abstract: Intuitive decision making refers to decision making based on situational pattern recognition, which happens without deliberation. It is a fast and effortless process that occurs without complete awareness. Moreover, it is believed that implicit learning is one means by which a foundation for intuitive decision making is developed. Accordingly, the present study investigated several factors that affect implicit learning and the development of intuitive decision making in a simulated real-world environment: (1) simple versus complex situational patterns; (2) the diversity of the patterns to which an individual is exposed; (3) the underlying mechanisms. The results showed that simple patterns led to higher levels of implicit learning and intuitive decision-making accuracy than complex patterns; increased diversity enhanced implicit learning and intuitive decision-making accuracy; and an embodied mechanism, labeling, contributes to the development of intuitive decision making in a simulated real-world environment. The results suggest that simulated real-world environments can provide the basis for training intuitive decision making, that diversity is influential in the process of training intuitive decision making, and that labeling contributes to the development of intuitive decision making. These results are interpreted in the context of applied situations such as military applications involving remotely piloted aircraft. / Dissertation/Thesis / Ph.D. Psychology 2011

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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.

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The thesis begins by examining the evolution of human performance modeling from the initial stimulus-response methods introduced during the industrial revolution to model factory worker productivity, continues with a discussion of the information processing model where human cognition was modeled as a series of actions carried out in a predefined order, and ends with the concept of cognitive control whereby cognition is not considered a context-free mental process but modeled as an individual's ability to maintain control under varying contexts and to counter the effects of disturbances. The results from a preliminary evaluation conducted to determine if CCMs could be measured and if they provided any additional insight cognitive work are presented, and reveal that CCMs could be measured and the self-assessed CCM varied as predicted. A design process is developed which utilizes the CCMs as representing specific patterns of activity, thus specifying the design requirements. Following this design process, a prototype is created and evaluated using a controlled experiment to examine the effectiveness of the CWSS. The experiment examines performance, workload, and patterns of activity, and has several interesting findings. The first is that performance was independent of the almost all of the predictors and covariates including participant's Self-assessed CCM, with the exception of CCM transitions. As in the preliminary study, participants who reported transitioning between CCMs also reported decreased performance, increased frustration and actually performed worse. Second, perceived performance varied linearly with a participant's self-assessed CCM, but not with the actual performance. Third, participants report lower levels of effort when using a CWSS DM that matched their operational CCM. Finally, the design process successfully created a CWSS with DMs which support strategic and tactical CCMs. Unfortunately, no specific performance improvements were found for cases where the participant's CCM matched the DM as hypothesized, calling into question the effectiveness of creating different design modes for performance improvement. This thesis presents two methods for measuring CCMs: one direct single scale and one indirect composite scale. The measurements correlate highly. Both have a high degree of face validity and user acceptance. In the end, the composite measure may be a more robust measure of CCM because it provides a greater degree of diagnosticity by specifically inquiring after different aspects of CCM and is less susceptible to an individual's interpretation of the relative importance of the multiple dimensions of CCMs included in the definitions.

abstract: Clinicians confront formidable challenges with information management and coordination activities. When not properly integrated into clinical workflow, technologies can further burden clinicians’ cognitive resources, which is associated with medical errors and risks to patient safety. An understanding of workflow is necessary to redesign information technologies (IT) that better support clinical processes. This is particularly important in surgical care, which is among the most clinical and resource intensive settings in healthcare, and is associated with a high rate of adverse events. There are a growing number of tools to study workflow; however, few produce the kinds of in-depth analyses needed to understand health IT-mediated workflow. The goals of this research are to: (1) investigate and model workflow and communication processes across technologies and care team members in post-operative hospital care; (2) introduce a mixed-method framework, and (3) demonstrate the framework by examining two health IT-mediated tasks. This research draws on distributed cognition and cognitive engineering theories to develop a micro-analytic strategy in which workflow is broken down into constituent people, artifacts, information, and the interactions between them. It models the interactions that enable information flow across people and artifacts, and identifies dependencies between them. This research found that clinicians manage information in particular ways to facilitate planned and emergent decision-making and coordination processes. Barriers to information flow include frequent information transfers, clinical reasoning absent in documents, conflicting and redundant data across documents and applications, and that clinicians are burdened as information managers. This research also shows there is enormous variation in how clinicians interact with electronic health records (EHRs) to complete routine tasks. Variation is best evidenced by patterns that occur for only one patient case and patterns that contain repeated events. Variation is associated with the users’ experience (EHR and clinical), patient case complexity, and a lack of cognitive support provided by the system to help the user find and synthesize information. The methodology is used to assess how health IT can be improved to better support clinicians’ information management and coordination processes (e.g., context-sensitive design), and to inform how resources can best be allocated for clinician observation and training. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2017

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This thesis explores home energy management (HEM), an emerging field for interface design and sustainability. Section 1 introduces HEM’s broader context. In Section 2, I review the literature surrounding HEM. Section 3 outlines the usability study on the ecobee Smart Thermostat, to evaluate the technology’s ease-of-use, and better understand users’ experience with current HEM technology. Section 4 describes a “Critical Making” workshop, where participants investigated HEM through material interaction and discussion. Section 5 describes and evaluates the potential design spaces gleaned from previous sections. In Section 6, I return to the literature to investigate key concepts underlying the design intervention for the chosen design space. Section 7 describes my design intervention and experimental evaluation. In Section 8, I present the study results, which suggest enhanced display labelling had a significant and directional effect on user-selected temperatures. In Section 9, I discuss these results, study limitations, and make conclusions and recommendations.