Although there are many forms of organization on the Web, one of the most prominent ways to organize web content and websites are tags. Tags are keywords or terms that are assigned to a specific piece of content in order to help users understand the common relationships between pieces of content. Tags can either be assigned by an algorithm, the author, or the community. These tags can also be organized into tag clouds, which are visual representations of the structure and organization contained implicitly within these tags. Importantly, little is known on how we use these different tagging structures to understand the content and structure of a given site. This project examines 2 different characteristics of tagging structures: font size and spatial orientation. In order to examine how these different characteristics might interact with individual differences in attentional control, a measure of working memory capacity (WMC) was included. The results showed that spatial relationships affect how well users understand the structure of a website. WMC was not shown to have any significant effect; neither was varying the font size. These results should better inform how tags and tag clouds are used on the Web, and also provide an estimation of what properties to include when designing and implementing a tag cloud on a website.

Research on priming has shown that a stimulus can cause people to behave according to the stereotype held about the stimulus. Two experiments were conducted in which the effects of elderly priming were tested by use of a driving simulator. In both experiments, participants drove through a simulated world guided by either an elderly or a younger female voice. The voices told the participants where to make each of six turns. Both experiments yielded slower driving speeds in the elderly voice condition. The effect was universal regardless of implicit and explicit attitudes towards elderly people.

By extracting communication sequences from audio data collected during two separate five-person mission-planning tasks, interaction patterns in team communication were analyzed using a recurrence-based, nonlinear dynamics approach. These methods, previously successful in detecting pattern change in a three-person team task, were evaluated for their applicability to larger team settings, and their ability to detect pattern change when team members switched roles or locations partway through the study (Study 1) or change in patterns over time (Study 2). Both traditional interaction variables (Talking Time, Co-Talking Time, and Sequence Length of Interactions) and dynamic interaction variables (Recurrence Rate, Determinism, and Pattern Information) were explored as indicators and predictors of changes in team structure and performance. Results from these analyses provided support that both traditional and dynamic interaction variables reflect some changes in team structure and performance. However, changes in communication patterns were not detected. Because simultaneous conversations are possible in larger teams, but not detectable through our communication sequence methods, team pattern changes may not be visible in communication sequences for larger teams. This suggests that these methods may not be applicable for larger teams, or in situations where simultaneous conversations may occur. Further research is needed to continue to explore the applicability of recurrence-based nonlinear dynamics in the analysis of team communication.

This thesis describes a synthetic task environment, CyberCog, created for the purposes of 1) understanding and measuring individual and team situation awareness in the context of a cyber security defense task and 2) providing a context for evaluating algorithms, visualizations, and other interventions that are intended to improve cyber situation awareness. CyberCog provides an interactive environment for conducting human-in-loop experiments in which the participants of the experiment perform the tasks of a cyber security defense analyst in response to a cyber-attack scenario. CyberCog generates the necessary performance measures and interaction logs needed for measuring individual and team cyber situation awareness. Moreover, the CyberCog environment provides good experimental control for conducting effective situation awareness studies while retaining realism in the scenario and in the tasks performed.

Although current urban search and rescue (USAR) robots are little more than remotely controlled cameras, the end goal is for them to work alongside humans as trusted teammates. Natural language communications and performance data are collected as a team of humans works to carry out a simulated search and rescue task in an uncertain virtual environment. Conditions are tested emulating a remotely controlled robot versus an intelligent one. Differences in performance, situation awareness, trust, workload, and communications are measured. The Intelligent robot condition resulted in higher levels of performance and operator situation awareness (SA).

The International Standards Organization (ISO) documentation utilizes Fitts’ law to determine the usability of traditional input devices like mouse and touchscreens for one- or two-dimensional operations. To test the hypothesis that Fitts’ Law can be applied to hand/air gesture based computing inputs, Fitts’ multi-directional target acquisition task is applied to three gesture based input devices that utilize different technologies and two baseline devices, mouse and touchscreen. Three target distances and three target sizes were tested six times in a randomized order with a randomized order of the five input technologies. A total of 81 participants’ data were collected for the within subjects design study. Participants were instructed to perform the task as quickly and accurately as possible according to traditional Fitts’ testing procedures. Movement time, error rate, and throughput for each input technology were calculated.

Additionally, no standards exist for equating user experience with Fitts’ measures such as movement time, throughput, and error count. To test the hypothesis that a user’s experience can be predicted using Fitts’ measures of movement time, throughput and error count, an ease of use rating using a 5-point scale for each input type was collected from each participant. The calculated Mean Opinion Scores (MOS) were regressed on Fitts’ measures of movement time, throughput, and error count to understand the extent to which they can predict a user’s subjective rating.

Intelligence analysts’ work has become progressively complex due to increasing security threats and data availability. In order to study “big” data exploration within the intelligence domain the intelligence analyst task was abstracted and replicated in a laboratory (controlled environment). Participants used a computer interface and movie database to determine the opening weekend gross movie earnings of three pre-selected movies. Data consisted of Twitter tweets and predictive models. These data were displayed in various formats such as graphs, charts, and text. Participants used these data to make their predictions. It was expected that teams (a team is a group with members who have different specialties and who work interdependently) would outperform individuals and groups. That is, teams would be significantly better at predicting “Opening Weekend Gross” than individuals or groups. Results indicated that teams outperformed individuals and groups in the first prediction, under performed in the second prediction, and performed better than individuals in the third prediction (but not better than groups). Insights and future directions are discussed.

Nicotine and tobacco use, whether it be through cigarette smoking or other devices, creates negative health conditions in pilots. The literature that was reviewed pertained to nicotine withdrawal symptoms and their negative impact on pilot performance. There have been studies conducted in order to explore how these symptoms impact pilot performance using cigarettes as the only nicotine device and does not specify the nicotine levels or the frequency of use. This thesis extends this work to examine the relationship between the nicotine withdrawal symptoms and the nicotine behaviors of pilots. It was hypothesized that the extent of withdrawal symptoms may differ by device and by nicotine levels and frequency of use, with higher levels and more frequent use being associated with more severe withdrawal symptoms. These behaviors included the device they use to take nicotine whether it be cigarettes, vaporizers, e-cigarettes, or smokeless tobacco. The behaviors also included exploration of how nicotine levels relate to withdrawal symptoms whether the nicotine level is as low as 3mg or high as 36mg. The last relationship that was explored was that between the withdrawal symptoms presented in pilots and how often they used nicotine, whether it be often as every day or less frequent as 1-2 times a year. It was found that there is no statistical relationship between nicotine withdrawal symptoms and the nicotine habits such as device used, nicotine level used, and frequency of use.

The prospects of commercially available autonomous vehicles are surely tantalizing, however the implementation of these vehicles and their strain on the social dynamics between motorists and pedestrians remains unknown. Questions concerning how autonomous vehicles will communicate safety and intent to pedestrians remain largely unanswered. This study examines the efficacy of various proposed technologies for bridging the communication gap between self-driving cars and pedestrians. Displays utilizing words like “safe” and “danger” seem to be effective in communicating with pedestrians and other road users. Future research should attempt to study different external notification interfaces in real-life settings to more accurately gauge pedestrian responses.

Minimally invasive surgery is a surgical technique that is known for its reduced

patient recovery time. It is a surgical procedure done by using long reached tools and an

endoscopic camera to operate on the body though small incisions made near the point of

operation while viewing the live camera feed on a nearby display screen. Multiple camera

views are used in various industries such as surveillance and professional gaming to

allow users a spatial awareness advantage as to what is happening in the 3D space that is

presented to them on 2D displays. The concept has not effectively broken into the

medical industry yet. This thesis tests a multi-view camera system in which three cameras

are inserted into a laparoscopic surgical training box along with two surgical instruments,

to determine the system impact on spatial cognition, perceived cognitive workload, and

the overall time needed to complete the task, compared to one camera viewing the

traditional set up. The task is a non-medical task and is one of five typically used to train

surgeons’ motor skills when initially learning minimally invasive surgical procedures.

The task is a peg transfer and will be conducted by 30 people who are randomly assigned

to one of two conditions; one display and three displays. The results indicated that when

three displays were present the overall time initially using them to complete a task was

slower; the task was perceived to be completed more easily and with less strain; and

participants had a slightly higher performance rate.