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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
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
Working memory capacity and fluid intelligence are important predictors of performance in educational settings. Thus, understanding the processes underlying the relation between working memory capacity and fluid intelligence is important. Three large scale individual differences experiments were conducted to determine the mechanisms underlying the relation between working memory capacity and

Working memory capacity and fluid intelligence are important predictors of performance in educational settings. Thus, understanding the processes underlying the relation between working memory capacity and fluid intelligence is important. Three large scale individual differences experiments were conducted to determine the mechanisms underlying the relation between working memory capacity and fluid intelligence. Experiments 1 and 2 were designed to assess whether individual differences in strategic behavior contribute to the variance shared between working memory capacity and fluid intelligence. In Experiment 3, competing theories for describing the underlying processes (cognitive vs. strategy) were evaluated in a comprehensive examination of potential underlying mechanisms. These data help inform existing theories about the mechanisms underlying the relation between WMC and gF. However, these data also indicate that the current theoretical model of the shared variance between WMC and gF would need to be revised to account for the data in Experiment 3. Possible sources of misfit are considered in the discussion along with a consideration of the theoretical implications of observing those relations in the Experiment 3 data.
ContributorsWingert, Kimberly Marie (Author) / Brewer, Gene A. (Thesis advisor) / McNamara, Danielle (Thesis advisor) / McClure, Samuel (Committee member) / Redick, Thomas (Committee member) / Arizona State University (Publisher)
Created2018
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Description
This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test

This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test taker’s non-verbal cues indicated that time delay, the variation of a student’s head pose relative to the computer screen and confusion had significantly statistical relation to cheating behaviors. Additionally, time delay, head pose relative to the computer screen, confusion, and the interaction term of confusion and time delay were predictors in a support vector machine of cheating prediction with an average accuracy of 70.7%. The current algorithm could automatically flag suspicious student behavior for proctors in large scale online courses during remotely administered exams.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John C. (Thesis advisor) / Craig, Scotty D. (Thesis advisor) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015