Design Frictions for Mindful Interactions: The Case for Microboundaries

Design frictions, a term found in popular media articles about user experience design, refer to points of difficulty occurring during interaction with technology. Such articles often argue that these frictions should be removed from interaction flows in order to reduce the risk of user frustration and disengagement. In this paper we argue that, in many scenarios, designing friction into interactions through the introduction of microboundaries, can, in fact, have positive effects. Design frictions can disrupt "mindless" automatic interactions, prompting moments of reflection and more "mindful" interaction. The potential advantages of intentionally introduced frictions are numerous: from reducing the likelihood of errors in data-entry tasks, to supporting health-behaviour change

Integrating knowledge of multitasking and interruptions across different perspectives and research methods

Multitasking and interruptions have been studied using a variety of methods in multiple fields (e.g., HCI, cognitive science, computer science, and social sciences). This diversity brings many complementary insights. However, it also challenges researchers to understand how seemingly disparate ideas can best be integrated to further theory and to inform the design of interactive systems. There is therefore a need for a platform to discuss how different approaches to understanding multitasking and interruptions can be combined to provide insights that are more than the sum of their parts. In this article we argue for the necessity of an integrative approach. As part of this argument we provide an overview of articles in this special issue on multitasking and interruptions. These articles showcase the variety of methods currently used to study multitasking and interruptions. It is clear that there are many challenges to studying multitasking and interruptions from different perspectives and using different techniques. We advance a six-point research agenda for the future of multi-method research on this important and timely topic

Diminished Control in Crowdsourcing: An Investigation of Crowdworker Multitasking Behavior

Obtaining high-quality data from crowds can be difficult if contributors do not give tasks sufficient attention. Attention checks are often used to mitigate this problem, but, because the roots of inattention are poorly understood, checks often compel attentive contributors to complete unnecessary work. We investigated a potential source of inattentiveness during crowdwork: multitasking. We found that workers switched to other tasks every five minutes, on average. There were indications that increasing switch frequency negatively affected performance. To address this, we tested an intervention that encouraged workers to stay focused on our task after multitasking was detected. We found that our intervention reduced the frequency of task-switching. It also improves on existing attention checks because it does not place additional demands on workers who are already focused. Our approach shows that crowds can help to overcome some of the limitations of laboratory studies by affording access to naturalistic multitasking behavior

Designing gamified rewards to encourage repeated app selection: Effect of reward placement

Designers commonly use gamification to improve the frequency of engagement with apps, but often fail to consider the impact of placement on reward value. As rewards tend to depreciate if delayed (termed temporal discounting), placing a reward further into the future can significantly affect its ability to motivate behaviour. We examine the most effective placement of gamified rewards so as to reduce discounting and to increase the frequency an application is used. In two online studies, users were asked to choose between fictional budget tracking applications that varied in the placement of either monetary (N=70) or gamified (N=70) rewards. In both experiments we found that people more frequently used the application that provided rewards before, rather than after, the task. As predicted by temporal discounting, our work suggests that placing rewards early in the interaction sequence leads to an improvement in the perceived value of that reward, motivating further selection. We discuss the findings in the context of designing effective reward structures to encourage more frequent app engagement