The role of spatial consistency in dual-task detection: Implications for automatic and controlled search.

摘要

The goal of this dissertation is to understand what enables successful dual-task performance when one of the component tasks continuously requires attention. Simultaneously performing two tasks is extremely challenging. When first attempting to dual-task, performance tends to be effortful and error prone even when both tasks have been trained extensively in isolation. Although single-task practice is helpful, dual-task practice is necessary in order to learn how to coordinate, integrate and prioritize component tasks. Dual-tasking is cognitively resource intensive and therefore it is critical to automate as much task related processing as possible. When one of the component tasks continuously requires attention, such as a varied-mapped (VM) task, it presents an additional challenge. Schneider and Fisk (1982a) demonstrated that the attention-consuming VM task must be prioritized throughout training in order for the performer to learn to dual-task without cost. Furthermore, they demonstrated that cost-free dual-tasking is only possible when the attention-consuming VM task is paired with an automatic consistently-mapped (CM) task. Hill and Schneider conducted pilot research demonstrating that participants were unable to prioritize the attention-consuming VM task despite intention and extensive training. The current study is an attempt to understand the source of this failure. Three hypotheses were tested, 1) CM target pop-out enables CM-VM proficient dual-tasking, 2) consistent spatial search across task load enables proficient dual-tasking 3) distractor segregation impedes proficient dual-tasking. Four experiments were conducted in which participants attempted to learn to perform a CM-VM dual-task without cost. All participants were instructed to prioritize the attention-consuming VM task; however some experimental groups incurred greater dual-task interference. The behavioral data suggests that both CM task pop-out and consistent spatial search across task loads enable CM-VM dual-task performance without cost. The result highlights the importance of minimizing confusability and implementing multiple levels of consistency when attempting to train a cognitively intensive high workload skill.