高职AI通识课程虚实融合教学的实践路径

The Practical Path of Virtual-Real Integration Teaching in Higher Vocational AI General Education Courses

摘要: 针对高职人工智能通识课程教学中普遍存在的内容抽象、实训资源匮乏、教学场景单一等问题，探索虚实融合教学模式改革的实践路径与实施效果。在系统梳理虚实融合教学与AI通识课程改革研究进展的基础上，研究提出“校企协同、虚实融合、项目驱动”三位一体的教学模式，并以山东外贸职业学院软件技术专业两个平行班级为对象，开展了为期一学期的准实验教学。实验班在虚拟仿真资源共建、“虚–实–虚”螺旋递进教学流程设计、AIGC辅助教学工具开发及数据驱动多元评价体系构建四个维度进行了系统改革。教学数据表明，实验班的知识掌握与项目实践平均分较对照班提高11.2% (独立样本t检验结果显示，t (84) = 3.76，p < 0.001，Cohen’s d = 0.81，达到中等以上效应量)，学习满意度达91.2%，AIGC工具应用能力显著提升。虚实融合教学模式能有效激发学习兴趣、降低认知门槛、提升AI实践能力与人机协作素养，为高职院校在有限实训条件下开展高质量的AI通识教育提供了一个有潜力的、值得进一步验证的教学改革初步方案。

Abstract: To address the prevalent issues in higher vocational AI general education courses, such as abstract content, insufficient training resources, and monotonous teaching scenarios, this study explores the practical path of virtual-real integration teaching reform and its implementation effects. Based on a systematic review of the research progress on virtual-real integration teaching and AI general education curriculum reform, a three-in-one teaching model of “school-enterprise collaboration, virtual-real integration, and project-driven learning” is proposed. A one-semester quasi-experimental teaching was conducted with two parallel classes in the Software Technology major at Shandong Foreign Trade Vocational College. The experimental class carried out systematic reforms in four dimensions: co-building virtual simulation teaching resources, designing a “virtual-real-virtual” spiral progressive teaching process, developing AIGC-assisted teaching tools, and constructing a data-driven diversified evaluation system. Teaching data show that the average project score of the experimental class was 11.2% higher than that of the control class (independent samples t-test results show t (84) = 3.76, p < 0.001, Cohen’s d = 0.81), the learning satisfaction rate reached 91.2%, and the ability to apply AIGC tools was significantly improved. The virtual-real integration teaching model can effectively stimulate learning interest, lower cognitive barriers, and enhance AI practical ability and human-machine collaboration literacy, providing a promising and preliminarily verified teaching reform case for higher vocational colleges to carry out high-quality AI general education under limited conditions.