Department of Psychology, University of Edinburgh, Edinburgh, Scotland.
Max Planck Institute for Human Development, Lentzeallee 94, Berlin, Germany.
Psychon Bull Rev. 2022 Dec;29(6):2314-2324. doi: 10.3758/s13423-022-02120-1. Epub 2022 Jul 13.
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.
一次改变一个变量，同时控制其他变量，这是科学实验的一个关键方面，也是 STEM 课程的核心组成部分。然而，据报道，儿童在学习和实施这一策略方面存在困难。为什么儿童对如何最好地干预因果系统的直觉与科学实践相冲突？数学分析表明，控制变量并不总是最有效的学习策略，其有效性取决于问题的“因果稀疏性”，即有多少变量可能影响结果。我们测试了 7 至 13 岁儿童（n=104）根据对因果稀疏性的预期，调整学习策略的程度。我们报告了新的证据，证明以前的一些工作可能低估了儿童的因果学习技能：儿童可以进行和解释对照实验，对因果稀疏性敏感，并利用这些信息调整他们的测试策略，表现出适应性决策。
