Browsing by Author "David Kaber, Committee Chair"

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    An Accessible Cognitive Modeling Tool for Evaluation of Human-Automation Interaction in the Systems Design Process.
    (2010-11-04) Gil, Guk Ho; David Kaber, Committee Chair; Robert St. Amant, Committee Member; Michael Feary, Committee Member; David Dickey, Committee Member; Yuan-Shin Lee, Committee Member
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    Analysis of Patient-Robot Interaction Using Statistical and Signal Processing Methods.
    (2010-09-22) Swangnetr, Manida; Ezat Sanii, Committee Chair; Yuan-Shin Lee, Committee Chair; David Kaber, Committee Chair; Jeffrey Thompson, Committee Member; Gracious Ngaile, Committee Member
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    Application of Deterministic and Stochastic Components of the Ocular Dynamic System.
    (2010-08-30) Wang, Xuezhong; Simon Hsiang, Committee Chair; David Kaber, Committee Chair; Peter Bloomfield, Committee Member; Yuan-Shin Lee, Committee Member; Lori Holcomb, Committee Member
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    Cognitive Task Analyses for Life Science Automation Training Program Design.
    (2008-08-11) Green, Rebecca; Regina Stoll, Committee Member; Robert St. Amant, Committee Member; Christopher Mayhorn, Committee Co-Chair; David Kaber, Committee Chair
    The purpose of this study was to develop a systematic approach to the translation of Cognitive Task Analyses (CTAs), including Goal Directed Task Analysis (GDTA) and Abstraction Hierarchy (AH) models, into a Situation Awareness (SA) based training program for operators of High-throughput (biological) screening (HTS) systems. Traditional on-the-job (OTJ) training of new HTS operators usually consists of several weeks of assisting a lead biochemist to become familiar with methods and automated systems. Unfortunately, this approach to training is typically unstructured and learning results may be highly variable. In order to design instruction to support learning of cognitive processes as part of HTS, the information demands engendered by the task need to be identified. This can be achieved using CTAs as the basis for training program design. Various CTA methods, including the Critical Decision Method (CDM) and Precursor-Action-Results-Interpretation, have been used to develop training. However, no standardized methods exist for relating the outcomes of the integration of multiple CTA methods to support training program design. This study, therefore, combined information requirements from a GDTA and system resource requirements identified through AH models to establish content on HTS processes for delivery through an electronic training program. The goals and sequences of task steps within the training program were identified by the GDTA. The use of AH models of the HTS system provided a method for determining the purpose and function of the software and devices relative to different operator functional requirements. This combination of information from the CTAs provided a systematic approach for specifying training strategies and parameters. The training program presented learners with content for development of the three levels of operator SA (perception, comprehension, and projection) and knowledge structures pertaining to HTS system operations. Following development of the prototype electronic training program and the comparison traditional training program, an evaluation occurred through a three-part survey with comparison to the traditional lab training provided to expert operators of an HTS system. The evaluation incorporated two knowledge assessment tests, a usability survey, and a survey of the effectiveness of the SA elements of the training program. Results provided preliminary evidence that a CTA-based training program can improve operators' knowledge structures beyond OTJ training. Furthermore, operator performance on SA questions indicated improvements in knowledge structures associated with perceptual elements, comprehension of those elements, and projection of the future states of HTS systems. Additionally, since experience can lead to differences in operator mental models pertaining to HTS systems, the effect of two types of overall experience and individual task experience were measured. Results indicated that the CTA-based training program was effective in providing improved SA knowledge and general knowledge structures for HTS operators beyond their initial knowledge of the system (i.e., considering work experience and education). A heuristic-based evaluation of both training programs identified few unique usability problems, suggesting the usability of the training programs did not interfere with the development of learner knowledge structures. Finally, on the basis of these results, a set of general guidelines for the design of the CTA-based training programs was developed. These guidelines included methods for structuring the components of the training program to support the three levels of SA and the amount of text that should be shown for each task.
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    Development and Empirical Assessment of a Model of Situation Awareness for Multitasking with Locomotion
    (2007-01-19) Sheik Nainar, Mohamed Ashraf Ali; David Kaber, Committee Chair; Simon Hsiang, Committee Co-Chair; Gary Mirka, Committee Member; Jason Osborne, Committee Member
    Human locomotion has long been considered an overly practiced motor behavior. However, recent research has revealed a demand of locomotion on attentional resources, especially when performed during multitasking. Situation Awareness (SA), a cognitive construct critical to decision making and performance in complex tasks, has been shown to be important while multitasking with cognitive and physical workloads. No research has been conducted on the role of SA during locomotion with perturbations (e.g., slips and trips) and concurrent cognitive task performance (e.g., walking and talking on cell phone). The primary objective of this research was to develop a model of SA for multitasking with locomotion to conduct an empirical study to assess the validity of the proposed model for explaining proactive gait control in response to locomotion hazards. To support the empirical work, a virtual reality locomotion interface (VRLI) was developed to present walkers with realistic virtual locomotion environments (VLE) similar to everyday locomotion activities. An initial version of the VRLI consisted of a computer controlled treadmill, a head mounted display (HMD), and a graphical workstation running the VLEs and controlling the treadmill, based on participant movement using motion tracking sensors. The VRLI setup was validated through a pilot study that compared overground walking with treadmill walking in a VLE. Results showed similarities in walking characteristics between the conditions. Based on the pilot study, further enhancements were made to the setup. These included using a rear projection screen with a stereo projector and light-shutter goggles and a new treadmill with an embedded force plate (under the belt) for collecting gait ground reaction forces (GRF) and center of pressure (COP) data. Using the enhanced VRLI, an experiment was conducted to evaluate the utility of SA during locomotion and validate the proposed model of SA for proactive gait control for responding to locomotion hazards. In this experiment, the controlled variables included navigation aid type (NT), a priori knowledge (AK) and perturbation cueing (PC). NT consisted of two levels &8212; map-based navigation (MBN) and instruction-based navigation (IBN) and was manipulated between-subjects. AK consisted of three levels, low, medium and high, and was also manipulated between-subjects. The AK manipulation involved controlled the initial exposure of the walker to the test VLE and hence controlled their mental model development on the task environment. The low AK group was trained with a low fidelity VLE and medium AK and high AK groups were trained with a high-fidelity VLE, but only the latter group experienced a perturbation. The PC variable was manipulated within-subjects and it consisted of combinations of visual cueing and physical cueing of locomotion hazards forming four levels — visual only, physical only, visual plus physical and no cueing. Dependent variables measured included a battery of GRF and COP variables along with response accuracy to SA probes presented using a real-time probing technique. Twelve males and twelve females from the NCSU student population participated in the experiment and performed the navigation task following four different routes in the VLE. Results revealed participant proactive preparation for locomotion hazards, as observed through significant changes in GRF and COP measures. Effects included the nature of cueing of the perturbation and prior exposure to a trial with a perturbation involving visual cueing. There was also a complex interaction between NT, AK and PC that revealed greater participant proactive control during MBN with higher AK under visual plus physical cueing compared to IBN with lower AK under visual only cueing. SA accuracy under MBN was higher for probes requiring subjects to project VLE future states, as compared to IBN. Analysis of correlations between SA performance and gait response measures in five steps leading up to participants encountering perturbations revealed a negative relationship between SA and weight acceptance (at heel strike) with each step closer to the perturbation. The correlation was also significantly affected by the manipulated variables (list variables here in parentheses) and their higher order interactions. The study revealed that higher SA performance was associated with greater proactive control (decreased weight acceptance — flat footed walking). The results provided preliminary empirical validation of the proposed model of SA for multitasking with locomotion. Further experimental studies need to be conducted for a more fine grained investigation of the relationship of SA with specific proactive gait control mechanisms (e.g., accommodating, avoiding) under multitasking situations.
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    Development of a Haptic-based Rey-Osterrieth Complex Figure Testing and Training System with Computer Scoring and Force-feedback Rehabilitation Functions.
    (2010-05-06) Li, Yingjie; David Kaber, Committee Chair; Yuan-Shin Lee, Committee Chair; Christopher Healey, Committee Member; Simon Hsiang, Committee Member; Larry Tupler, Committee Member; Robert St. Amant, Committee Member
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    The Effects of In-vehicle Automation and Reliability on Driver Situation Awareness and Trust
    (2006-01-07) Ma, Ruiqi; David Kaber, Committee Chair
    The cognitive construct of situation awareness (SA) has not been well developed in the domain of driving. The objective of this study was to define a new transactional model of SA in various driving behaviors and activities, as influenced by automation and in-vehicle device use. Specifically, this study investigated the implications of adaptive cruise control (ACC) and cellular phone use in driving on a direct and objective measure of SA; investigate the effect of varying reliability of in-vehicle automation (navigation aids) on driver SA and trust; and assess differences in human trust in a human aid versus an automation aid in a simulated driving task. Twenty participants drove a virtual car and performed a freeway driving task (Experiment A) as well as a suburb navigation task (Experiment B). In the freeway driving, participants were required to drive using ACC or manual control modes, and received navigation information from one of two sources: a human or in-vehicle automation aid via cell phone or separate display screen, respectively. During the navigation driving, participants were required to drive through the suburban area following all traffic signs and directions from the navigation aid under different levels of information reliability (100%, 80% and 60%). A control condition was also used in which aids only presented a telemarketing survey and participants navigated using a map. Driver SA was assessed at the end of each experiment using a SA global assessment technique. Driver workload was collected at the same time using the NASA- TLX. Driver trust in the navigation aid information was measured using a subjective survey of initial subject trust expectations as well as a subjective rating at the close of each trial (end of Experiment B). Across both experiments, multiple dimensions of task performance were measured. MANOVA results for Experiment A revealed significant main effects for both ACC control mode and navigation aid type on driver performance, but no interaction effect. Findings were similar for driver SA except there was no effect of aid type. ANOVA results indicated use of the ACC system to improve driver SA and operational driver behaviors by reducing the task load in Experiment A. MANOVA results for Experiment B revealed only a significant effect of navigation aid reliability on driver performance and SA. ANOVA results revealed that perfect navigation information generally improved driving performance and driver SA for strategic driving behavior compared to unreliable navigation aid information and the control condition (task-irrelevant information). The results also revealed that drivers had higher initial trust expectations and expectation of fewer errors by the automation compared to the human. However, when participants experienced automation aid errors or inefficiency, their trust in the automation declined more sharply than trust in the human advisor. The results of this empirical work provide insight into the importance of driver SA in operational and strategic type driving tasks and associated actions. It identifies in-vehicle automation and devices as underlying factors in linkages of levels of SA to specific driving behaviors in the transactional model and serves to quantify the impact of the factors on driving performance. Validation of the proposed model and identification of other underlying factors may lead to its future use for predictive purposes.
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    The Effects of Scaffolding Equipment Interventions on Muscle Activation and Task Performance in Frame Assembly and Disassembly Tasks.
    (2010-12-16) Gangakhedkar, Shruti; David Kaber, Committee Chair; Thom Hodgson, Committee Member; Naomi Glasscock, Committee Member; Anne McLaughlin, Committee Member
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    An Empirical Assessment of the Role of Driver Motivation and Emotion State, and Driving Conditions in Perceived Safety Margins
    (2009-06-29) Zhang, Yu; Kevin Gross, Committee Member; Denis Cormier, Committee Member; David Kaber, Committee Chair
    Models of motivation in driver behavior have been developed to predict driver performance under different conditions. Among existing models, Näätänen and Summala’s multi-dimensional threshold model (1976) was selected as basis for the current study. Näätänen and Summala proposed that driver behavior is modified not only according the degree of difficulty of traffic situations, but also based on driver risk tolerance in specific tasks. They also observed that risk-taking is based on driver motives and emotional states. According to this model, various factors may influence driver behavior. For instance, traffic patterns (other driver behavior) and driver motivation to comply with social norms, extreme emotions triggered by special circumstances (emergencies), and long-term emotional tendencies. The latter factor has been assessed using Driver Stress Inventories (Matthews, Desmond, Joyner, Carcary, & Gilliland, 1996). Näätänen and Summala’s model also indentified measures of change in driver risk-taking decisions, or safety margins, as being predictors of driver performance. The objectives of this study were to: 1) provide empirical evidence of the influence of motivation and emotional factors, as identified by Näätänen and Summala, in driver risk-taking behavior; and 2) identify any additional variables that might mediate the effects of motivational factors on behavior, including roadway environment complexity. The study examined the following specific factors: 1) traffic patterns, including traffic jam, school zone, normal traffic flow and speeding conditions to assess the influence of social norms on driver behavior; 2) driver payment systems, including time-based and performance-based compensation to assess the influence of extreme emotions on performance; and 3) environment complexity, including rural and city conditions to assess the influence of changes in task difficulty on behavior. Response measures included safety margins and speed measures. Safety margin measures consisted of: 1) spatial variables, including headway distance (HW) and lateral distance (DH); and 2) time variables, including time headway (THW), time to collision (TTC) and time to line crossing (TTLC). Speed measures consisted of average speed, maximum speed and the percentage of time spent speeding. Ten participants drove a virtual car in a high-fidelity simulator and performed daily driving tasks (e.g., lane maintenance, lead-car following, passing, negotiating intersections, etc.). A split-plot experiment design was used with the whole-plot (trial) factors including environment complexity and the payment system. Traffic pattern was manipulated as the split-plot factor with each of the four patterns occurring during a single segment in each trial. Participants complete eight test trials, including two replications all combinations of complexity and payment system. Participants were also required to finish a DSI prior to simulated-driving tasks. The experiment results revealed the effect of the motivational factor/payment system. More risky driving behavior was associated with the performance-based payment system compared to the time-based system. The influence of environment complexity was also observed. Smaller safety margins appeared in the rural environment as compared to city. The effects of traffic pattern were significant across all response measures except TTLC: traffic jams led to minimum safety margins; speeding segments produced the highest driving speeds and largest safety margins; school zones were associated with conservative behavior, including lower speeds and larger safety margins. The traffic pattern also interacted with the roadway complexity condition in terms of THW. Drivers were influenced more by the behaviors of other drivers in the city versus rural setting. Correlation analyses showed significant linear associations between long-term emotional tendencies and safety margin and speed measures. In summary, the current research contributed to the further development of motivational models of driving behavior by providing reliable evidence of factors that are significantly influential in perceived safety margins and performance. The study also identified additional (lateral vs. longitudinal) measures for sensitively specifying safety margins. Future research should investigate a broader range of emotional factors that may be related with safety margins. The role of long-term emotional tendencies in driver performance should also be studied under a broader range of conditions, including roadway hazard exposure. In addition to this, future work might examine more diverse driving populations (beyond college students) to obtain a more comprehensive understanding of motivational/emotional factors in driving performance.
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    The Influence of Dynamics, Flight Domain and Individual Flight Training & Experience on Pilot Perception of Clutter in Aviation Displays.
    (2010-05-15) Naylor, James; David Kaber, Committee Chair; Jason Osborne, Committee Member; Simon Hsiang, Committee Member