–AI collaboration. The framework puts AI as an always-available intelligent assistant, responsible for standardized, repetitive and data-intensive tasks, while teachers as a higher-level teaching activity such as case discussions, critical thinking development, classroom interaction, ethical guidance and teaching innovation. Based on the framework, the paper designs an AI-supported teaching system and it includes four modules: the AI dynamic case generator, the AI teaching resource assistant, the AI learning analysis and personalized tutoring system, and the AI simulation training system. These modules form a continuous chain: case introduction - resource preparation - learning tracking - skill training - case update. The paper also discusses the implementation path, expected outcomes, teacher capacity building, and the broader generalizability of this model. The paper concludes the collaboration between teachers and AI can enable teachers to transform from task executors to learning facilitators and value creators, thereby enhancing the teaching efficiency and educational quality in International Freight Forwarding education.
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Xiaohui Liu (2026) studied this question.
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