【摘要】 为适应信息化、智能化时代的需求，《工程教育认证标准》新增“计算思维”和“批判性思维”观测点，旨在培养学生在解决复杂工程问题中运用计算思维的能力，并通过批判性思维实现创新和持续学习。然而，课程设计面临混杂因子干扰、静态评价体系、缺乏动态优化机制等挑战，难以有效支撑这两个观测点的达成。为此，本文基于因果科学理论，提出“引入中介消除混杂”方法，精准量化教学干预的因果效应，并以能源信息物理系统课程为例，具体展示如何引入中介变量消除混杂因子的干扰，量化教学干预效果并实现课程的持续改进。更多还原

【Abstract】 To meet the demands of the information and intelligent era, the Engineering Education Accreditation Standards have introduced new evaluation criteria for “computational thinking” and “critical thinking”, aiming to cultivate students’ ability to apply computational thinking in solving complex engineering problems and achieve innovation and lifelong learning through critical thinking. However, course design faces challenges such as confounding factor interference, static evaluation systems, and a lack of dynamic optimization mechanisms, making it difficult to effectively support the achievement of these two criteria. To address these issues, this paper, based on causal science theory, proposes the method of “mediator-based confounding elimination” to accurately quantify the causal effects of teaching interventions. Taking the “energy cyber-physical systems” course as an example, it demonstrates how mediator variables can be introduced to eliminate confounding factor interference, quantify teaching intervention effects, and achieve continuous course improvement.更多还原