Time-Based Expectancy in Temporally Structured Task Switching

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Abstract

In many situations, people have to switch between different tasks. Previous research has shown that task switching leads to relatively slow responses and high error rates. In many real-life task-switching contexts, tasks are not randomly distributed over time, but the temporal distribution of tasks carries information. Often the delay before a task predicts to some degree which task it will be, like when a longer browser loading time for a website makes the search for an alternative more likely. The present study investigated whether and how humans adapt to such temporal regularities. In a series of five experiments, intertask delays predicted with different probabilities the task in the upcoming trial, or whether the task switches in the upcoming trial. Participants adapted their response behavior to the predictability of the task, for all tested degrees of predictability (70%, 80%, 90%), but only for the degree of 90% predictability when the task transition was temporally predictable. The adaptation was implicit and task repetitions as well as switches, both benefitted from this adaptation. Likewise, performance after 500 ms and 1,500 ms delays was facilitated by time-based predictability. The results are discussed in the context of previous findings on nontemporal task predictability.

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