商工融合视域下生成式AI赋能《数据结构》课程教学改革探索

Integrating Business and Engineering: Exploring Generative AI-Enabled Teaching Reform of the “Data Structures” Course

摘要: 生成式人工智能的广泛应用正在改变编程类课程的教学环境。针对商科院校《数据结构》课程中“学生所学难以应用于实践”、“课程内容与产业需求脱节”的问题，本文尝试将商科领域的业务逻辑与工科领域的算法思维相结合，实现“商工融合”。具体工作包括：提出“认知负荷分层转移模型”；构建覆盖零售、金融、物流、营销、供应链五大领域的商务场景教学案例库；探索“双师三导”教学模式。教学实践表明，学生的商务问题解决能力、算法应用能力和课程满意度均有提升。这一经验可为同类院校的课程改革提供参考。

Abstract: The growing adoption of generative AI is reshaping the teaching environment of programming courses. In business-oriented universities, the “Data Structures” course has long faced two interconnected problems: “students struggle to apply what they have learned” and “the course content does not align well with industry needs”. We attempt to bridge this gap by integrating business logic with engineering-oriented algorithmic thinking—an approach we term “business-engineering integration”. Our specific efforts include: proposing a “hierarchical cognitive load transfer model”; developing a case library of business scenarios covering five domains—retail, finance, logistics, marketing, and supply chain; and exploring a “dual-mentor, triple-guidance” teaching model. Classroom practice shows that students’ ability to solve business problems, their competence in applying algorithms, and their overall course satisfaction have all improved. This experience may serve as a reference for curriculum reform in similar institutions.