Uncovering variability in children's concepts and conceptual change
Capturing the structure and development of human conceptual knowledge is a challenging but fundamental task in Cognitive Science. The most prominent approach to uncovering these concepts is Multidimensional scaling (MDS), which has provided insight into the structure of human perception and conceptual knowledge. However, MDS usually requires participants to produce large numbers of similarity judgments, leading to prohibitively long experiments for most developmental research. Furthermore, MDS provides a single psychological space, tailored to a fixed set of stimuli. In contrast, we present a method that learns psychological spaces flexibly and generalizes to novel stimuli. In addition, our approach uses a simple, developmentally appropriate task, which allows for short and engaging developmental studies. We evaluate the feasibility of our approach on simulated data and find that it can uncover the true structure even when the data consists of aggregations of diverse categorizers. We then apply the method to data from the World Color Survey and find that it can discover language-specific color organization. Finally, we use the method in a novel developmental experiment and find age-dependent differences in conceptual spaces for fruit categories. These results suggest that our method is robust and widely applicable in developmental tasks with children as young as four years old.