Cognitive complexity mitigation strategies are methods and approaches utilized by users to reduce the apparent complexity of problems thus making them easier to solve. These strategies often effective because they mitigate the limitations of human working memory and attention resources. Such cognitive complexity mitigation strategies are used throughout the design, development and operational processes of complex systems. Thus, a better understanding of these strategies, and methods that leverage them, can help improve the efficiency of such processes. Additionally, changes in the use of these strategies across various environments can identify cognitive differences in operating and developing across these contexts. This knowledge can help improve the effectiveness of cross-context user transfers by suggesting change management processes that incorporate the degree of cognitive difference across contexts. In order to document cognitive complexity mitigation strategies and the change in their usage, two application domains are studied. Firstly, cognitive complexity mitigation strategies used by designers during the engineering design process are found through an ethnographic immersion with a participating engineering firm, followed by an analysis of the designer's logbooks and validation interviews with the designers. Results include identification of five strategies used by the designers to mitigate design complexity. These strategies include Blackbox Modeling, Whitebox Modeling, Decomposition, Visualization and Prioritized Lists. The five complexity mitigation strategies are probed further across a larger sample of engineering designers and the usage frequency of these strategies is assessed across commonly performed engineering design activities which include the Selection, Configuration and Parametric activities. The results indicate the preferred use of certain strategies based on the engineering activity being performed. Such preferential usage of complexity mitigation strategies is also assessed with regards to Original and Redesign projects types. However, there is no indication of biased strategy usage across these two project characterizations. These results are an example of a usage-frequency based difference analysis; such analyses help identify the strategies that experience increased or reduced usage when transferring across activities. In contrast to the first application domain, which captures changes in how often strategies are used across contexts, the second application domain is a method of assessing differences based on how a specific strategy is used differently across contexts. This alternative method is developed through a project that aims to optimize the transfer of air traffic controllers across different airspace sectors. The method uses a previously researched complexity mitigation strategy, knows as a structure based abstraction, to develop a difference analysis tool called the Sector Abstraction Binder. This tool is used to perform cognitive difference analyses between air traffic control sectors by leveraging characteristic variations in how structure based abstractions are applied across different sectors. This Sector Abstraction Binder is applied to two high-level airspace sectors to demonstrate the utility of such a method.

<p> Automation has been known to provide both costs and benefits to experienced humans engaged in a wide variety of operational endeavors. Its influence on skill acquisition for novice trainees, however, is poorly understood. Some previous research has identified impoverished learning as a potential cost of employing automation in training. One prospective mechanism for any such deficits can be identified from related literature that highlights automation's role in reducing cognitive workload in the form of perceived task difficulty and mental effort. However three experiments using a combination of subjective self-report and EEG based neurophysiological instruments to measure mental workload failed to find any evidence that link the presence of automation to workload or to performance deficits resulting from its previous use. Rather the results in this study implicate engagement as an underlying basis for the inadequate mental models associated with automation-induced training deficits. The conclusion from examining these various states of cognition is that automation-induced training deficits observed in novice unmanned systems operators are primarily associated with distraction and disengagement effects, not an undesirable reduction in difficulty as previous research might suggest. These findings are consistent with automation's potential to push humans too far "out of the loop" in training. The implications of these findings are discussed.</p>

Cognitive complexity mitigation strategies are methods and approaches utilized by users to reduce the apparent complexity of problems thus making them easier to solve. These strategies often effective because they mitigate the limitations of human working memory and attention resources. Such cognitive complexity mitigation strategies are used throughout the design, development and operational processes of complex systems. Thus, a better understanding of these strategies, and methods that leverage them, can help improve the efficiency of such processes. Additionally, changes in the use of these strategies across various environments can identify cognitive differences in operating and developing across these contexts. This knowledge can help improve the effectiveness of cross-context user transfers by suggesting change management processes that incorporate the degree of cognitive difference across contexts. In order to document cognitive complexity mitigation strategies and the change in their usage, two application domains are studied. Firstly, cognitive complexity mitigation strategies used by designers during the engineering design process are found through an ethnographic immersion with a participating engineering firm, followed by an analysis of the designer's logbooks and validation interviews with the designers. Results include identification of five strategies used by the designers to mitigate design complexity. These strategies include Blackbox Modeling, Whitebox Modeling, Decomposition, Visualization and Prioritized Lists. The five complexity mitigation strategies are probed further across a larger sample of engineering designers and the usage frequency of these strategies is assessed across commonly performed engineering design activities which include the Selection, Configuration and Parametric activities. The results indicate the preferred use of certain strategies based on the engineering activity being performed. Such preferential usage of complexity mitigation strategies is also assessed with regards to Original and Redesign projects types. However, there is no indication of biased strategy usage across these two project characterizations. These results are an example of a usage-frequency based difference analysis; such analyses help identify the strategies that experience increased or reduced usage when transferring across activities. In contrast to the first application domain, which captures changes in how often strategies are used across contexts, the second application domain is a method of assessing differences based on how a specific strategy is used differently across contexts. This alternative method is developed through a project that aims to optimize the transfer of air traffic controllers across different airspace sectors. The method uses a previously researched complexity mitigation strategy, knows as a structure based abstraction, to develop a difference analysis tool called the Sector Abstraction Binder. This tool is used to perform cognitive difference analyses between air traffic control sectors by leveraging characteristic variations in how structure based abstractions are applied across different sectors. This Sector Abstraction Binder is applied to two high-level airspace sectors to demonstrate the utility of such a method.

Accuracy of the measurement data used for the decision making process or for shipboard operations and control is very important to ensure the reliability and survivability. The uncertainties present in measurement data need to be minimized for reliable system operation. In this work, a fuzzy logic based model is developed to deal with uncertainty in the meter data. Operational and historical parameters of the meters were used to determine a ‘trust’ value of individual meter. A fuzzy correction system for measurement data was used to generate an input dataset for a genetic algorithm based reconfiguration system. Additionally, with the goal of optimizing the performance of power system operator, the effects of Decision Support System (DSS) on the quality of decisions taken by the operator were examined. Unaided and aided interface prototypes were developed and usability tests were carried out on interface prototypes with users having knowledge of power systems.

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A comprehensive model of enterprise transformation is developed, along with a more specific model that includes multiple process factors inherent in transformation. The process factors are drawn from literature as well as primary research conducted for the dissertation. Specific considerations of time, cognitive attention, control and leadership are proposed to affect various outcome measures of transformation. This dissertation is conducted within the context of the retail industry. Financial analyses are included in order to provide an empirical basis for choice of retail industry context. Interviews with multiple retail executives acted as a source of primary, qualitative data with which to develop the model and inform the creation of a survey. A broad based empirical survey provided a second source of data with which to test the hypotheses about the impacts of multiple transformation factors on success metrics. Results indicate a large percentage of the variance in the outcomes of transformation can be explained with specific, actionable measures. Clarity of goals and plans, and strong leadership support are all shown to be important in affecting successful change. Additional factors, including flexibility in plans and goals, and leadership communication levels provide additional support for the hypotheses. Implications for theory and practice are elaborated, and future considerations for the research are discussed.

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<p>The purpose of this thesis was to integrate cognitive science into an existing organization of software systems development, and to display the benefits and importance of applying the theory and methodology of this interdisciplinary field onto this type of research. This was to be accomplished through participating in a project at ISD Datasystem AB, with the objective to investigate and develop new principles of man - machine interaction for fighter control, and build an appropriate workstation prototype. The participation spanned across the first iteration of the project’s development cycle, specified in accordance to the Rational Unified Process. A field study was conducted and several LoFi-prototypes of the graphical and physical man - machine interface (MMI) were made, as well as an evaluation of the developed prototype. The evaluation was performed with the help of end-users, who valuated the prototype in an inquiry and an interview after having performed a scenario interacting with it. The results showed that the prototype’s usability was highly valuated by the users.Data collected during the evaluation could also be used to guide further development of the prototype. The theoretical research and the empirical work in the project both showed that cognitive science is a valuable, and perhaps, an indispensable asset to software systems development, and that the knowledge and tools of cognitive science can be used in order to develop computer systems that are to be integrated in distributed man -machine systems of high complexity.</p>

The goal of this research is increased safety in aviation. Aviation is a highly automated and complex, as well as, safety critical human-machine system. The pilot communicates with the system via a human-machine interface in cockpit. In an alerting situation this interface is in part an auditory alerting system. Human errors are often consequences of actions brought about by poor design. Pilots complain that they may be both disturbed and annoyed of alerts, which may affect performance, especially in non-normal situations when the mental workload is high. This research is based on theories in ergonomics and cognitive engineering with the assumption that improved human performance within a system increase safety. Cognitive engineering is a design philosophy for reducing the effort required by cognitive functions by changing the technical interface, which may lead to improved performance. Knowledge of human abilities and limitations and multidisciplinary interrelated theories between humans, sounds and warnings are used. Several methods are involved in this research, such as literature studies, field studies, controlled experiments and simulations with pilots. This research defines design requirements for sounds appropriate in auditory alerts as Natural Warning Sounds. For example, they have a natural meaning within the user’s context, are compatible with the auditory information process, are pleasant to listen to (not annoying), are easy to learn and are clearly audible. A design process for auditory alerting systems is suggested. It includes methods of associability and sound imagery, which develop Natural Warning Sounds, and combines these with an appropriate presentation format. Associability is introduced and represents the required effort to associate sounds to their assigned alert function meaning. An associable sound requires less effort and fewer cognitive resources. Soundimagary is used to develop sound images. A sound image is a sound, which by its acoustics characteristics has a particular meaning to someone without prior training in a certain context. Simulations of presentation formats resulted in recommendations for cancellation capabilities and avoiding continuously repeated alerts. This research brings related theories closer to practice and demonstrates general methods that will allow designers, together with the users of the system, to apply them in their own system. / QC 20100910

This work presents the application of a cognitive engineering design method to the design of operational procedures and ground control station interfaces for uninhabited aerial vehicles (UAVs). Designing for UAV systems presents novel challenges, both in terms of selecting and presenting adequate information for effective teleoperation, and in creating operational procedures and ground control station interfaces that are robust to a range of UAV platforms and missions. Creating a coherent set of operating procedures, automatic functions and operator interfaces requires a systematic design approach that considers the system and the mission at different levels of abstraction and integrates the different element of the system. Several models are developed through the application of this cognitive engineering method. An analysis of the work of operating a UAV creates an abstraction decomposition space (ADS) model. The ADS helps identify the control tasks needed to operate the system. A strategies analysis then identifies methods for implementing these control tasks. The distribution of activities and roles between the human and automated components in the system is then considered in a social organization and cooperation analysis. These insights are applied to the design of coherent sets of operational procedures, ground control station interfaces and automatic functions for a specific UAV in support of a continuous target surveillance (CTS) mission. The importance of the coherence provided by the selected design method in the design of UAV operational procedures and ground control station interfaces is analyzed through a human in the loop simulation experiment for this mission. The results of the simulation experiment indicate that UAV controllers using coherently designed elements achieve significantly higher mission performance and experience lower workloads than those that when using incoherently matched elements.