18 research outputs found

    Making a Task Difficult: Evidence That Device-Oriented Steps Are Effortful and Error-Prone

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    Errors in the execution of procedural tasks can have severe consequences. Attempts to ameliorate these slip errors through increased training and motivation have been shown to be ineffective. Instead, we identified the steps in a task procedure on which errors are most likely to occur, so that these might be designed out of the task procedure in the first place. Specifically, we considered whether device-oriented steps (i.e., steps in the task procedure that do not directly contribute to the achievement of the task goal) are more error-prone than task-oriented steps (i.e., steps that do directly contribute to the task goal). Two experiments are reported in which participants were trained to perform a novel procedural task. Across conditions, we manipulated the extent to which each step in the task procedure appeared to contribute to the achievement of the task goal (i.e., alternating the assignment of a task step between device- and task-oriented), while keeping the interface and underlying task procedure the same. Results show that participants made more errors and took longer to complete a task step when it played a device-oriented role rather than a task-orientated role. These effects were exacerbated by the introduction of a secondary task designed to increase working memory load, suggesting that when a task step plays a device-oriented role it is more weakly represented in memory. We conclude that device-oriented task steps are inherently problematic and should be avoided where possible in the design of task procedures

    Human Error Analysis in Software Engineering

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    As the primary cause of software defects, human error is the key to understanding, detecting and preventing software defects. This chapter first reviews the state of art of an emerging area: software fault defense based on human error mechanisms. Then, an approach for human error analysis (HEA) is proposed. HEA consists of two important components: human error modes (HEM) and an undated version of causal mechanism graphs (CMGs). Human error modes are the general erroneous patterns that humans tend to behave in a variety of activities. Causal mechanism graph provides a way to extract the error-prone contexts in software development, and link the contexts to general human error modes. HEA can be used at various phases of software development, for both defect detection and prevention purposes. An application case is provided to demonstrate how to use HEA

    The design with intent method: A design tool for influencing user behaviour

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    The official published version can be found at the link below.Using product and system design to influence user behaviour offers potential for improving performance and reducing user error, yet little guidance is available at the concept generation stage for design teams briefed with influencing user behaviour. This article presents the Design with Intent Method, an innovation tool for designers working in this area, illustrated via application to an everyday human–technology interaction problem: reducing the likelihood of a customer leaving his or her card in an automatic teller machine. The example application results in a range of feasible design concepts which are comparable to existing developments in ATM design, demonstrating that the method has potential for development and application as part of a user-centred design process

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

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    While experiments have been run online for some time with positive results, there are still outstanding questions about the kinds of tasks that can be successfully deployed to remotely situated online participants. Some tasks, such as menu selection, have worked well but these do not represent the gamut of tasks that interest HCI researchers. In particular, we wondered whether long-lasting, time-sensitive tasks that require continuous concentration could work successfully online, given the confounding effects that might accompany the online deployment of such a task. We ran an archetypal interruption experiment both online and in the lab to investigate whether studies demonstrating such characteristics might be more vulnerable to a loss of control than the short, time-insensitive studies that are representative of the majority of previous online studies. Statistical comparisons showed no significant differences in performance on a number of dimensions. However, there were issues with data quality that stemmed from participants misunderstanding the task. Our findings suggest that long-lasting experiments using time-sensitive performance measures can be run online but that care must be taken when introducing participants to experimental procedures

    Talk, text, tag? Understanding self-annotation of smart home data from a user’s perspective

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    Delivering effortless interactions and appropriate interventions through pervasive systems requires making sense of multiple streams of sensor data. This is particularly challenging when these concern people’s natural behaviours in the real world. This paper takes a multidisciplinary perspective of annotation and draws on an exploratory study of 12 people, who were encouraged to use a multi-modal annotation app while living in a prototype smart home. Analysis of the app usage data and of semi-structured interviews with the participants revealed strengths and limitations regarding self-annotation in a naturalistic context. Handing control of the annotation process to research participants enabled them to reason about their own data, while generating accounts that were appropriate and acceptable to them. Self-annotation provided participants an opportunity to reflect on themselves and their routines, but it was also a means to express themselves freely and sometimes even a backchannel to communicate playfully with the researchers. However, self-annotation may not be an effective way to capture accurate start and finish times for activities, or location associated with activity information. This paper offers new insights and recommendations for the design of self-annotation tools for deployment in the real world

    If Erring is Human, is System Use Divine?:Omission Errors During Post-Adoptive System Use

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    Our study contributes to the research on human error during IS use by studying the antecedents of the omission errors that occur during routine instances of computerized work. While attention lapses have been identified as the main mechanism leading to omission errors, we still know little about how such lapses come about during post-adoptive system use. To address this limitation, we draw our theoretical insights from theories of attention and prospective memory to illustrate how the different forms of system use carry the potential to explain patterns of human error. Accordingly, we distinguish between two forms of use history that can consist of features that are either related or unrelated to the execution of a focal task and examine their effects on the frequency of omission errors. We also examine the interaction effects of task variation on the aforementioned relationship. Our hypotheses are tested by analyzing log data associated with the use of a newly introduced mobile application in the context of a sailing sports event. Our results indicate that restricting one's system use on related task features reduces omission errors, whereas a use history based on unrelated task features produces the opposite effects. Further, task diversity positively moderates the relationship between a use history of unrelated features and omission errors, but has no significant moderating effect on the relationship between a use history of related features and omission errors. Our findings hold a number of implications for the literature on human error, and these are discussed alongside with the implications of our study for practitioners and system design

    An empirical investigation of post-completion error: A cognitive perspective.

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    Forgetting to retrieve your original after photocopying, forgetting to collect your card after a withdrawal from a cash machine, are examples of a specific type of omission error termed post-completion error (Byrne & Bovair, 1997). A post-completion error (PCE) is the omission of a "clean-up" step after the main goal of a task is fulfilled. The error phenomenon has the property of being infrequent but persistent it does not occur very often and, yet, it continues to occur now and again. This thesis is an empirical investigation of PCE to examine factors that provoke or mitigate the error. The investigation consists of two series of experiments. The first series of experiments is an extension of Byrne & Bovair's finding of the effect of high working memory demand on the increased occurrences of PCE. A novel paradigm was designed and adopted in the experiments it was found that PCE also occurs in problem-solving tasks, which impose a high demand on working memory load. Results from the experiments also suggest that the use of static visual cues may reduce the error rate. The second series of experiments investigates the effect of interruption on PCE in a procedural task paradigm. Based on the activation-based goal memory model (Altmann & Trafton, 2002) predictions were made on the effect of interruption position and duration on the error. Results show that PCE is more likely to occur with interruption occurring just before the post-completion step. Interruption occurring earlier in the task has no effect on PCE rate it was found to be the same as having no interruptions at all. Moreover, interruption as brief as 15 seconds was found to be disruptive enough to increase PCE rate. The same disruptive effect was also obtained for other non-PCEs. The scarcity and disparate nature of the existing theoretical approaches to PCE motivated a meta-theoretical analysis of PCE. The analysis has resulted in the identification of the major criteria required for an adequate account of PCE. Although a complete cognitive model of PCE is beyond the scope of the current thesis, the meta-theoretical analysis offers new insights into the understanding of PCE and aids future theoretical development. The current thesis constitutes a methodological advance in studying PCE. New factors that provoke or mitigate the occurrence of the error were identified through empirical investigations. New insights into the understanding of the error were also possible through a meta-theoretical analysis within a coherent theoretical structure

    The role of goal relevance in the occurrence of systematic slip errors in routine procedural tasks

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    Slip errors can have severe consequences but are notoriously difficult to reduce. Training, visual cues and increasing motivation are generally not effective in eliminating these slips. Instead, the approach this work takes is to identify which steps in a routine task are most error prone, so that these can be designed out of device interactions. In particular, device- and task-oriented steps are investigated. Device-oriented steps are "extra" steps imposed by the device that do not directly contribute towards the task goal. Conversely, task-oriented steps directly bring the user closer to their goal. The main hypothesis addressed in this work is that device-oriented steps are more problematic than task-oriented ones. The concepts of device- and task-oriented steps are investigated more closely, by analysing the literature on routine action and mental representations of different steps. The core diff erence between the steps is found to be how relevant a step is to the goal. This is further supported by two qualitative studies. A series of experimental studies investigates the cognitive mechanisms underlying device and task-oriented steps. This is addressed through six experiments that address error rates, step times, proportion of omissions and sensitivity to working memory load. Participants learned one of three routine tasks, with several carefully controlled device- and task-oriented steps. The results show that on device-oriented steps, error rates are higher, step times are longer, the proportion of omissions is greater, and working memory load has an increased effect. These findings support the hypothesis that activation levels are lower on device-oriented steps. The thesis concludes that a step's relevance to the task goal plays an important role in the occurrence of errors. This work has implications for both our understanding of routine procedural action as well as the design of devices
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