Analogy Generation in Science Experts and Novices.

There is a critical inconsistency in the literature on analogical retrieval. On the one hand, a vast set of laboratory studies has found that people often fail to retrieve past experiences that share deep relational commonalities, even when they would be useful for reasoning about a current problem. On the other hand, historical studies and naturalistic research show clear evidence of remindings based on deep relational commonalities. Here, we examine a possible explanation for this inconsistency-namely, that remindings based on relational principles increase as a function of expertise. To test this claim, we devised a simple analogy-generation task that can be administered across a wide range of expertise. We presented common events as the bases from which to generate analogies. Although the events themselves were unrelated to geoscience, we found that when the event was explainable in terms of a causal principle that is prominent in geoscience, expert geoscientists were likely to spontaneously produce analogies from geoscience that relied on the same principle. Further, for these examples, prompts to produce causal analogies increased their frequency among nonscientists and scientists from another domain, but not among expert geoscientists (whose spontaneous causal retrieval levels were already high). In contrast, when the example was best explained by a principle outside of geoscience, all groups required prompting to produce substantial numbers of analogies based on causal principles. Overall, this pattern suggests that the spontaneous use of causal principles is characteristic of experts. We suggest that expert scientists adopt habitual patterns of encoding according to the key relational principles in their domain, and that this contributes to their propensity to spontaneously retrieve relational matches. We discuss implications for the nature of expertise and for science instruction and assessment.

A test of the circumvention-of-limits hypothesis in scientific problem solving: the case of geological bedrock mapping.

Sources of individual differences in scientific problem solving were investigated. Participants representing a wide range of experience in geology completed tests of visuospatial ability and geological knowledge, and performed a geological bedrock mapping task, in which they attempted to infer the geological structure of an area in the Tobacco Root Mountains of Montana. A Visuospatial Ability × Geological Knowledge interaction was found, such that visuospatial ability positively predicted mapping performance at low, but not high, levels of geological knowledge. This finding suggests that high levels of domain knowledge may sometimes enable circumvention of performance limitations associated with cognitive abilities.