A Predictive Model of Human Error based on User Interface Development Models and a Cognitive Architecture
A Predictive Model of Human Error based on User Interface Development Models and a Cognitive Architecture
复制标题
基于用户界面开发模型和认知架构的人为错误预测模型
DOI：
--
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Klaus
中科院分区：
文献类型：
--
作者：
M. Halbrügge;Michael Quade;Klaus
设备的概念。任务导向允许识别特别容易出错的子任务。面向设备的任务发生在用户界面需要额外的步骤时，这些步骤并不直接有助于用户的目标。它们包括但不限于初始化错误和完成后错误（例如，在收到钱后取出银行卡）。面向设备的任务的脆弱性通常通过使它们成为强制性的来抵消（例如，通过在银行卡被移除之前不分发钱），使得在没有专门的用户测试的情况下预测用户在给定界面的哪里会有问题变得更加困难。在本文中，我们将展示如何认知建模可以用来预测错误率的面向设备和面向任务的子任务相对于一个给定的应用程序逻辑。这个过程是通过利用用户界面Meta信息，基于模型的用户界面开发。
The concept of devicevs. task-orientation allows to identify subtasks that are especially prone to errors. Device-oriented tasks occur whenever a user interface requires additional steps that do not directly contribute to the users’ goals. They comprise, but are not limited to, initialization errors and postcompletion errors (e.g., removing a bank card after having received money). The vulnerability of device-oriented tasks is often counteracted by making them obligatory (e.g., by not handing out the money before the bank card has been removed), making it even harder to predict where users will have problems with a given interface without dedicated user tests. In this paper we show how cognitive modeling can be used to predict error rates of device-oriented and task-oriented subtasks with respect to a given application logic. The process is facilitated by exploiting user interface meta information from model-based user interface development.
通过从用户界面开发模型导出增强的认知模型来预测任务执行时间
DOI：
10.1145/2607023.2607033
发表时间：
2014
期刊：
Proceedings of the 2014 ACM SIGCHI symposium on Engineering interactive computing systems
影响因子：
--
作者：
Halbrügge;Engelbrecht;Albayrak;Möller
通讯作者：
Möller