Language is a powerful instrument for extracting relational information from stimuli. In a label extension task common labels invite comparison processes that help children focus on the more subtle relational similarity and away from the readily available perceptual similarity of the stimuli. The current experiment aims to explore whether non-linguistic representations of category membership are sufficient to invite such abstractions of relational information. Preschool children were asked to extend a category to either a relational or an object match. When given the opportunity to compare two instances of the category, and provided with a non- linguistic cue children extended the category to the relational match. These results further extend the benefit of comparison in learning, and suggest that language labels are not the only cue children can use in category formation.

The present study examined the role of detecting the initial causal system model followed by engaging in active vs. passive structural alignment in recognizing the key causal principles in subsequent novel examples. The results echo prior research on the benefit of analogical comparison in learning relational categories: participants who were prompted to compare outperformed participants in the baseline condition. Moreover, while the accurate representation of the causal system predicted noticing the relational structure in novel examples, making more accurate relational mappings made participants more likely to notice the structure above and beyond having an accurate representation. These findings offer insight into the role of active vs. passive analogical comparison and have implications for conditions that might support learning of relational categories.

Literature on memory research shows that when memorizing, people may blend two situations, i.e. when memorizing one story, they add elements from another story. Most of the cognitive models assume that the superficial similarity between two episodes is the primary factor for blending. However, there is evidence that people blend dissimilar stories as well, if these stories share the same relational structure. We contrasted the two factors in a single study and performed experiments with the same design and stimuli with adults and with 4-5-year-old children. The results show that there is no qualitative difference between the performance of adults and children. Also, both adults and children blend either pictures that have surface or structural similarity depending on the abstractness of the objects in them.

The ability to notice relational patterns across situations is crucial to learning. An important question is how people build transferable and generalizable knowledge by learning from examples. The study investigated the conditions that make comparison and explanation beneficial to learning by comparing learning outcomes of engaging in explanation or comparison in a categorization task and examining how varying degrees of instructional support affect these two processes. The results showed an advantage of comparison over explanation; however, this was specific to combination of relational labels and definitions and prompts to compare. These results add to existing research and extend our understanding of how best to support college students learning relatively difficult material. The findings also inform ways educators can support learning by developing instructional designs that support learning through analogical reasoning.

We tested whether relational knowledge is represented as a set of relations among entities or as a set of relational roles towhich entities are bound. Participants performed four relational processing tasks with the same set of word-pair stimuli:relational exemplar generation; similarity ranking; analogical verification; and a paired-associate learning task. In thesimilarity ranking task, we gathered separate rankings for relational, role and semantic similarity between word pairs.Relational similarity predicted exemplar generation frequencies, analogical verification accuracy and RTs, and relationalluring in associative memory. Role similarity predicted exemplar generation frequency, and, weakly, analogical verificationRTs. Semantic similarity did not predict any of the tasks, after controlling for the other two factors. Contrary to currenttheories which posit that semantic similarity is more important for retrieving relevant analogues, and that analogicalmapping is based on role-filler bindings, relational similarity was the strongest predictor across all tasks.