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In 4 experiments, participants alternated between different tasks or performed the same task repeatedly. The tasks for 2 of the experiments required responding to geometric objects in terms of alternative classification rules, and the tasks for the other 2 experiments required solving arithmetic problems in terms of alternative numerical operations. Performance was measured as a function of whether the tasks were familiar or unfamiliar, the rules were simple or complex, and visual cues were present or absent about which tasks should be performed. Task alternation yielded switching-time costs that increased with rule complexity but decreased with task cuing. These factor effects were additive, supporting a model of executive control that has goal-shifting and rule-activation stages for task switching. It appears that rule activation takes more time for switching from familiar to unfamiliar tasks than for switching in the opposite direction.

Three experiments investigated the proposal that inductive inferences about different properties depend on different measures of similarity. In Experiments 1 and 2, Ss were given the premise that a category of animals has some property and judged the probability that another category of animals also has that property. Ss made the strongest inferences when the kind of property (anatomical or behavioral) corresponded to the kind of similarity between the animal categories (anatomical or behavioral). These results cannot be explained in terms of a single measure of similarity underlying induction. In Experiment 3, Ss rated the similarity of animal pairs with respect to anatomy or behavior. Regression analyses showed that both behavioral and anatomical similarity influenced behavioral inferences, but only anatomical similarity influenced anatomical inferences.People use similarity to make inferences. When Category A has Property P, people are more likely to infer that Category B also has Property P to the extent that A and B are perceived to share other features. We propose that, in addition, Property P itself has an important role in determining which features are used to evaluate the similarity between Categories A and B. Inductive reasoning does not rely on a fixed notion of similarity; instead, the similarity between A and B will be evaluated with respect to features that are relevant to Property P. In particular, we propose that different measures of similarity are used when people make inferences about anatomical properties and behavioral properties of animals so that people focus on similarity in terms of anatomical features for anatomical inferences, and they focus on behavioral similarity for behavioral inferences.

Many socially important search tasks are characterized by low target prevalence, meaning that targets are rarely encountered. For example, transportation security officers (TSOs) at airport checkpoints encounter very few actual threats in carry-on bags. In laboratory-based visual search experiments, low prevalence reduces the probability of detecting targets (Wolfe, Horowitz, & Kenner, 2005). In the lab, this "prevalence effect" is caused by changes in decision and response criteria (Wolfe & Van Wert, 2010) and can be mitigated by presenting a burst of high-prevalence search with feedback (Wolfe et al., 2007). The goal of this study was to see if these effects could be replicated in the field with TSOs. A total of 125 newly trained TSOs participated in one of two experiments as part of their final evaluation following training. They searched for threats in simulated bags across five blocks. The first three blocks were low prevalence (target prevalence ≤ .05) with no feedback; the fourth block was high prevalence (.50) with full feedback; and the final block was, again, low prevalence. We found that newly trained TSOs were better at detecting targets at high compared to low prevalence, replicating the prevalence effect. Furthermore, performance was better (and response criterion was more "liberal") in the low-prevalence block that took place after the high-prevalence block than in the initial three low-prevalence blocks, suggesting that a burst of high-prevalence trials may help alleviate the prevalence effect in the field.

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