Comparisons in Category Learning: How Best to Compare For What

Comparisons in Category Learning: How Best to Compare for What Erin Jones Higgins (eljones3@illinois.edu) Department of Psychology, 603 E. Daniel St. Champaign, IL, 61820 USA Brian H. Ross (bhross@illinois.edu) Department of Psychology, 603 E. Daniel St. Champaign, IL, 61820 USA Abstract Learners frequently compare across examples of categories in order to learn more about them. Surprisingly little work has been done looking at how the type of comparison one engages in during learning affects what information is eventually learned. Across three experiments we show that the type of comparison, either within-category or between-category, affects what conceptual information is acquired and the benefits of each type of comparison change depending on the type of category one is learning. Keywords: comparisons, category learning, problem solving Introduction Category knowledge is used in a variety of ways and there is evidence that the way categories are learned affects how they are represented (Markman & Ross, 2003). Specifically, the particulars of the learning task are critical for determining what information a learner acquires (e.g. Jones & Ross, in press). This view of the learner as actively processing items suggests the potential importance of other kinds of active processing. Comparison of examples has often been suggested as important for category learning (e.g. Spalding & Ross, 1994), but the various possibilities for comparisons have not been adequately explored. A better understanding of learning requires a better understanding of comparison effects. In this paper, we suggest that the type of comparison affects later performance, but its effect is modulated by type of category. Most comparisons research examines how comparisons enable better analogical transfer. In these experiments the focus is on how comparing across examples benefits analogical reasoning contrasted with not comparing at all, rather than focusing on different types of comparisons. When learners are told to compare across examples, successful transfer to novel problems is higher than when comparisons are not part of learning (e.g. Gentner, Lowenstein, & Thompson, 2003). It is not the case that any comparison will benefit learning. Rittle-Johnson and Star (2009) demonstrated that the type of information being compared when solving math problems affects what is learned. Learners who compared different solution methods to the same problem showed greater conceptual knowledge and flexibility than learners who compared different problem types. These results suggest that the type of comparison matters for learning tasks that rely on comparisons. It is clear that comparisons are critical to category learning, so the type of comparison could also be important to consider. It is possible that between- and within-category comparisons provide the learner with very different information about the category or categories being learned, and one or the other could be beneficial depending on the goals of the task and what information the learner needs to take away from the comparison. This observation has yet to be addressed in the category learning literature. Gentner’s (1983) structure-mapping theory proposes that people reason through analogies by noticing common relational structures of the two instances being compared (abstracted from the surface features of the examples). In addition, it is easier to notice differences between two examples when they are highly similar compared to when they are not similar because highly similar examples share many alignable differences (Markman & Wisniewski, 1997; Gentner & Markman, 1997). How this theory plays out in category learning is not yet clear. On the one hand, structure-mapping theory might predict that within-category comparisons are more beneficial than between-category comparisons because items from the same category will be more similar to each other and have more alignable differences. On the other hand, if the categories being compared have many alignable differences, then between- category comparison could also be helpful for learning the feature values for each category. Additionally, there are categories whose relational structure is not difficult to acquire. For these types of categories, between-category comparisons may also be more helpful if learning to distinguish between categories is critical. There is some evidence suggesting that between-category comparison is more beneficial for category learning. Kornell and Bjork (2008) had participants learn categories of paintings. When examples from one category were spaced between examples from other categories, learners were better able to classify novel items from those categories at test compared with novel items from categories whose instances were massed together during learning. The examples were presented one at a time, so participants were never told to make comparisons, however, the benefit for spaced items suggests that they did benefit from having examples from multiple categories in mind. There are reasons that within- and between-category comparisons could be helpful, though it seems that the impact of each comparison type could be modulated by