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Description
The American Heart Association (AHA) estimates that there are approximately 200,000 in-hospital cardiac arrests (IHCA) annually with low rates of survival to discharge at about 22%. Training programs for cardiac arrest teams, also termed code teams, have been recommended by the Institute of Medicine (IOM) and in the AHA's consensus

The American Heart Association (AHA) estimates that there are approximately 200,000 in-hospital cardiac arrests (IHCA) annually with low rates of survival to discharge at about 22%. Training programs for cardiac arrest teams, also termed code teams, have been recommended by the Institute of Medicine (IOM) and in the AHA's consensus statement to help improve these dismal survival rates. Historically, training programs in the medical field are procedural in nature and done at the individual level, despite the fact that healthcare providers frequently work in teams. The rigidity of procedural training can cause habituation and lead to poor team performance if the situation does not match the original training circumstances. Despite the need for team training, factors such as logistics, time, personnel coordination, and financial constraints often hinder resuscitation team training. This research was a three-step process of: 1) development of a metric specific for the evaluation of code team performance, 2) development of a communication model that targeted communication and leadership during a code blue resuscitation, and 3) training and evaluation of the code team leader using the communication model. This research forms a basis to accomplish a broad vision of improving outcomes of IHCA events by applying conceptual and methodological strategies learned from collaborative and inter-disciplinary science of teams.
ContributorsHinski, Sandra T. (Author) / Cooke, Nancy J. (Thesis advisor) / Roscoe, Rod (Committee member) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
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Description
With social technology on the rise, it is no surprise that young students are at the forefront of its use and impact, particularly in the realm of education. Due to greater accessibility to technology, media multitasking and task-switching are becoming increasingly prominent in learning environments. While technology can have numerous

With social technology on the rise, it is no surprise that young students are at the forefront of its use and impact, particularly in the realm of education. Due to greater accessibility to technology, media multitasking and task-switching are becoming increasingly prominent in learning environments. While technology can have numerous benefits, current literature, though somewhat limited in this scope, overwhelmingly shows it can also be detrimental for academic performance and learning when used improperly. While much of the existing literature regarding the impact of technology on multitasking and task-switching in learning environments is limited to self-report data, it presents important findings and potential applications for modernizing educational institutions in the wake of technological dependence. This literature review summarizes and analyzes the studies in this area to date in an effort to provide a better understanding of the impact of social technology on student learning. Future areas of research and potential strategies to adapt to rising technological dependency are also discussed, such as using a brief "technology break" between periods of study. As of yet, the majority of findings in this research area suggest the following: multitasking while studying lengthens the time required for completion; multitasking during lectures can affect memory encoding and comprehension; excessive multitasking and academic performance are negatively correlated; metacognitive strategies for studying have potential for reducing the harmful effects of multitasking; and the most likely reason students engage in media-multitasking at the cost of learning is the immediate emotional gratification. Further research is still needed to fill in gaps in literature, as well as develop other potential perspectives relevant to multitasking in academic environments.
ContributorsKhanna, Sanjana (Author) / Roberts, Nicole (Thesis director) / Burleson, Mary (Committee member) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
This research evaluates a cyber test-bed, DEXTAR (Defense Exercises for Team Awareness Research), and examines the relationship between good and bad team performance in increasingly difficult scenarios. Twenty-one computer science graduate students (seven three-person teams), with experience in cybersecurity, participated in a team-based cyber defense exercise in the context of

This research evaluates a cyber test-bed, DEXTAR (Defense Exercises for Team Awareness Research), and examines the relationship between good and bad team performance in increasingly difficult scenarios. Twenty-one computer science graduate students (seven three-person teams), with experience in cybersecurity, participated in a team-based cyber defense exercise in the context of DEXTAR, a high fidelity cybersecurity testbed. Performance measures were analyzed in addition to team process, team behavior, and workload to examine the relationship between good and bad teams. Lessons learned are reported that will inform the next generation of DEXTAR.
ContributorsBradbury, Aaron (Author) / Cooke, Nancy J. (Thesis advisor) / Branaghan, Russell (Committee member) / Roscoe, Rod (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This increasing role of highly automated and intelligent systems as team members has started a paradigm shift from human-human teaming to Human-Autonomy Teaming (HAT). However, moving from human-human teaming to HAT is challenging. Teamwork requires skills that are often missing in robots and synthetic agents. It is possible that

This increasing role of highly automated and intelligent systems as team members has started a paradigm shift from human-human teaming to Human-Autonomy Teaming (HAT). However, moving from human-human teaming to HAT is challenging. Teamwork requires skills that are often missing in robots and synthetic agents. It is possible that adding a synthetic agent as a team member may lead teams to demonstrate different coordination patterns resulting in differences in team cognition and ultimately team effectiveness. The theory of Interactive Team Cognition (ITC) emphasizes the importance of team interaction behaviors over the collection of individual knowledge. In this dissertation, Nonlinear Dynamical Methods (NDMs) were applied to capture characteristics of overall team coordination and communication behaviors. The findings supported the hypothesis that coordination stability is related to team performance in a nonlinear manner with optimal performance associated with moderate stability coupled with flexibility. Thus, we need to build mechanisms in HATs to demonstrate moderately stable and flexible coordination behavior to achieve team-level goals under routine and novel task conditions.
ContributorsDemir, Mustafa, Ph.D (Author) / Cooke, Nancy J. (Thesis advisor) / Bekki, Jennifer (Committee member) / Amazeen, Polemnia G (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Team communication facilitates team coordination strategies and situations, and how teammates perceive one another. In human-machine teams, these perceptions affect how people trust and anthropomorphize their machine counterparts, which in turn affects future team communication, forming a feedback loop. This thesis investigates how personifying and objectifying contents in human-machine team

Team communication facilitates team coordination strategies and situations, and how teammates perceive one another. In human-machine teams, these perceptions affect how people trust and anthropomorphize their machine counterparts, which in turn affects future team communication, forming a feedback loop. This thesis investigates how personifying and objectifying contents in human-machine team communication relate to team performance and perceptions in a simulated remotely piloted aircraft system task environment. A total of 46 participants grouped into teams of two were assigned unique roles and teamed with a synthetic pilot agent that in reality was a trained confederate following a script. Quantities of verbal personifications and objectifications were compared to questionnaire responses about participants’ perceived trust and anthropomorphism of the synthetic pilot, as well as team performance. It was hypothesized that verbal personifications would positively correlate with reflective trust, anthropomorphism, and team performance, and that verbal objectifications would negatively correlate with the same measures. It was also predicted that verbal personifications would decrease over time as human teammates interact more with the machine teammate, and that verbal objectifications would increase. Verbal personifications were not found to be correlated with trust and anthropomorphism outside of perceptions related to gender, albeit patterns of change in the navigator’s personifications coincided with a co-calibration of trust among the navigator and the photographer. Results supported the prediction that verbal objectifications are negatively correlated with trust and anthropomorphism of a teammate. Significant relationships between verbal personifications and objectifications and team performance were not found. This study provides support to the notion that people verbally personify machines to ease communication when necessary, and that the same processes that underlie tendencies to personify machines may be reciprocally related to those that influence team trust. Overall, this study provides evidence that personifying and objectifying language in human-machine team communication is a viable candidate for measuring the perceptions and states of teams, even in highly restricted communication environments.
ContributorsCohen, Myke C. (Author) / Cooke, Nancy J. (Thesis advisor) / Chiou, Erin K. (Committee member) / Amazeen, Polemnia G. (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Human-agent teams (HATs) are expected to play a larger role in future command and control systems where resilience is critical for team effectiveness. The question of how HATs interact to be effective in both normal and unexpected situations is worthy of further examination. Exploratory behaviors are one that way adaptive

Human-agent teams (HATs) are expected to play a larger role in future command and control systems where resilience is critical for team effectiveness. The question of how HATs interact to be effective in both normal and unexpected situations is worthy of further examination. Exploratory behaviors are one that way adaptive systems discover opportunities to expand and refine their performance. In this study, team interaction exploration is examined in a HAT composed of a human navigator, human photographer, and a synthetic pilot while they perform a remotely-piloted aerial reconnaissance task. Failures in automation and the synthetic pilot’s autonomy were injected throughout ten missions as roadblocks. Teams were clustered by performance into high-, middle-, and low-performing groups. It was hypothesized that high-performing teams would exchange more text-messages containing unique content or sender-recipient combinations than middle- and low-performing teams, and that teams would exchange less unique messages over time. The results indicate that high-performing teams had more unique team interactions than middle-performing teams. Additionally, teams generally had more exploratory team interactions in the first session of missions than the second session. Implications and suggestions for future work are discussed.
ContributorsLematta, Glenn Joseph (Author) / Chiou, Erin K. (Thesis advisor) / Cooke, Nancy J. (Committee member) / Roscoe, Rod D. (Committee member) / Arizona State University (Publisher)
Created2019
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Description
The choices of an operator under heavy cognitive load are potentially critical to overall safety and performance. Such conditions are common when technological failures arise, and the operator is forced into multi-task situations. Task switching choice was examined in an effort to both validate previous work concerning a model of

The choices of an operator under heavy cognitive load are potentially critical to overall safety and performance. Such conditions are common when technological failures arise, and the operator is forced into multi-task situations. Task switching choice was examined in an effort to both validate previous work concerning a model of task overload management and address unresolved matters related to visual sampling. Using the Multi-Attribute Task Battery and eye tracking, the experiment studied any influence of task priority and difficulty. Continuous visual attention measurements captured attentional switches that do not manifest into behaviors but may provide insight into task switching choice. Difficulty was found to have an influence on task switching behavior; however, priority was not. Instead, priority may affect time spent on a task rather than strictly choice. Eye measures revealed some moderate connections between time spent dwelling on a task and subjective interest. The implication of this, as well as eye tracking used to validate a model of task overload management as a whole, is discussed.
ContributorsZabala, Garrett (Author) / Gutzwiller, Robert S (Thesis advisor) / Cooke, Nancy J. (Committee member) / Gray, Rob (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Cyber threats are growing in number and sophistication making it important to continually study and improve all dimensions of cyber defense. Human teamwork in cyber defense analysis has been overlooked even though it has been identified as an important predictor of cyber defense performance. Also, to detect advanced forms of

Cyber threats are growing in number and sophistication making it important to continually study and improve all dimensions of cyber defense. Human teamwork in cyber defense analysis has been overlooked even though it has been identified as an important predictor of cyber defense performance. Also, to detect advanced forms of threats effective information sharing and collaboration between the cyber defense analysts becomes imperative. Therefore, through this dissertation work, I took a cognitive engineering approach to investigate and improve cyber defense teamwork. The approach involved investigating a plausible team-level bias called the information pooling bias in cyber defense analyst teams conducting the detection task that is part of forensics analysis through human-in-the-loop experimentation. The approach also involved developing agent-based models based on the experimental results to explore the cognitive underpinnings of this bias in human analysts. A prototype collaborative visualization tool was developed by considering the plausible cognitive limitations contributing to the bias to investigate whether a cognitive engineering-driven visualization tool can help mitigate the bias in comparison to off-the-shelf tools. It was found that participant teams conducting the collaborative detection tasks as part of forensics analysis, experience the information pooling bias affecting their performance. Results indicate that cognitive friendly visualizations can help mitigate the effect of this bias in cyber defense analysts. Agent-based modeling produced insights on internal cognitive processes that might be contributing to this bias which could be leveraged in building future visualizations. This work has multiple implications including the development of new knowledge about the science of cyber defense teamwork, a demonstration of the advantage of developing tools using a cognitive engineering approach, a demonstration of the advantage of using a hybrid cognitive engineering methodology to study teams in general and finally, a demonstration of the effect of effective teamwork on cyber defense performance.
ContributorsRajivan, Prashanth (Author) / Cooke, Nancy J. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2014