Interrupting users engaged in tasks typically has negative effects on their task completion time, error rate, and affective state. Empirical research has shown that these negative effects can be mitigated by deferring interruptions until more opportune moments in a user's task sequence. However, existing systems that reason about when to interrupt do not have access to models of user tasks that would allow for such finer-grained temporal reasoning. To enable this reasoning, we have developed an integrated framework for specifying and monitoring user tasks. For task specification, our framework provides a language that supports expressive specification of tasks using a concise notation. For task monitoring, our framework provides an event database and handler that manages events from any instrumented application and a task monitor that observes a user's progress through specified tasks. We describe the design and implementation of our framework, showing how it can be used to specify and monitor practical, representative user tasks. We also report results from two user studies measuring the effectiveness of our existing implementation. The use of our framework will enable attention aware systems to consider a user's position in a task when reasoning about when to interrupt.
- Task models
- Task monitoring
ASJC Scopus subject areas
- Arts and Humanities (miscellaneous)
- Human-Computer Interaction