Recovering from an interruption: Investigating speed−accuracy trade-offs in task resumption behavior.

Abstract

Interruptions are disruptive because they take time to recover from, in the form of a resumption lag, and lead to an increase in the likelihood of errors being made. Despite an abundance of work investigating the effect of interruptions on routine task performance, little is known about whether there is a link between how quickly a task is resumed following an interruption (i.e., the duration of the postinterruption resumption lag) and the likelihood that an error is made. Two experiments are reported in which participants were interrupted by a cognitively demanding secondary mental arithmetic task while working on a routine sequential data-entry task. In Experiment 1 the time-cost of making an error on the primary task was varied between conditions. When errors were associated with a high time-cost penalty, participants made fewer errors and resumed the primary task more slowly than when errors were associated with a low time-cost penalty. In Experiment 2 participants were prohibited from resuming the primary task quickly by a 10-s system lockout period following the completion of the interrupting task. This lockout period led to a significant reduction in resumption errors because the lockout prohibited fast, inaccurate task resumptions. Taken together, our results suggest that longer resumption lags following an interruption are beneficial in terms of reducing the likelihood of errors being made. We discuss the practical implications of how systems might be designed to encourage more reflective task resumption behavior in situations where interruptions are commonplace. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Home is Where the Lab is: A Comparison of Online and Lab Data From a Time-sensitive Study of Interruption

“…In the first set of analyses (Processed data) we use data cleaning techniques to minimize the impact of outliers on our results. These techniques are standard both in laboratory investigations of interruptions (e.g., Brumby, Cox, Back, & Gould, 2013) and in online experiments. Indeed, in the crowdsourcing domain, tools have been developed specifically for aiding this process (e.g., Rzeszotarski & Kittur, 2012).…”

Interrupted by pain: An anatomy of pain-contingent activity interruptions

“…Retrieval depends on how well this information had been 7 encoded to memory during the interruption lag [33], characteristics of goal B-related activity, but also on conditions during the resumption lag, such as the presence of reminders indicating where the activity should be resumed from [32]. The duration of the resumption lag has been shown to influence quality of performance after resumption, with longer resumption lags decreasing the probability of errors [7]. Facing difficulties with retrieval, however, may decrease the probability to resume the task.…”

Modelling the Interruption on HCI Using BDI Agents with the Fuzzy Perceptions Approach: An Interactive Museum Case Study in Mexico

“…We can compare the proposed research with other recovery techniques [44,45], analysing ways to resume after interruption; through comparison, we can see that our research improves and strengthens the interaction in order to increase attention in the exhibition. Moreover, we analysed if negative effects of the interruption are avoided if the user's performance increases having a complete and uninterrupted interaction.…”