The difference between generating counterexamples and using them during reasoning

摘要

The aim of this article is to provide insight into the types of long-term knowledge that are used for solving causal conditional inferences. Two taxonomies were constructed to map the types of counterexample. The available counterexamples are traditionally probed via a counterexample generation task. We observed that there are some significant differences in the types of counterexample retrieved in the reasoning task versus the generation task. The generation task can be used for predicting answers that sprout from a reasoning process that takes counterexample into account, but some participants use a different reasoning process in which the available semantic information is not used as contrasting evidence. Nonetheless, we found that the results of the generation task validly predicted the proportion of inferences accepted as well as the number of counterexamples used during reasoning.