Everyday conditional reasoning: a working memory-dependent tradeoff between counterexample and likelihood use.

Abstract

Considerable evidence has revealed that working memory capacity is an important determinant of conditional reasoning performance. There are two accounts describing the conditional inference process, the probabilistic and the mental models accounts. According to the mental models account, reasoners retrieve and integrate counterexample information to attain a conclusion. According to the probabilistic account, reasoners base their judgments on probabilistic information. It can be assumed that reasoning according to the mental models process would require more working memory resources than would solving the inference on the basis of probabilistic information. By means of a verbal report study, we showed that participants with low working memory capacity more often use probabilistic information, whereas participants with higher working memory capacity are more likely to use counterexample information. Working memory capacity thus not only relates to reasoning performance, it also determines which process reasoners will engage in.