Production and comprehension have long been viewed as inseparable components of language. The study of vision, by contrast, has centered almost exclusively on comprehension. Here we investigate drawing—the most basic form of visual production. How do we convey concepts in visual form, and how does refining this skill, in turn, affect recognition? We developed an online platform for collecting large amounts of drawing and recognition data, and applied a deep convolutional neural network model of visual cortex trained only on natural (...) images to explore the hypothesis that drawing recruits the same abstract feature representations that support natural visual object recognition. Consistent with this hypothesis, higher layers of this model captured the abstract features of both drawings and natural images most important for recognition, and people learning to produce more recognizable drawings of objects exhibited enhanced recognition of those objects. These findings could explain why drawing is so effective for communicating visual concepts, they suggest novel approaches for evaluating and refining conceptual knowledge, and they highlight the potential of deep networks for understanding human learning. (shrink)

The ability to analyze arguments is critical for higher-level reasoning, yet previous research suggests that standard university education provides at best modest improvements in students’ analytical reasoning abilities. What techniques are most effective for cultivating these skills? Here we investigate the effectiveness of a 12-week undergraduate seminar in which students practice a software-based technique for visualizing the logical structures implicit in argumen- tative texts. Seminar students met weekly to analyze excerpts from contemporary analytic philosophy papers, completed argument visualization problem sets, (...) and received individualized feedback on a weekly basis. We found that Seminar students improved substantially more on LSAT Logical Reasoning test forms than Control students (d = .71, p < .001), suggesting that learning how to visualize arguments in the seminar led to large generalized improvements in students’ analytical reasoning skills. Moreover, blind scoring of final essays from Seminar students and Control students, drawn from a parallel lecture course, revealed large differences in favor of seminar students (d = 0.87, p = .005). Seminar students understood the arguments better, and their essays were more accurate and effectively structured. Taken together, these findings deepen our understanding of how visualizations support logical reasoning, and provide a model for improving analytical reasoning pedagogy. (shrink)