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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.

Climate scientists are increasingly called upon to collaborate with policy makers to develop climate science–informed policy decisions. However, there are concerns that existing professional and cultural boundaries will remain persistent barriers to fulfilling the potential promise of these collaborations. The perception that scientists will be learning by doing while pursuing these efforts does little to assuage these concerns because more research is needed into how scientists actually learn to collaborate more effectively. Using interviews with 18 individuals identified by their peers as particularly successful participants in collaborations between Native American Tribes and climate science organizations, this paper offers suggested practices and examines learning processes underlying the development of these suggestions. The development of the list of suggested practices highlights the extent to which having the right attitude, taking the right actions, and cultivating the right processes are intertwined factors associated with success in these collaborations. Analysis of the learning processes underlying interviewees’ suggestions for suggested practices offered five sources of information that frequently led interviewees to reflect on their experiences and gain new knowledge from them. Despite these common trends, each interviewee described a reflection system that they had cultivated to continually monitor and enhance their work in collaborations that was personalized and distinctive from those the other interviewees used. Increased attention to these tailored reflection systems offers a path forward for understanding how experiential learning can most effectively enhance climate change decision support.