Abstract—In response to the requirements of the Ministry of Education for the construction of national first-class courses, and to promote the deep integration of teaching mode innovation and scientific evaluation, this study focuses on the optimization of the BOPPPS teaching mode, which is widely used in engineering and medical education because of its goal-oriented and closed-loop feedback design, but relies on teachers' experience in teaching adjustment and is prone to confuse the correlation and causality between measures and effects. For this reason, this study takes the front door criterion and counterfactual inference of causal inference science and migrates them to be applied to education, mediated elimination of confounding and counterfactual inference are used to optimize the BOPPPS model, and exploring a continuous improvement scheme using an information security course as an example. The results show that the improved model significantly improves the rationality of experimental design and teaching effectiveness, helps teaching decision-making shift from experience-driven to data-driven, meets the national curriculum standard of civic-political integration, and provides an innovative paradigm for the accreditation of engineering education. 
 

Keywords—BOPPPS teaching model, pedagogical reform, counterfactual reasoning, causal inference 

Cite: Yao Xiao, Bin Duan, and Yi Kuang, "Causal Inference for BOPPPS Instructional Model Continuous Improvement Programs," International Journal of Learning and Teaching, Vol. 11, No. 6, pp. 402-407, 2025.

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