This project is creating new learning materials and strategies to foster the ability of students to reason by analogy about global climate change and is assessing student ability to use analogies to make and evaluate claims about global climate change. The PIs are testing the hypothesis that we can dramatically improve the climate change literacy of non-science majors through explicit instruction about analogical reasoning in a general education-science course that focuses on Global Change. The project is focusing on analogical reasoning because 1) analogical reasoning is central in higher-level learning, 2) scientists routinely use analogies to generate hypotheses and to solve research problems, and 3) scientists commonly use analogies to convey information about complex systems responsible for global climate change. The PIs are testing their hypothesis using matched experimental and control classes taught by the same instructor. They are assessing the ability of students to generate causal explanations of processes that drive global change through a mixed methods approach. The PIs are developing new instructional materials and assessment instruments based on the understanding of analogical reasoning by cognitive scientists. In particular, the PIs are helping students to understand analogies and are also improving their analogical reasoning by focusing on five dimensions of analogical reasoning suggested by decades of research: retrieval, mapping, evaluation, abstraction and re-representation. By analyzing the efficacy of their approach, the PIs are developing a new, detailed model of how best to teach analogical reasoning specifically within the context of improving climate change literacy.
The goal of this project was to teach undergraduates fundamental concepts of geoscience in order to foster understanding of the mechanisms and consequences of climate change. More specifically, we sought ways to support students’ use of analogies from familiar domains to geoscience topics. Educational research has shown that analogies are very often used in geoscience instruction and in science instruction in general. For example, to explain convection in the earth’s mantle, instructors often use the analogy of a lava lamp: oil (heated by a lamp from below), expands and rises; as it rises it cools and its density increases, causing it to sink to the bottom, where the cycle begins again. Although such analogies can be very helpful, students sometimes fail to derive the benefits, especially if insufficient instructional support is provided. We hypothesized that if students were given supportive materials to help them work through the analogies, they would be able to draw inferences from the analogies to better understand the geoscience topic matter. With evidence of the instructive nature of analogies, we designed exercises that asked students to place elements from the geoscience concepts into correspondence with their analogous elements from more familiar base concepts, highlighting their common structure. One group of students completed a series of such analogy exercises, while a second group of students drew diagrams of the causal structure of the same set of target geoscience concepts (another method that we hypothesized would support learning physical science concepts). Both the causal diagram group and analogy group outperformed typical students in such a course, but contrary to prediction, the analogy group did not do better than the causal diagram group. Based on further analysis, we concluded that our initial implementation of the analogy exercises had focused too heavily on how individual elements from base and target domains corresponded (e.g. lamp bulb --> core), and not enough on the more important causal structures (e.g., the idea that heating a fluid leads to expansion, and that expansion leads to lower density, and so on). And it is understanding these deeper structures that is key to understanding the geoscience concepts, and the key goal of making analogical comparisons. We followed up on this work by modifying a subset of the analogy exercises so that they focused on both deep causal parallels as well as correspondences between individual elements. When we tested these analogy exercises on a new group of students, we found that students were actually better at aligning the deeper structures than at finding correspondences between the individual elements. That is, they often had some grasp of the overall similarity between the two domains, while not quite seeing how individual elements from each domain corresponded. The next step in this research is to further investigate the optimal way to design such analogy exercises to maximize understanding through supporting the ability of students to recognize both the common deep structures and how individual elements correspond. Further, based on the positive results with causal diagrams, we hypothesize that asking student to construct such diagrams may also aid students in understanding scientific domains. Future work should focus on how to integrate the use of such diagrams with analogical comparison.
