Understanding changes in mental workload during execution of goal-directed tasks and its application for interruption management

Abstract

Notifications can have reduced interruption cost if delivered at moments of lower mental workload during task execution. Cognitive theorists have speculated that these moments occur at subtask boundaries. In this article, we empirically test this speculation by examining how workload changes during execution of goal-directed tasks, focusing on regions between adjacent chunks within the tasks, that is, the subtask boundaries. In a controlled experiment, users performed several interactive tasks while their pupil dilation, a reliable measure of workload, was continuously measured using an eye tracking system. The workload data was extracted from the pupil data, precisely aligned to the corresponding task models, and analyzed. Our principal findings include (i) workload changes throughout the execution of goal-directed tasks; (ii) workload exhibits transient decreases at subtask boundaries relative to the preceding subtasks; (iii) the amount of decrease tends to be greater at boundaries corresponding to the completion of larger chunks of the task; and (iv) different types of subtasks induce different amounts of workload. We situate these findings within resource theories of attention and discuss important implications for interruption management systems.

Real-time Prediction of User Performance based on Pupillary Assessment via Eye-Tracking

“…The little IS-related work on the relationship between task-evoked mental effort and pupillary responses stems mainly from certain researchers: Bailey and Iqbal (2008), Iqbal et al (2005), Gwizdka (2014bGwizdka ( , 2016, Gwidzka and Zhang (2015), Buettner (2013Buettner ( , 2015Buettner ( , 2016aBuettner ( , 2016bBuettner ( , 2017b, and Buettner et al (2013). Iqbal et al (2005) and Bailey and Iqbal (2008) measured changes in mental effort when individuals executed different types of tasks (planning routes, editing documents, and classifying emails) (n1 = 12, n2 = 24).…”

“…Iqbal et al (2005) and Bailey and Iqbal (2008) measured changes in mental effort when individuals executed different types of tasks (planning routes, editing documents, and classifying emails) (n1 = 12, n2 = 24). Gwizdka (2014bGwizdka ( , 2016 demonstrated that pupil size is related to levels of information relevance.…”

“…Since previous work (e.g., Iqbal, Adamczyk, Zheng, & Bailey, 2005;Bailey & Iqbal, 2008;Buettner, Daxenberger, Eckhardt, & Maier, 2013) has demonstrated that the completion of a sequence of subtasks in realistic task environments (e.g., orientation, information search, reading, recall of information, writing) leads to a recurrent mental effort resulting in an observable variability of the pupil diameters, we evaluate whether the pupil diameter variability predicts user performance. Against this background, we formulate the following research question: RQ: Does the pupil diameter variability predict user performance?…”

Robust Multimodal Cognitive Load Measurement (RMCLM)

“…Bailey and Iqbal (2008) empirically examined changes in mental workload during goal-directed interactive tasks including reading comprehension, mathematical reasoning, product searching, and object manipulation. Percentage change in pupil size was used as the task-evoked pupillary response for continuous workload measurement.…”

How Do Task Structure and Uncertainty Influence Task-Interleaving Strategies During Distracted Driving?

“…For example, people tend to interleave at boundaries between sub-tasks (Payne, Duggan, & Neth, 2007). Sub-task boundaries provide an opportune time to interleave because cognitive workload is lower at sub-task boundaries (Bailey & Iqbal, 2008) and it is easier to resume a task at sub-task boundaries (Monk, Boehm-Davis, & Trafton, 2004). Brumby, Salvucci, and Howes (2009) found that drivers interleaved a distracting dialing task at sub-task boundaries.…”