基于知识图谱与AI课程的国际贸易课程智慧化教学模式探索

Exploration of an Intelligent Teaching Model for International Trade Courses Based on Knowledge Graph and AI Curriculum

摘要: 数字经济背景下，国际贸易业态持续革新，传统教学模式面临知识碎片化、供给同质化、内容滞后化及评价单一化等困境。文章以破解这些困境为目标，探索知识图谱与人工智能技术融合的国际贸易课程智慧化教学模式。首先阐述国际贸易课程知识图谱与AI课程的建设路径，以及智慧教学平台、跨领域团队、多模态资源库等相关配套保障机制；随后从构建系统性学习框架、定制个性化学习路径、精准推荐教学资源、完善多元化评价体系、赋能线下PBL项目式学习五个维度，分析知识图谱与AI课程在教学实践中的具体应用。该模式能有效提升教学内容时效性与学生综合素养，为数字贸易时代复合型经贸人才培养提供实践路径，也为高校专业课程智慧化改革提供参考。

Abstract: Against the backdrop of the digital economy, the formats of international trade continue to innovate, while the traditional teaching model faces such dilemmas as fragmented knowledge, homogeneous supply, outdated content, and simplistic evaluation. Aiming to address these dilemmas, this paper explores an intelligent teaching model for international trade courses that integrates knowledge graphs and AI technology. Firstly, it expounds on the construction paths of the knowledge graph for international trade courses and the AI course, as well as relevant supporting guarantee mechanisms including the intelligent teaching platform, interdisciplinary team, and multi-modal resource database. Subsequently, from five dimensions—constructing a systematic learning framework, customizing personalized learning paths, accurately recommending teaching resources, improving a diversified evaluation system, and empowering offline PBL project-based learning—it analyzes the specific application of the knowledge graph and AI course in teaching practice. This model can effectively enhance the timeliness of teaching content and students’ comprehensive literacy, providing a practical path for cultivating compound economic and trade talents in the era of digital trade, and also offering a reference for the intelligent reform of professional courses in colleges and universities.