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Enhanced Task Modelling for Systematic Identification and Explicit Representation of Human Errors

机译:增强的任务建模,用于系统识别和明确表示人类错误

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Task models produced from task analysis, are a very important element of UCD approaches as they provide support for describing users goals and users activities, allowing human factors specialists to ensure and assess the effectiveness of interactive applications. As user errors are not part of a user goal they are usually omitted from tasks descriptions. However, in the field of Human Reliability Assessment, task descriptions (including task models) are central artefacts for the analysis of human errors. Several methods (such as HET, CREAM and HERT) require task models in order to systematically analyze all the potential errors and deviations that may occur. However, during this systematic analysis, potential human errors are gathered and recorded separately and not connected to the task models. Such non integration brings issues such as completeness (i.e. ensuring that all the potential human errors have been identified) or combined errors identification (i.e. identifying deviations resulting from a combination of errors). We argue that representing human errors explicitly and systematically within task models contributes to the design and evaluation of error-tolerant interactive system. However, as demonstrated in the paper, existing task modeling notations, even those used in the methods mentioned above, do not have a sufficient expressive power to allow systematic and precise description of potential human errors. Based on the analysis of existing human error classifications, we propose several extensions to existing task modelling techniques to represent explicitly all the types of human error and to support their systematic task-based identification. These extensions are integrated within the tool-supported notation called HAMSTERS and are illustrated on a case study from the avionics domain.
机译:任务分析生产的任务模型是UCD方法的一个非常重要的元素,因为它们提供了描述用户目标和用户活动的支持,允许人为的因素专家确保和评估交互式应用的有效性。由于用户错误不是用户目标的一部分,它们通常从任务描述中省略。然而,在人类可靠性评估领域,任务描述(包括任务模型)是用于分析人类错误的中央文物。几种方法(例如Het,Cream和Hert)需要任务模型,以便系统地分析可能发生的所有潜在误差和偏差。然而,在这种系统分析中,潜在的人为错误被收集和单独记录,并未连接到任务模型。这种非整合带来了完整性的问题(即确保已经确定了所有潜在的人为错误)或组合错误识别(即识别由错误组合产生的偏差)。我们认为,在任务模型中明确和系统地代表人类错误有助于耐堵塞交互式系统的设计和评估。然而,如本文所示,现有的任务建模符号,即使是上述方法中使用的任务建模符号,也没有足够的表现力,以允许系统和精确描述潜在的人类误差。基于对现有人为错误分类的分析,我们提出了几种扩展到现有的任务建模技术,以明确表示人为错误的所有类型,并支持其基于系统的任务的识别。这些扩展集成在名为仓鼠的工具支持的符号内,并在航空电子域中的案例研究中进行说明。

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