Several studies have shown that predictive and causal judgments vary depending on whether the question used to assess the relationship between events is presented after each piece of information or only after all the available information has been observed. This effect could be understood by assuming that in the two cases people perceive that the test question requires that different sets of evidence be taken into account. This hypothesis is tested in the present experiments through contextual manipulations that take place at the time of training and at the time of test. Our results show that people use this contextual information to infer which set of events should be considered when making their subjective assessments. The results are at odds with current theoretical approaches, but it is possible to develop mechanisms that would allow these models to account for the observed evidence. Learning to predict future events from present events is one of the most powerful adaptive tools, since it allows an organism to find the necessary resources for survival and to avoid dangerous situations. Given its importance, this kind of predictive learning was the central focus of animal behavior research throughout the twentieth century. During the last decades, predictive learning has also become important in the area of human cognition, where it has given rise to a great amount of empirical and theoretical research. The vast amount of evidence provided by this research has sometimes turned out to be quite difficult to explain by the available theoretical approaches. Many variables usually neglected by theoretical models influence the process of human learning of predictive relations among events or the way in which humans use the acquired information. Among other things, it has been shown that the probe question used to assess participants ’ judgment (Matute,

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