Proceedings of the Annual Meeting of the Cognitive Science Society

Previous research has shown that our subjective sense of certainty doesn't always accurately reflect the strength of the evidence that has been presented to us. We investigate several key factors that drive children's certainty using a Boolean concept learning task. We created an idealized learning model to predict children's accuracy and certainty during the experiment, given past evidence that they have seen in the task, and we compared its predictions with our behavioral results. Our results suggest that while predictors from the idealized learning model capture children's accuracy, behavioral predictors generated by the behavioral data can better predict children's certainty. We also show that younger children's certainty can be explained by the idealized learning model, while older children's certainty is primarily predicted by how well they observed themselves doing in the experiment.