Inferring Multitasking Breakpoints from Single-Task Data


Recent research has shown that computer users placed in a deferrable multitasking situation generally postpone secondary-task interruptions until points of low mental workload in the primary task. Studies examining this phenomenon have relied on empirical data that explicitly show user switch points in the course of multitask performance. This paper addresses a related question: Can these same switch points, found empirically in a multitasking context, be inferred solely from single-task data? We investigate this question and propose an approach that analyzes a particular behavioral signature in single-task data — outliers in the distributions of time between task actions — to infer multitasking breakpoints. We evaluate this approach using behavioral data from a user-interface task, showing how the proposed method’s inferences from single-task data match well to the real switch points observed during multitask performance.

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