Steps towards a system for inferring the interruptibility status of knowledge workers (original) (raw)
Related papers
Predicting human interruptibility with sensors
2005
Abstract A person seeking another person's attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations.
Employing Consumer Wearables to Detect Office Workers' Cognitive Load for Interruption Management
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Office workers' productivity and well-being are reduced by interruptions, especially if they occur during an inconvenient moment. Interruptions in phases of high cognitive load are more disruptive than in phases of low cognitive load. Based on an explorative study, we suppose the presence of social codes that signal office workers' interruptibility. We propose a system that utilizes the cognitive load of an office worker to indicate situations suitable for interruptions. The cognitive load is inferred from office workers' physiological state measured by a consumer smartwatch. The system adapts an externally mounted smart device to indicate if the office worker is interruptible. To predict the cognitive load, we trained a classifier with ten office workers and achieved an accuracy between 66% and 86%. In order to validate the classifier's accurateness in an office setting, we performed a verification study with five office workers: We systematically triggered interrup...
Reducing Interruptions at Work
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Due to the high number and cost of interruptions at work, several approaches have been suggested to reduce this cost for knowledge workers. These approaches predominantly focus either on a manual and physical indicator, such as headphones or a closed office door, or on the automatic measure of a worker's interruptibilty in combination with a computer-based indicator. Little is known about the combination of a physical indicator with an automatic interruptibility measure and its long-term impact in the workplace. In our research, we developed the FlowLight, that combines a physical traffic-light like LED with an automatic interruptibility measure based on computer interaction data. In a large-scale and long-term field study with 449 participants from 12 countries, we found, amongst other results, that the FlowLight reduced the interruptions of participants by 46%, increased their awareness on the potential disruptiveness of interruptions and most participants never stopped using it.
Predicting human interruptibility with sensors: a Wizard of Oz feasibility study
2003
Abstract A person seeking someone else's attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, today's computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user.
Eighth International Symposium on Wearable Computers, 2004
For the estimation of user interruptability in wearable and mobile settings, we propose in to distinguish between the users' personal and social interruptability. In this paper, we verify this thesis with a user study on 24 subjects. Results show that there is a significant difference between social and personal interruptability. Further, we present a novel approach to estimate the social and personal interruptability of a user from wearable sensors. It is scalable for a large number of sensors, contexts, and situations and allows for online adaptation during run-time. We have developed a wearable platform, that allows to record and process the data from a microphone, 12 body-worn 3D acceleration sensors, and a location estimation. We have evaluated the approach on three different data sets, with a maximal length of two days.
Human Interruption Management in Workplace Environments: An Overview
Engineering, Technology & Applied Science Research, 2020
Interruptions are unexpected breaks that introduce new tasks on top of ongoing activities. In work environments, interruptions occur when operators and decision-makers have to deal simultaneously with several stimuli and information sources and have to make decisions so as to maintain the flow of activities at a satisfactory level of performance or quality of service. The causes and effects of interruptions and their subsequent management strategies in workplace environments have been researched in the past, however, only a few review articles are available to report on current advances in this area, to analyze contributions, and to highlight open research directions. This paper offers an up-to-date review and a framework for interruptions and interruption management strategies. The current approaches to identify, report, and manage interruptions in a variety of workplace environments are reviewed and a description of environmental characteristics that favor the occurrence of interr...
Awareness Displays and Interruptions in Teams
SSRN Electronic Journal, 2000
Work life is filled with interruptions, most of which benefit the interrupter at the expense of the one being interrupted. We conducted an experiment to determine whether peripheral awareness information about a remote collaborator's workload aids in timing interruptive communication. Results indicate motivation to use the display exists, irrespective of whether both parties are rewarded as part of a team or not. When an informational display was present, a majority of participants used it to time their communication sensitively. We found that a display with an abstract representation of a collaborator's workload is best; it leads to better timing of interruptions without overwhelming the interrupter.
Advances in Intelligent Systems and Computing, 2016
This study seeks to determine if it is necessary for a software agent to monitor the communication channel between a human operator and human collaborators to effectively detect appropriate times to convey information or "interrupt" the operator in a collaborative communication task. The study explores the outcome of overall task performance and task time of completion (TOC) at various delivery times of periphery task interruptions. A collaborative, goaloriented task is simulated via a dual-task where an operator participates in the primary collaborative communication task and a secondary keeping track task. User performance at various interruption timings: random, fixed, and humandetermined (HD) are evaluated to determine whether an intelligent form of interrupting users is less disruptive and benefits users' overall interaction. There is a significant difference in task performance when HD interruptions are delivered in comparison with random and fixed timed interruption. There is a 54% overall accuracy for task performance using HD interruptions compared to 33% for fixed interruptions and 38% for random interruptions. These results are promising and provide some indication that monitoring a communication channel or adding intelligence to the interaction can be useful for the exchange.
Sensemaking tasks are difficult to accomplish with limited time and attentional resources because analysts are faced with a constant stream of new information. While this information is often important, the timing of the interruptions may detract from analyst's work. In an ideal world, there would be no interruptions. But that is not the case in real world sensemaking tasks. So, in this study, we explore the value of timing interruptions based on an analyst's state of arousal as detected by Electrodermal activity derived form galvanic skin response (EDA). In a laboratory study, we compared performance when interruptions were timed to occur during increasing arousal, decreasing arousal, at random intervals or not at all. Analysts performed significantly better when interruptions occurred during periods of increasing arousal than when they were random. Further, analysts rated process component of team experience significantly higher also during periods of increasing arousal than when they were random. Self-reported workload was not impacted by interruptions timing. We discuss how system designs could leverage inexpensive off-the-shelf wrist sensors to improve interruption timing.
CO-WORKER: Toward Real-Time and Context-Aware Systems for Human Collaborative Knowledge Building
Cognitive Computation, 2012
The information exchange occurring during human interactions, conveyed through verbal and nonverbal communication modes builds up a newshared knowledge among the interacting people. A current automatic meeting assistance system is just able to store such an exchange (for successive offline processing), while it would be valuable developing automatic tools that provide appropriate support as it takes place. Currently, the international scientific community is strongly committed towards the implementation of intelligent instruments able to recognize, and process in real time relevant interactional signals in order to provide timely support to the happening interaction. This work will argue on an even more comprehensive paradigm for collaborative computer support to human interaction, not adequately addressed in the literature so far, concerning the implementation of Human-Computer Interaction (HCI) systems able to process in real time multimodal signals, to infer contextual information, and support in a collaborative way human interaction in-group activities, such as learning, discussion, work cooperation, decision-making, and problem solving. Such systems should act as co-workers, actively cooperating and contributing to the group's knowledge building, and pretending to share with the group, significances and individual potentialities rather than act as passive data storing devices. In carrying out their functions, these HCI systems will be placed on a group cognitive level, where individual purposes, actions, and emotions are mediated by the group interaction and meanings are mainly built through the group shared knowledge and experience.