Two studies, an experimental category learning task and a computational simulation, examined how sequencing training instances to maximize comparison and memory affects category learning. In Study 1, 2-year-old children learned color categories with three training conditions that varied in how categories were distributed throughout training and how similarity between exemplars progressed across instances. The results indicate that beginning learning by interacting with a limited set of highly similar exemplars leads to more learning than when the instances are distributed and dissimilar. In Study 2, order effects were examined with a symbolic connectionist model of general learning and representation discovery (DORA). The results of the studies suggest that when the presentation of instances is ordered in such a way that discrete instances of a category can be more readily connected in memory, category learning and discovery are more likely to occur.