The adaptivity of children’s search processes

Andreas Wilke

Clarkson University, Department of Psychology

Humans and other organisms must search effectively for the resources they need, whether these are physical (e.g., food or shelter) or informational (e.g., patterns in the world, or concepts stored in memory). Most human search studies have focused on brief (static) laboratory tasks, but being effective in realistic search settings requires adapting to changing environments over both short and long terms, and to changing individual abilities developmentally. In this talk, I will report on two ongoing projects that investigate how young children grow to understand searchable patterns as clusters and sequences.

A tendency to perceive illusory streaks or clumps in random sequences of data—the hot hand phenomenon—has been identified as a human universal tied to our evolutionary history of foraging for clumpy resources. In the first project, we investigated how this misperception of randomness and ecologically relevant statistical thinking broadly develops ontogenetically. Based on our work with adults, we developed three iPad-based decision-making tasks that assess how 3- to 10-year-old children decide that sequential events will continue in a streak or not, their understanding of randomness, and their ability to reason in spatially dependent terms. In a second project, we assessed more specifically to what extent children can differentiate among objective alternation probabilities of various kinds, specifically when they are non-random and do indeed contain statistical regularities. The distributions that were used included clumpy ones (where a hit is more likely to predict another hit nearby or vice versa) and dispersed ones (where a hit is more likely to predict a miss nearby or vice versa). Our project collected data at research sites in the United States and in Germany. Our analyses suggest that children, indeed, hold strong expectations of clumpy resources when they search through and reason with various statistical distributions.