Information systems provide users with valuable information that is relevant to users’ tasks, as well as irrelevant information that is not helpful to the user. Irrelevant information become a distraction and distract the users from their current task, there by impairing performance. Guided by distraction-conflict theory, processing efficiency theory, attentional control theory, cognitive load theory and memory for goals theory, this study investigated the distraction effect by exploring the research question, “How do task-irrelevant distractions interrupt the users of information systems and influence their performance?”. To investigate how distractions from technology influence users’ performance, this experimental research examined the relationship between the variables of distraction, cognitive load, anxiety and task performance. Data were gathered through lab experiment using imotion eye tracking system. The major findings revealed that task-irrelevant distraction negatively influenced the users by increase anxiety and cognitive load as well as increase the time devoted to primary task. We also found that the cognitive load partially mediates the relationship between distraction and time spending on task.

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The complexity and broadening of competencies have led to a number of assessment frameworks that advocate for the use of rater judgment in direct observation of clinical performance. The degree to which these assessment processes produce scores that are valid, are therefore vitally dependent on a rater’s cognitive ability. A number of theories suggest that many of the cognitive structures needed to complete rating tasks are capacity limited and may therefore become a source of difficulty when rating demands exceed resources. This thesis explores the role of rating demands on the performance and behaviour of raters in the assessment of clinical competence and asks: in what way do rating demands associated with rating clinical performance affect rater performance and behaviour? I hypothesized that as rating demands increase, rating performance declines and raters engage in cognitive avoidance strategies in order to complete the task. I tested this hypothesis by manipulating intrinsic and extraneous sources of load for raters in the assessment of clinical performance. Results consistently demonstrated that intrinsic load, specifically broadening raters’ focus by increasing the number of dimensions to be considered simultaneously, negatively affected indicators of rating quality. However, extraneous demands failed to result in the same effect in 2 of 3 experiments. When we explored the cognitive strategies raters engage under high load conditions we learned of a number of strategies to reduce cognitive work, including idiosyncratically minimizing intrinsic demands (leading to poor inter-rater reliability) and active elimination of sources of extraneous load, explaining both findings. When we induced extraneous load in manner that could not be easily minimized by raters, we also found impairments in rater performance, specifically the provision of feedback. I conclude that rating demands, whether induced intrinsically or by extraneous sources, impair rater performance affecting both the utility of scores and the opportunity for learner development. Implications for health professions education and future directions are discussed. / Dissertation / Doctor of Philosophy (PhD)

Powered exoskeletons have the potential to revolutionize the labor workplace across many disciplines, from manufacturing to agriculture. However, there are still many barriers to adoption and widespread implementation of exoskeletons. One major research gap of powered exoskeletons currently is the development of a control framework to best cooperate with the user. This limitation is first in understanding the physical and cognitive interaction between the user and exoskeleton, and then in designing a controller that addresses this interaction in a way that provides both physical assistance towards completing a task, and a decrease in the cognitive demand of operating the device. This work demonstrates that multi-objective, optimization-based control can be used to provide a coincident implementation of autonomous robot control, and human-input driven control. A parameter called 'acceptance' can be added to the weights of the cost functions to allow for an automatic trade-off in control priority between the user and robot objectives. This is paired with an update function that allows for the exoskeleton control objectives to track the user objectives over time. This results in a cooperative, powered exoskeleton controller that is responsive to user input, dynamically adjusting control autonomy to allow the user to act to complete a task, learn the control objective, and then offload all effort required to complete the task to the autonomous controller. This reduction in effort is physical assistance directly towards completing the task, and should reduce the cognitive load the user experiences when completing the task. To test the hypothesis of whether high task assistance lowers the cognitive load of the user, a study is designed and conducted to test the effect of the shared autonomy controller on the user's experience operating the robot. The user operates the robot under zero-, full-, and shared-autonomy control cases. Physical workload, measured through the force they exert to complete the task, and cognitive workload, measured through pupil dilation, are evaluated to significantly show that high-assistance operation can lower the cognitive load experienced by a user alongside the physical assistance provided. Automatic adjustment in autonomy works to allow this assistance while allowing the user to be responsive to changing objectives and disturbances. The controller does not remove all mental effort from operation, but shows that high acceptance does lead to less mental effort. When implementing this control beyond the simple reaching task used in the study, however, the controller must be able to both track to the user's desired objective and converge to a high-assistance state to lead to the reduction in cognitive load. To achieve this behavior, first is presented a method to design and enforce Lyapunov stability conditions of individual tasks within a multi-objective controller. Then, with an assumption on the form of the input the user will provide to accomplish their intended task, it is shown that the exoskeleton can stably track an acceptance-weighted combination of the user and robot desired objectives. This guarantee of following the proper trajectory at corresponding autonomy levels results in comparable accuracy in tracking a simulated objective as the base shared autonomy approach, but with a much higher acceptance level, indicating a better match between the user and exoskeleton control objectives, as well as a greater decrease in cognitive load. This process of enforcing stability conditions to shape human-exoskeleton system behavior is shown to be applicable to more tasks, and is in preparation for validation with further user studies. / Doctor of Philosophy / Powered exoskeletons are robots that can be worn by users to physically aid them in accomplishing tasks. These robots differ in scale, from single-joint devices like powered ankle supports or lower-back braces for lifting, to large, multi-joint devices with a broad range of capabilities and potential applications. These multi-joint exoskeletons have been used in many applications such as medical rehabilitation robots, and labor-assisting devices for enhancing strength and avoiding injury. Broader use and adoption in industry could have a great positive impact on the experience of workers performing any heavy-labor tasks. There are still barriers to widespread adoption, however. When closely interacting with machinery like a powered exoskeleton, workers want guarantees of saftey, trust, and cooperation that current exoskeletons have not been able to provide. In fact, studies have shown that industrial devices capable of providing significant assistive force when accomplishing a task, also tend to impart additional, uncomfortable disturbance forces on the user. For example, a lower-body exoskeleton meant to help in lifting tasks might make the simple act of walking more difficult, both physically and mentally. There is a need for exoskeletons that are intuitively cooperative, and can provide both physical assistance towards completing a task and cognitive assistance that makes coordinating with the human user easier. In this dissertation we examine the control problem of powered exoskeletons. In the past, many powered exoskeleton controllers are direct, scripted controllers with exact objectives, or actions tied only to human input. To go beyond this, we leverage "multi-objective-control", originally designed for humanoid robots, which is capable of controlling the robot to accomplish multiple goals at the same time. This approach is the base on which a more complex controller can be created. We show first that the multi-objective control can be used to achieve human desired actions and robot autonomous control tasks at the same time, with a parameter to trade-off which actor, the human or the robot, has the priority control at that time. This framework has the capacity to allow the human to instruct the robot in tasks to accomplish, and then robot can fully mimic the user, offloading the physical effort required to accomplish the task. It is proposed that this offloading of effort from the user will also lower the cognitive load the user is under when actively commanding the exoskeleton. To test this hypothesis, a user study is conducted where human operators work with an upper-body powered exoskeleton to complete a simple reaching task. This study shows that on average, the more assistance the exoskeleton provides to the user, the lower their mental demand is. Additionally, when responding to new challenges or sudden disturbances, the robot can easily cooperate, balancing its own autonomy with the user's to allow the user to respond as they need to their changing environment, then resume active assistance when the change is resolved. Finally, to guarantee that the exoskeleton responds quickly and accurately to the user's intentions, a new strategy is derived to update the robot's internal objectives to match the users' goals. This strategy is based on the assumption that the exoskeleton knows what type of task the user is trying to complete. If this is true, then the exoskeleton can estimate the users objectives from the actions they task, and ensure assistance towards completing the task. This control design is proven in simulation, and in preparation for followup studies to evaluate the user experience of this improved strategy.

Denna studie undersökte hur smartklockors gränssnitt kan utformas för att upplevas användbara samt bidra till minimal kognitiv belastning under fysisk aktivitet. Smartklockors skärmar ställer andra krav på gränssnittet samt medför ett antal utmaningar för hur information kan presenteras på bästa sätt. Utöver detta brukar smartklockor användas i samband med fysisk aktivitet, som ställer höga krav på användarens uppmärksamhet. För att bibehålla hög kvalitet på träningen bör den kognitiva belastningen minska. För att undersöka detta har Cognitive Load Theory applicerats för att kunna optimera arbetsminnets kapacitet. Studien gjorde på personer i 20 års ålder. En kvalitativ datainsamling gjordes genom ett användartest och semistrukturerade intervjuer. Användartestet utfördes på en stationär cykel där deltagarna utförde ett antal uppgifter på en smartklocka. Efteråt skedde semistrukturerade intervjuer. Resultatet analyserades genom kategorisering och jämfördes med tidigare studier. Utifrån de mest förekommande resultaten skapades åtta designförslag. Resultaten visade att eliminering av viss information på gränssnitt kan minska den kognitiva belastningen samt höja användbarheten. Ett konsekvent gränssnitt skulle kunna minimera antal fel samt underlätta för användaren att korrigera fel. En tillämpning av de framtagna designförslagen kan eventuellt minimera den kognitiva belastningen vid interaktion med smartklockors gränssnitt vid fysisk aktivitet. Detta kan underlätta för användaren att fokusera på träningen samt uppleva klockan som mer användbar. / This study examined how an interface for smartwatches can be designed to be perceived as useful and reduce cognitive load during physical activity. Smartwatch screens have other demands on the interface and face several challenges regarding how information can be presented. In addition to this, smartwatches are often used in physical activity, which places high demands on user's attention. To maintain high-quality training, the cognitive load should be reduced. To investigate this, cognitive load theory has been applied to optimize the capacity of the working memory. The study looked at people in their 20s. Qualitative data collection was done through a user test and semi-structured interviews. The user test was done on a stationary bike, the participants performed several tasks on the smartwatch. The participants rode a stationary bicycle while performing tasks on a smartwatch, followed by semistructured interviews. The results were analyzed by thematization and compared with previous studies. Based on the most common results, eight design proposals were created. The results showed that by eliminating unnecessary information, the interface can reduce cognitive load and increase usability. A consistent interface could minimize the number of errors and make it easier for the user to correct errors. An application of the developed design proposals may minimize the external load when interacting with the smartwatch interface during physical activity. This can support users can focus on training and experience the watch as more useful.

För att lyckas lösa problem och använda kunskap behöver en person först ha lärt sig grundläggande kunskap om problemområdet. Sådant lärande kräver att den lärandes arbetsminne inte överbelastas med oändamålsenlig information. Studien undersöker effekten av lärandetekniken worked examples, som visats vara effektiv för att inte överbelasta arbetsminnet inom ämnen som fysik och matematik. Worked examples kommer från cognitive load theory och här undersöks teknikens effekt inom biologiundervisning, med fokus på ämnesområdet ekologi. Högstadieelevers kunskap inom ekologi mättes, varpå de inom undervisning antingen arbetade med worked examples eller instuderingsfrågor. Därefter mättes deras kunskapsnivå återigen, för att på så vis jämföra metodernas effekt på deltagarnas lärande. Elever som lärts med worked examples visade på en större kunskapsutveckling gällande snarlika uppgifter som de övat på, medan kunskapsutveckling för frågor med andra lösningsmetoder gav tvetydigt resultat. Tekniken worked examples har härmed visats sig vara en användbar teknik inom ämnesområdet ekologi inom biologiundervisningen. Den kan med fördel användas under initial-inlärningsfas inom biologiämnet för att hjälpa elever förvärva kunskap.

Remotely-controlled technologies are no longer limited to military applications, such as unmanned military airborne weapons or explosive diffuser robots. Nowadays we can see more and more of remotely controlled devices used as medical equipment, toys, and so forth. One of the most recent areas of interest is robotic telepresence, also known as Mobile Robot Presence (MRP), which provides the ability to interact socially and professionally with other people and even objects in remote locations. One of the known issues with using remotely-controlled devices is the cognitive overload which their operators (pilots) experience and MRP pilots are no exception. However, despite vast research on different ways to address this in military or medical scenarios, little has been done regarding MRPs. This thesis study aims to make a contribution in closing that gap by suggesting a method, developing a prototype implementing it; then conducting an empirical assessment of the method and the prototype as a part of a broader study on MRP, supported by Swedish Research Council. I have suggested a method comprised of a Secondary-task (ST) method and Subjective Rating Scales (SRS), in which the latter act as an evaluation method for the former. Both of them were used in an overarching study in search for the best control device amongst four chosen devices. I collected and analyzed secondary task performance data (e.g. response time, error rates), subjective user ratings, explicit rankings, and observations recordings. My analysis of the collected data shows that using a monitoring and response face recognition secondary task is a plausible method for the assessment of MRP pilot’s cognitive load.

In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.