Children's Active Physical Learning Is as Effective and Goal-Targeted as Adults'

We explore how children and adults actively experiment within the physical world to achieve different epistemic goals. In our experiment, one hundred one 4- to 10-year-old children and 24 adults either passively observed or used a touchscreen interface to actively interact with objects in a dynamic physical microworld with the goal of inferring one of two latent physical properties: relative object masses or local forces of attraction and repulsion. We find an age improvement in judgments as well as an advantage for active over passive learning. With the help of Bayesian statistics and a computational modeling framework for the quantitative analysis of participants' actions, we show that children's and adults' actions are equally successful in targeting their goal-relevant uncertainty, but that adults and older children are better able to use this information to respond correctly. We further unpack children's and adults' experimental strategies qualitatively, finding adults more likely to use a "deconfounding" strategy to isolate properties of interest, potentially creating evidence less susceptible to cognitive and perceptual errors.