Leveraging characteristics of task structure to predict the cost of interruption

Abstract

A challenge in building interruption reasoning systems is to compute an accurate cost of interruption (COI). Prior work has used non task-specific cues to predict COI, but ignore characteristics related to the structure of a task. This work investigates how well characteristics of task structure can predict COI, as objectively measured by resumption lag. In an experiment, users were interrupted during task execution at various subtask boundaries to collect a large sample of resumption lag values. Statistical methods were employed to create a parsimonious model that uses characteristics of task structure to predict COI. A subsequent experiment with different tasks showed that the model can predict COI with reasonably high accuracy. Our model can be expediently applied to many goal-directed tasks, allowing systems to make more effective decisions about when to interrupt.

Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors

“…Such an automatic interruptibility measure can then be used to better coordinate interruptions by, for instance, providing visual cues or postponing them to a more suitable moment [37]. Prior work examined the use of context-aware sensors to gather information, such as audio and video streams, keyboard and mouse interaction, or task characteristics (e.g., [17,18,27]). …”

Resumption lag at interruptible timing might not be short in actual environment

“…Furthermore, our analysis of the relationship between task phases and RLa reveals that interruptions at the end of a task hardly affected the RLa. As suggested in previous studies [4], at the end of the task, the amount of information transmitted after AS is presumed to be small. Thus, interruptions at the end of task do not increase the cognitive cost.…”

“…On the other hand, Jin and Dabbish [5] suggested that the AS, which is a self-interruption, occurs for several reasons. Iqbal and Bailey [4] revealed that task phase affects the cognitive cost. To examine the effects of task phases, we categorized the ASs into three groups, i.e., "beginning of task," "continuation of task," and "ending of task," on the basis of the increase or decrease in the number of opened windows after AS.…”

“…The effects of task breakpoints have been investigated based on prior task-structure analyses [4]. Other studies focused on application switching (AS) as the task breakpoint during PC work [2,3].…”

Investigating interruptions in the context of computerised cognitive testing for older adults

“…Observational and simulated naturalistic studies of interruptions have addressed the many contextual, temporal, and social factors found to be predictive of COI. These have included task structure [16], primary task visibility during an interruption [17], the frequency of interruption [33] and the source and modality of an interruption [26]. Incorporating these factors was outside the scope of our laboratory experiment, but we plan to assess the impact of interruption frequency and modality on COI in the near future.…”