AI; International Trade Practice; Teaching reform; Interdisciplinary teaching
人工智能; 国际贸易实务; 教学改革; 跨学科教学
Abstract:
International Trade Practice, characterized by its practical and interdisciplinary nature, has long faced dilemmas such as scarce authentic cases, students’ weak legal foundations, limited practical training conditions, and teachers’ narrow professional backgrounds. Against the backdrop of artificial intelligence (AI) being widely integrated into higher education, this paper explores AI-driven teaching reform paths based on the course’s characteristics. Three implementation paths are put forward in the study : using AI to assist in compensatory legal teaching for pre-class knowledge preparation; leveraging large language models to generate high-fidelity cases for task-based teaching; and constructing virtual simulation environments for practical process training and precision assessment based on process data. Meanwhile, the collaborative implementation of these three schemes and the transformation of teachers’ roles are discussed. The aim is to provide references for improving the quality of International Trade Practice courses in the AI era and for the teaching reform of similar practical courses.
“国际贸易实务”兼具实务型与跨学科属性,传统教学长期面临真实案例来源匮乏、学生法律基础薄弱、实践教学条件受限及教师专业背景单一等困境。在人工智能广泛融入高等教育的背景下,本文基于该课程特点,探讨人工智能驱动的教学改革路径。研究提出三条实施路径:以人工智能辅助法学补偿性教学,实现课前知识预置;依托大语言模型生成高仿真案例,开展任务式教学;借助虚拟仿真系统构建实务流程模拟环境,并基于过程数据实现精准评价。同时,本文讨论了三类方案协同实施的教学闭环与教师角色转型问题,旨在为人工智能时代“国际贸易实务”课程质量提升及类似课程的教学改革提供实践参考。