Improving the Human–Computer Dialogue With Increased Temporal Predictability

Abstract

Objective: An experiment was conducted to investigate the impacts of length and variability of system response time (SRT) on user behavior and user experience (UX) in sequential computing tasks. Background: Length is widely considered to be the most important aspect of SRTs in human–computer interaction. Research on temporal attention shows that humans adjust to temporal structures and that performance substantially improves with temporal predictability. Method: Participants performed a sequential task with simulated office software. Duration and variability, that is, the number of different SRTs, was manipulated. Lower variability came at the expense of on average higher durations. User response times, task execution times, and failure rates were measured to assess user performance. UX was measured with a questionnaire. Results: A reduction in variability improved user performance significantly. Whereas task load and failure rates remained constant, responses were significantly faster. Although a reduction in variability came along with, on average, increased SRTs, no difference in UX was found. Conclusion: Considering SRT variability when designing software can yield considerable performance benefits for the users. Although reduced variability comes at the expense of overall longer SRTs, the interface is not subjectively evaluated to be less satisfactory or demanding. Time design should aim not only at reducing average SRT length but also at finding the optimum balance of length and variability. Application: Our findings can easily be applied in any user interface for sequential tasks. User performance can be improved without loss of satisfaction by selectively prolonging particular SRTs to reduce variability.