Matching Items (4)
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- All Subjects: Implicit Bias
- All Subjects: Time Delay
- Creators: Craig, Scotty D.
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 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
Description
Social categories such as race and gender are associated by people with certain characteristics (e.g. males are angry), which unconsciously affects how people evaluate and react to a person of specific social categories. This phenomenon, referred to as implicit bias, has been the interest of many social psychologists. However, the implicit bias research has been focusing on only one social category at a time, despite humans being entities of multiple social categories. The research also neglects the behavioral contexts in which implicit biases are triggered and rely on a broad definition for the locus of the bias regulation mechanism. These limitations raise questions on whether the current bias reduction strategies are effective. The current dissertation sought to address these limitations by introducing an ecologically valid and multidimensional method. In Chapters 1 and 2, the mouse-tracking task was integrated into the implicit association task to examine how implicit biases were moderated in different behavioral contexts. The results demonstrated that the manifestation of implicit biases depended on the behavioral context as well as the distinctive identity created by the combinations of different social categories. Chapter 3 laid groundwork for testing working memory as the processing capacity for the bias regulation mechanism. The result suggested that the hand-motion tracking indices of working memory load could be used to infer the capacity of an individual to suppress the influence of implicit bias. In Chapter 4, the mouse-tracking paradigm was integrated into the Stroop task with implicit associations serving as the Stroop targets. The implicit associations produced various effects including the conflict adaptation effect, like the Stroop targets, which suggested that implicit associations and Stroop stimuli are handled by overlapping cognitive mechanisms. Throughout these efforts, the current dissertation, first, demonstrated that a more ecologically valid and multidimensional approach is required to understand biased behaviors in detail. Furthermore, the current dissertation suggested the cognitive control mechanism as a finer definition for the locus of the bias regulation mechanism, which could be leveraged to offer solutions that are more adaptive and effective in the environment where collaboration and harmony are more important than ever.
ContributorsRheem, Hansol (Author) / Becker, D. Vaughn (Thesis advisor) / Craig, Scotty D. (Committee member) / Gutzwiller, Robert S. (Committee member) / Arizona State University (Publisher)
Created2019
Description
Cancer is a worldwide burden in every aspect: physically, emotionally, and financially. A need for innovation in cancer research has led to a vast interdisciplinary effort to search for the next breakthrough. Mathematical modeling allows for a unique look into the underlying cellular dynamics and allows for testing treatment strategies without the need for clinical trials. This dissertation explores several iterations of a dendritic cell (DC) therapy model and correspondingly investigates what each iteration teaches about response to treatment.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
ContributorsDickman, Lauren (Author) / Kuang, Yang (Thesis advisor) / Baer, Steven M. (Committee member) / Gardner, Carl (Committee member) / Gumel, Abba B. (Committee member) / Kostelich, Eric J. (Committee member) / Arizona State University (Publisher)
Created2020
Description
With the ongoing development of simulation technology, classic barriers to social interactions are beginning to be dismantled. One such exchange is encapsulated within education—instructors can use simulations to make difficult topics more manageable and accessible to students. Within simulations that include virtual humans, however, there are important factors to consider. Participants playing in virtual environments will act in a way that is consistent with their real-world behaviors—including their implicit biases. The current study seeks to determine the impact of virtual humans’ skin tone on participants’ behaviors when applying engineering concepts to simulated projects. Within a comparable study focused on a medical training simulation, significantly more errors and delays were made when working for the benefit of dark-skinned patients in a virtual context. In the current study, participants were given a choose-your-own-adventure style game in which they constructed simulated bridges for either a light- ordark-skinned community, and the number of errors and time taken for each decision was tracked. Results are expected to be consistent with previous study, indicating a higher number of errors and less time taken for each decision, although these results may be attenuated by a
lack of time pressure and urgency to the given situations. If these expected results hold, there may be implications for both undergraduate engineering curriculum and real-world engineering endeavors.
lack of time pressure and urgency to the given situations. If these expected results hold, there may be implications for both undergraduate engineering curriculum and real-world engineering endeavors.
ContributorsEldemire, Kate (Author) / Craig, Scotty D. (Thesis director) / Roscoe, Rod D. (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05