Abstract：Continuous improvement can monitor and improve the teaching quality of colleges and universities for a long time. How to carry out scientific and effective continuous improvement of course teaching based on the evaluation results has become a hot topic at present. This paper introduces the “back-door adjustment” of causal inference science, analyzes the importance of learning confounding control in teaching causal inference, and explains from the mechanism why it is necessary to strengthen the process evaluation of diversified contents including learning motivation, strategies, emotions, attitudes, and values, and proposes a continuous improvement model based on the control of learning confounding. Firstly, analyze the existing learning confounding factors based on diversified evaluation contents, construct a causal diagram of course teaching and control the confounding variables by back-door adjustment, to calculate the causal effect of teaching methods on the learning outcomes. Secondly, propose improvement measures to eliminate the interference of confounding, and analyze the reasons for the improvement and the effects of the intervention through the causal diagram. Finally, it is implemented in teaching, and plans for future improvement are developed based on the new evaluation results. The practical results show that the model is scientific and effective.
龙璇, 段斌, 柯其聪. 基于学情混杂控制的课程质量评价持续改进模式研究[J]. 电气技术, 2022, 23(10): 67-73.
LONG Xuan, DUAN Bin, KE Qicong. Research on continuous improvement model of course quality evaluation based on learning confounding control. Electrical Engineering, 2022, 23(10): 67-73.
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