Switch It Up! How Context Influences the Efficiency of Redundancy Gains in a Peripheral Task

Abstract

Optimizing the time and accuracy with which peripheral tasks can be monitored concurrent with a central primary task is of paramount importance for human factors researchers developing human systems. Nonetheless, peripheral tasks are often evaluated in isolation, and their effectiveness is assumed to generalize to multi-task contexts. Our work acknowledges that peripheral displays may be utilized in a variety of operational contexts. Across four experiments, we examine peripheral task detection speeds under several contextual factors related to operator workload and task-set. We use the capacity coefficient from the Systems Factorial Technology framework to quantify the extent that context influences redundant signal enhancements in a peripheral detection task. Across four experiments, we manipulated the presence, difficulty, and stability of the primary task to simulate different workload contexts. Using a novel time-varying estimate of workload capacity, we show that efficiency in detecting redundant peripheral targets decreases with high primary task demands. Our results also indicated higher capacity in less stable environments but a correspondingly greater workload impairment in these conditions. Implications for system design include consideration of the expected operator workload, as well as attention recruiting strategies to improve peripheral task detection speeds.