Children’s failure to control variables may reflect adaptive decision making

Changing one variable at a time while controlling others is a key aspect of scientific experimentation and a central component of STEM curricula. However, children reportedly struggle to learn and implement this strategy. Why do children's intuitions about how best to intervene on a causal system conflict with scientific practices? Mathematical analyses have shown that controlling variables is not always the most efficient learning strategy, and that its effectiveness depends on the "causal sparsity'' of the problem, i.e. how many variables are likely to impact the outcome. We tested the degree to which 7- to 13-year-old children (n = 104) adapt their learning strategies based on expectations about causal sparsity. We report new evidence demonstrating that some previous work may have undersold children's causal learning skills: Children can perform and interpret controlled experiments, are sensitive to causal sparsity, and use this information to tailor their testing strategies, demonstrating adaptive decision-making.

逐个变更变量并控制其他变量是科学实验的关键要素，亦为STEM课程的核心组成部分。然而，据报告，儿童在学习并实施这一策略时存在困难。为何儿童对如何最佳干预因果系统的直觉与科学实践相悖？数学分析表明，控制变量并非总是最有效的学习策略，其有效性取决于问题的“因果稀疏度”，即可能影响结果变量的数量。我们测试了7至13岁儿童（n = 104）根据对因果稀疏度的预期调整其学习策略的程度。我们报告了新的证据，表明先前的一些工作可能低估了儿童的因果学习技能：儿童能够进行并解释控制实验，对因果稀疏度敏感，并利用这一信息调整其测试策略，展现了适应性决策能力。