Cognitive task analysis and interface design in a technical troubleshooting domain

A model of the interface design process is proposed that uses two interdependent levels of cognitive analysis: (a) study of the criterion task through the analysis of expert/novice differences, and (b) evaluation of the working user interface design through the application of practical interface analysis methodology (the GOMS model). This dual analysis is reviewed in the context of HYDRIVE, an intelligent tutoring system that has been designed to facilitate the development of aircraft hydraulics systems troubleshooting skills. Initial cognitive task analyses identified critical troubleshooting skills and procedures. However, even with an initial cognitive task analysis, the GOMS analysis resulted in significant and beneficial design changes.     

Cognitive task analysis: a proposal to model reactive behaviours

A tentative analysis and design of behaviours to be implemented in robots has been developed. For that purpose we have analysed the human behaviour of the person who executes the robot task. Afterwards we have transferred this analysis to the robot in charge of the same task. The cognitive task analysis, a powerful tool coming from cognitive psychology, has been used to study the behaviour granularity of the robots. This analysis is of paramount importance because the implementation of more sophisticated robot behaviours depends on the appropriate selection of the basic robot behaviours. The paper introduces a brief explanation of different types of robot architectures, and our motivation, to give, later on, some ideas concerning the cognitive task analysis and the used methods; finally, as an example, the behaviour of a postman is modelled by using those tools to get the necessary behaviours for a robot in charge of that task.     

Cognitive styles as an explanation of experts’ individual differences: A case study in computer-assisted troubleshooting diagnosis

Individual differences are a crucial aspect of field studies because of the consequences they can have on performance. However, in Cognitive Ergonomics, individual differences have mainly been interpreted as expertise effects. As can be noted from the literature, this limitation has led to difficulties in explaining differences between experts. Using a case study which identifies significant variations between expert performances [Jouglet, D., Piechowiak, S., Vanderhaegen, F., 2003. A shared workspace to support man-machine reasoning: application to cooperative distant diagnosis. Cognition, Technology & Work 5, 127–139], we attempt to go beyond the traditional approach based on expertise levels. Instead, we refer to the notion of cognitive styles. First, we consider methodological issues raised by a posteriori identification of cognitive styles within this diagnosis task. Second, we present the results of our analysis showing that individual differences are related to a particular dimension of cognitive style in which a balance between task requirements and cognitive resources is managed. Finally, we draw conclusions on the importance of cognitive styles in Cognitive Ergonomics.     

Cognitive simulation as a tool for cognitive task analysis

Cognitive simulations are runnable computer programs that represent models of human cognitive activities. We show how one cognitive simulation built as a model of some of the cognitive processes involved in dynamic fault management can be used in conjunction with small-scale empirical data on human performance to uncover the cognitive demands of a task, to identify where intention errors are likely to occur, and to point to improvements in the person-machine system. The simulation, called Cognitive Environment Simulation or CES, has been exercised on several nuclear power plant accident scenarios. Here we report one case to illustrate how a cognitive simulation tool such as CES can be used to clarify the cognitive demands of a problem-solving situation as part of a cognitive task analysis.     

Cognitive simulation as a tool for cognitive task analysis.

Cognitive simulations are runnable computer programs that represent models of human cognitive activities. We show how one cognitive simulation built as a model of some of the cognitive processes involved in dynamic fault management can be used in conjunction with small-scale empirical data on human performance to uncover the cognitive demands of a task, to identify where intention errors are likely to occur, and to point to improvements in the person-machine system. The simulation, called Cognitive Environment Simulation or CES, has been exercised on several nuclear power plant accident scenarios. Here we report one case to illustrate how a cognitive simulation tool such as CES can be used to clarify the cognitive demands of a problem-solving situation as part of a cognitive task analysis.     

Developing radical innovation capabilities: Exploring the effects of training employees for creativity and innovation

The resilience of organizations is increasingly dependent on their ability to develop radical innovation capabilities. While the literature documents numerous cases of organizations that already have radical innovation capabilities, the question of organizational devices that can be used to stimulate the emergence of such capabilities remains poorly addressed. Specifically, training for innovation and creativity has been proposed as a means to foster innovation capabilities; however, there has been little empirical evidence concerning the long‐term impacts of such training. To fill this gap, this article aims to document and evaluate the efforts of the research institute of a major Canadian energy company to provide training for innovation and creativity to initiate a radical innovation capability. We rely on a longitudinal study over the span of 18 months, where we observed 128 h of training and conducted 70 semi‐structured interviews with a sample of 40 researchers. We found that training for creativity and innovation has the potential to develop individual creative skills for exploration, to catalyze and federate collective action through common methods and a shared sense of what innovation entails, and to help create a common language and vocabulary between the different groups or divisions of an organization to talk about exploration.     

Cognitive skills training: lessons learned

This paper describes lessons we have learned about presenting cognitive skills training. We have used ShadowBox as our training approach (Klein and Borders in J Cogn Eng Decis Mak 10:268–280, 2016), but the lessons apply regardless of specific techniques employed. We analyze key takeaways and lessons learned throughout the course of multiple ShadowBox projects. We explain how the original ShadowBox mission statement has evolved based on these lessons learned. Recommendations are offered for others who are engaged in cognitive skills training.     

Optimization of decision networks in structured task environments

This paper considers the problem of determining the optimal distributed decision strategy for a team of decision-makers (DMs) arranged in an arbitrary acyclic organizational structure and controlling a complex structured process. Each DM has access to uncertain and partial information about the task environment and can control only a portion of it. We present an influence diagram model of the joint task-organization system and formulate the optimal team strategy in terms of a set of coupled hypothesis testing tasks at DMs. Specifically, we show that the scope of a local decision task is determined by the interaction of the task structure (what can be measured) and of the information access structure of the organization (who can measure what); while the control structure (who can influence what event) has an impact on the locally perceived costs associated with the decision options available. Theoretical results are illustrated via a numerical example, and connections to existing decision models are discussed     

Cognitive architectures: choreographing the dance of mental operations with the task environment

OBJECTIVE: In this article, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors and provide a cognitive engineering-oriented taxonomy of these architectures and a snapshot of their use for cognitive engineering. BACKGROUND: Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50-year preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. METHOD: The review defines three formative eras in cognitive engineering research: the 1950s, 1980s, and now. RESULTS: In the first era, the fledging fields of cognitive science and human factors emphasized characteristics of the dancer the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance (i.e., the dynamic interaction between mental operations and task environment). The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. CONCLUSIONS: Hybrid architectures present the best vector for introducing cognitive science theories into a renewed engineering-based human factors. APPLICATION: The taxonomy provided in this article may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.     

The troubleshooting task implementation in automotive chassis using virtual interactive technique and knowledge-based approach

In this study, a troubleshooting task model of automobile chassis is proposed. It integrates a task implementation method with virtual interactive techniques. Declarative knowledge entities make up the kernel of task model. It makes the task more controllable and automatable. Solution of the knowledge entities is directly used to support automotive chassis repair and maintenance. Furthermore, this system allows learners to operate a practical task module for troubleshooting through the Internet. The framework developed is not dependent on specific automobile style or software configuration and it uses open software (e.g. Java, MySQL, etc.) in the problem reasoning, virtual display and data storage. The framework can achieve the advantages and goals of (1) providing references for technicians in detection of chassis problems to promote repairing skills; (2) constructing a Web-based troubleshooting architecture of automotive chassis that can enhance learners’ (e.g. students, freshman, and drivers) knowledge and techniques; and (3) creating a prototype environment for distance learning to eliminate the limitation of space and time.     

On structured output training: hard cases and an efficient alternative

We consider a class of structured prediction problems for which the assumptions made by state-of-the-art algorithms fail. To deal with exponentially sized output sets, these algorithms assume, for instance, that the best output for a given input can be found efficiently. While this holds for many important real world problems, there are also many relevant and seemingly simple problems where these assumptions do not hold. In this paper, we consider route prediction, which is the problem of finding a cyclic permutation of some points of interest, as an example and show that state-of-the-art approaches cannot guarantee polynomial runtime for this output set. We then present a novel formulation of the learning problem that can be trained efficiently whenever a particular ‘super-structure counting’ problem can be solved efficiently for the output set. We also list several output sets for which this assumption holds and report experimental results.     

Task and training requirements analysis methodology (TTRAM): an analytic methodology for identifying potential training uses of simulator networks in teamwork-intensive task environments

A methodology designed to identify potential application areas for use of networked simulations is presented. The technique, known as task and training requirements analysis methodology (TTRAM), has been independently applied to the analysis of numerous US military aircraft simulator networking requirements, and appears to effectively discriminate tasks that are prone to skill decay, that are critical to mission success, that require high levels of internal and external teamwork, and that require additional training support.     

Scenarios and task analysis

A Critical Review of Carroll's book on scenario-based design is offered [Making Use: Scenario-Based Design of Human–Computer Interactions (2000)]. Carroll characterises scenarios as ‘stories about use’. The paper demonstrates that Carroll's proposals about scenarios and their use in software engineering can be fitted into the broader framework of task analysis in Human–Computer Interaction.     

Disruptive information system innovation: the case of internet computing

Abstract. Information system (IS) innovation can be defined as a novel organizational application of digital computer and information communication technologies (ICT). This paper discusses how modalities of applying ICT technologies in their form and scope exhibit radical breaks, which are introduced herein as ‘disruptive IS innovations’. This notion of disruptive IS innovation is developed by drawing upon and extending Swanson's (1994) theory of IS innovation as well as the concept of radical innovation. Disruptive innovations strongly influence the future trajectory of the adoption and use of ICT in organizational contexts and make the trajectory deviate from its expected course. In doing so, these disruptive innovations distinctly define what an IS is and how it is deployed in order to address current and future organizational and managerial prerogatives. Such changes are triggered breakthroughs in the capability of ICT that lead to the revision and expansion of associated cognitive models (frames) of computing. Disruptive IS innovations are those that lead to changes in the application of ICT that are both pervasive and radical. The pervasive nature implies that innovative activity spans all innovation subsets of the quad‐core model of IS innovation introduced herein. Innovation types include: IS use and development processes; application architecture and capability; and base technologies. Radical in nature, disruptive is innovations depart in significant ways from existing alternatives and lead to deviation from expected use and diffusion trajectory. This paper demonstrates the importance of a concept of disruptive IS innovation by investigating how changes triggered by internet computing (Lyytinen et al., 1998) meet the conditions of a disruptive IS innovation defined herein. The analysis also affirms both the pervasive and radical nature of internet computing and explains how internet computing has fundamentally transformed the application portfolio, development practices and IS services over time. The analysis demonstrates that, with the concept of disruptive IS innovation, we can fruitfully analyse ‘long’ waves of ICT evolution – an issue that has largely been overlooked in the IS community. On a theoretical plane, the paper advocates the view that we need to look beyond linear, unidirectional, and atomistic concepts of the diffusion of IS innovations where innovative activity takes places in a linear fashion by oscillating between small technological innovations and small organizational innovations. In contrast, IS innovation can exhibit fundamental discontinuity; we need to theoretically grasp such disruptive moments. The recent influx of innovation, spurred by internet‐based technology, offers one such moment.     

The cognitive task analysis methods for job and task design: review and reappraisal

This work examined the hypothesis that elderly people are less confident than young people in their own computer knowledge. This was done by having 49 young (M = 22.6 years) and 42 older (M = 68.6 years) participants to assess their global self-efficacy beliefs and to make item-by-item prospective (feeling-of-knowing: FOK) and retrospective (confidence level: CL) judgments about their knowledge in the two domains of computers and general knowledge. The latter served as a control domain. Item difficulty was equated across age groups in each domain. In spite of this age equivalence in actual performance, differences were found in FOK and CL ratings for computers but not for general knowledge, with older people being less confident than young people in their own computer knowledge. The greater age difference in ratings observed in the computer domain, as compared with the general domain, was even greater for the FOK than for the CL judgments. Statistical control of age differences in global self-efficacy beliefs in the computer domain (poorer in the older participants, but not in the general domain), eliminated age differences in FOK and CL judgments in the same domain. These findings confirm earlier ones. They suggest that underconfidence in their relevant abilities is one possible source of the difficulties that the elderly may encounter in mastering new computer technologies.     

The cognitive task analysis methods for job and task design: review and reappraisal

This paper reviews and reappraises the current research on the cognitive task analysis methodology for job or task design and analysis. Specifically, it classifies the current cognitive task analysis methods for job or task design and analysis, sorts out commonalities and differences among all these cognitive task analysis methodology for job and task design and analysis by conducting pros and cons comparisons, and provides guidelines in selecting cognitive task analysis methods for job and task design and analysis. Moreover, based on the current literature review, a validated human-centered information-processing model for cognitive task performance was developed based on human information processing theory. This new model focuses on identifying all cognitive aspects of human performance in technical work, with the goal of assisting job (re)design to increase human job performance.     

建筑技术创新风险的贝叶斯网络模型分析--以绿色建筑技术创新项目为例

传统的计算方法难以对建筑技术创新风险进行定量分析。通过专家先验知识与问卷调查数据相结合,可以建立建筑技术创新风险评估的贝叶斯信念网络模型。采用NETICA软件拟合样本数据,得到网络模型各个节点间的条件概率分布。在某绿色建筑技术创新项目中应用结果表明贝叶斯网络模型能够比较准确地实现对建筑技术创新风险的定量预测,与工程实际情况对比具有较好的符合性。