Matching Items (22)
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- All Subjects: psychology
- All Subjects: engineering
- Creators: Cooke, Nancy J.
Description
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.
ContributorsCovas-Smith, Christine Marie (Author) / Cooke, Nancy J. (Thesis advisor) / Patterson, Robert (Committee member) / Glenberg, Arthur (Committee member) / Homa, Donald (Committee member) / Arizona State University (Publisher)
Created2011
Description
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.
ContributorsBanas, Steven (Author) / Sanchez, Christopher A (Thesis advisor) / Branaghan, Russell (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
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.
ContributorsFoster, L Bryant (Author) / Branaghan, Russell (Thesis advisor) / Becker, David (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2012
Description
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.
ContributorsFouse, Shannon (Author) / Cooke, Nancy J. (Thesis advisor) / Becker, David (Thesis advisor) / Gorman, Jamie (Committee member) / Arizona State University (Publisher)
Created2012
Description
Student pilots are the future of aviation and one of the biggest problems that they face as new pilots is fatigue. The survey was sent out asking if student pilots were fatigued, if they attribute flight training, school work, work outside of school, and social obligations to their sleep loss, and how they spend their time on those activities. The survey was given to aviation students at Arizona State University (ASU) Polytechnic Campus. ASU student pilots were found to be fatigued through a single sample t-test. Other t-tests were done on each of the questions that asked student pilots how flight training, school work, work outside of school and social obligations affect their sleep loss. Flight training and school were found to be contributing to student pilots sleep loss. Work outside of school and social obligations were found to not be contributing to student pilots sleep loss. It was found that student pilots’ tendency to use a planner or calendar was found to not be significant. Along with this planning through the week when they will do assignments or study for exams was also not found to be significant. Students making lists of assignments and when they are due was also found to not be significant. The t-test also found that student pilots are neutral on the topic of whether good time management skills would help increase the amount of sleep that they get.
ContributorsHarris, Mariah Jean (Author) / Cooke, Nancy J. (Thesis advisor) / Nullmeyer, Robert (Thesis advisor) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
Human-robot interaction has expanded immensely within dynamic environments. The goals of human-robot interaction are to increase productivity, efficiency and safety. In order for the integration of human-robot interaction to be seamless and effective humans must be willing to trust the capabilities of assistive robots. A major priority for human-robot interaction should be to understand how human dyads have been historically effective within a joint-task setting. This will ensure that all goals can be met in human robot settings. The aim of the present study was to examine human dyads and the effects of an unexpected interruption. Humans’ interpersonal and individual levels of trust were studied in order to draw appropriate conclusions. Seventeen undergraduate and graduate level dyads were collected from Arizona State University. Participants were broken up into either a surprise condition or a baseline condition. Participants individually took two surveys in order to have an accurate understanding of levels of dispositional and individual levels of trust. The findings showed that participant levels of interpersonal trust were average. Surprisingly, participants who participated in the surprise condition afterwards, showed moderate to high levels of dyad trust. This effect showed that participants became more reliant on their partners when interrupted by a surprising event. Future studies will take this knowledge and apply it to human-robot interaction, in order to mimic the seamless team-interaction shown in historically effective dyads, specifically human team interaction.
ContributorsShaw, Alexandra Luann (Author) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Committee member) / Craig, Scotty (Committee member) / Arizona State University (Publisher)
Created2019
Description
Reading partners’ actions correctly is essential for successful coordination, but interpretation does not always reflect reality. Attribution biases, such as self-serving and correspondence biases, lead people to misinterpret their partners’ actions and falsely assign blame after an unexpected event. These biases thus further influence people’s trust in their partners, including machine partners. The increasing capabilities and complexity of machines allow them to work physically with humans. However, their improvements may interfere with the accuracy for people to calibrate trust in machines and their capabilities, which requires an understanding of attribution biases’ effect on human-machine coordination. Specifically, the current thesis explores how the development of trust in a partner is influenced by attribution biases and people’s assignment of blame for a negative outcome. This study can also suggest how a machine partner should be designed to react to environmental disturbances and report the appropriate level of information about external conditions.
ContributorsHsiung, Chi-Ping (M.S.) (Author) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
The purpose of this research was to determine if students who are enrolled in a professional flight program exhibit significantly higher rates of depression, stress, and anxiety. This study compared professional flight students to non-professional flight students to determine whether professional flight students have higher rates of depression and anxiety. In addition, this study sought to determine if there were higher depression, anxiety, and stress levels in upperclassmen (juniors and seniors) than in lowerclassmen (freshman and sophomore). Finally, upperclassmen and underclassmen within professional flight programs were compared to test if upperclassmen professional flight students exhibit higher rates for depression, anxiety and stress. These groups were compared to each other by using a survey that measures depression, anxiety, and stress. There were no statistically significant results. No singular group is more or less prone to depression, anxiety, or stress.
ContributorsJacobs, Destry (Author) / Niemczyk, Mary (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Nullmeyer, Robert (Committee member) / Cline, Paul (Committee member) / Arizona State University (Publisher)
Created2019
Description
Future autonomous vehicle systems will be diverse in design and functionality since they will be produced by different brands. In the automotive industry, trustworthiness of a vehicle is closely tied to its perceived safety. Trust involves dependence on another agent in an uncertain situation. Perceptions of system safety, trustworthiness, and performance are important because they guide people’s behavior towards automation. Specifically, these perceptions impact how reliant people believe they can be on the system to do a certain task. Over or under reliance can be a concern for safety because they involve the person allocating tasks between themselves and the system in inappropriate ways. If a person trusts a brand they may also believe the brand’s technology will keep them safe. The present study measured brand trust associations and performance expectations for safety between twelve different automobile brands using an online survey.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
The literature and results of the present study suggest perceived trustworthiness for safety of the automation and the brand of the automation, could together impact trust. Results revelated that brands closely related to the trust-based attributes, Confidence, Secure, Integrity, and Trustworthiness were expected to produce autonomous vehicle technology that performs in a safer way. While, brands more related to the trust-based attributes Harmful, Deceptive, Underhanded, Suspicious, Beware, and Familiar were expected to produce autonomous vehicle technology that performs in a less safe way.
These findings contribute to both the fields of Human-Automation Interaction and Consumer Psychology. Typically, brands and automation are discussed separately however, this work suggests an important relationship may exist. A deeper understanding of brand trust as it relates to autonomous vehicles can help producers understand potential for over or under reliance and create safer systems that help users calibrate trust appropriately. Considering the impact on safety, more research should be conducted to explore brand trust and expectations for performance between various brands.
ContributorsCelmer, Natalie (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Node-link diagrams are widely used to visualize the relational structure of real world datasets. As identical data can be visualized in infinite ways by simply changing the spatial arrangement of the nodes, one of the important research topics of the graph drawing community is to visualize the data in the way that can facilitate people's comprehension. The last three decades have witnessed the growth of algorithms for automatic visualization. However, despite the popularity of node-link diagrams and the enthusiasm in improving computational efficiency, little is known about how people read these graphs and what factors (layout, size, density, etc.) have impact on their effectiveness (the usability aspect of the graph, e.g., are they easy to understand?). This thesis is comprehensive research to investigate the factors that affect people's understanding of node-link diagrams using eye-tracking methods. Three experiments were conducted, including 1) a pilot study with 22 participants to explore the layout and size effect; 2) an eye tracking experiment with 43 participants to investigate the layout, size and density effect on people's graph comprehension using abstract node-link diagram and generic tasks; and 3) an eye tracking experiment with the same participants to investigate the same effects using a real visualization analytic application. Results showed that participants' spatial reasoning ability had significant impact on people's graph reading performance. Layout, size, and density were all found to be significant effects under different task circumstances. The applicability of the eye tracking methods on visualization evaluation has been confirmed by providing detailed evidence that demonstrates the cognitive process of participants' graph reading behavior.
ContributorsLiu, Qing (Author) / McKenna, Anna (Thesis advisor) / Jennifer, Jennifer (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2015