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Association between Student Engagement and Resilience in the Context of COVID-19

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During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot…

During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot survey was administered to 200 participants currently enrolled as undergraduate students at Arizona State University. A multiple regression analysis and Pearson correlations were calculated. A moderate, significant correlation was found between student engagement (total score) and resilience. A significant correlation was found between cognitive engagement (student’s approach and understanding of his learning) and resilience and between valuing and resilience. Contrary to expectations, participation was not associated with resilience. Potential explanations for these results were explored and practical applications for the university were discussed.
ContributorsEmmanuelli, Michelle (Author) / Jimenez Arista, Laura (Thesis director) / Sever, Amy (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Using Logistic Regression to Predict Stock Trends Based on Bag-of-Words Representations of News Article Headlines

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We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones…

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
ContributorsBarolli, Adeiron (Author) / Jimenez Arista, Laura (Thesis director) / Wilson, Jeffrey (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The Influence of Gender, Race and Intersectionality on Stress in Division I Head Basketball Coaches

Description
Research in intercollegiate athletics has provided a relatively large body of findings about the kinds of stressors found in high profile intercollegiate athletic environments and their effects on student-athletes. Research is less robust regarding stress and its effects on head coaches in high profile collegiate athletics. This study focuses on…

Research in intercollegiate athletics has provided a relatively large body of findings about the kinds of stressors found in high profile intercollegiate athletic environments and their effects on student-athletes. Research is less robust regarding stress and its effects on head coaches in high profile collegiate athletics. This study focuses on the types, frequencies, and intensities of stress experienced by NCAA, Division I head coaches. The purpose of the study is to identify the types, frequency, and intensity of stress common to 20 head basketball coaches participating in the study, as well as differences in their experiences based on gender, race and the intersectionality of race and gender. The participants in the study are 20 head coaches (five Black females, five Black males, five White females, and White males). The conceptual framework guiding the study is a definition of stress as an interaction between a person and her or his environment in which the person perceives the resources available to manage the situation to be inadequate (Lazarus & Folkman, 1984). The study’s design is an adaptation of prior research conducted by Frey, M., 2007 and Olusoga, P., Butt, J., Hays, K., & Maynard, I., 2009, and Olusoga, P., Butt, J., Maynard, I., & Hays, K., 2011. This study used qualitative and quantitative methods that triangulated results scores on Maslach’s Burn-out Inventory and the Perceived Stress Scale with the thick data collected from semi-structured interviews with the 20 head coaches from each of the three data sources to enhance the validity and reliability of the findings. The researcher analyzed the data collected by placing it in one of two categories, one representing attributes of the participants including race and gender; the second category was comprised of attributes of the Division I environment.
ContributorsRousseau, Julie B (Author) / Gray, Rob (Thesis advisor) / Vega, Sujey (Committee member) / Wilson, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2019