基于面授次数分析辅导中心对数学成绩的差异化影响。
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
- 用T-learner扩展出依赖治疗次数的因果效应模型
- 发现面授次数越多，教育效果越显著但边际递减
- 适合关注教育干预精准评估的研究者参考
本研究考察了驹込大学学术支持中心的教育效果。初步评估显示，因群体偏差导致中心实际影响被低估。为解决此问题，作者采用因果推断理论，利用T-learner评估了中心面对面（F2F）辅导项目的条件平均处理效应（CATE）。通过扩展T-learner，提出一种依赖于治疗次数（即面授次数）的新CATE函数，并据此预测不同面授次数下的辅导效果表现。
原文摘要 · Abstract (English)
This study examines the educational effect of the Academic Support Center at Kogakuin University. Following the initial assessment, it was suggested that group bias had led to an underestimation of the Center's true impact. To address this issue, the authors applied the theory of causal inference. By using T-learner, the conditional average treatment effect (CATE) of the Center's face-to-face (F2F) personal assistance program was evaluated. Extending T-learner, the authors produced a new CATE function that depends on the number of treatments (F2F sessions) and used the estimated function to predict the CATE performance of F2F assistance.
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