Computational and animal models suggest that the unlearning or pruning of incorrect meanings matters for word learning. However, it is currently unclear how such pruning occurs during word learning and to what extent it depends on supervised and unsupervised learning. In two experiments (N[subscript 1] = 40; N[subscript 2] = 42), adult…

Being able to estimate quantity is important in everyday life and for success in the STEM disciplines. However, people have difficulty reasoning about magnitudes outside of human perception (e.g., nanoseconds, geologic time). This study examines patterns of estimation errors across temporal and spatial magnitudes at large scales. We evaluated the…

Does expertise within a domain of knowledge predict accurate self-assessment of the ability to explain topics in that domain? We find that expertise increases confidence in the ability to explain a wide variety of phenomena. However, this confidence is unwarranted; after actually offering full explanations, people are surprised by the limitations…