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

机译:用于系统识别和人为错误的明确表示的增强型任务建模

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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:任务分析产生的任务模型是UCD方法的一个非常重要的组成部分,因为它们为描述用户目标和用户活动提供了支持,使人为因素专家可以确保和评估交互式应用程序的有效性。由于用户错误不是用户目标的一部分,因此通常从任务描述中将其省略。但是,在人类可靠性评估领域,任务描述(包括任务模型)是分析人为错误的主要人工制品。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错误和偏差。但是,在此系统分析过程中,潜在的人为错误被单独收集和记录,并且未与任务模型关联。这样的非集成带来诸如完整性(即,确保已经识别出所有潜在的人为错误)或组合的错误标识(即,标识由错误的组合导致的偏差)之类的问题。我们认为,在任务模型中明确,系统地表示人为错误有助于设计和评估容错交互系统。但是,正如本文所证明的那样,即使是上述方法中使用的现有任务建模符号,也没有足够的表达能力,无法对潜在的人为错误进行系统且精确的描述。在对现有人为错误分类进行分析的基础上,我们提出了对现有任务建模技术的若干扩展,以明确表示所有类型的人为错误并支持其基于任务的系统性识别。这些扩展集成在工具支持的称为HAMSTERS的表示法中,并在航空电子领域的案例研究中得到了说明。

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