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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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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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This thesis is broken into two parts: the research and the toolkit. The research portion examines the benefits posed by the Barrett Student Engagement team to the Barrett Polytechnic community. Literature on student retention and attrition, inside and outside of an honors curriculum, was reviewed to better understand likely factors

This thesis is broken into two parts: the research and the toolkit. The research portion examines the benefits posed by the Barrett Student Engagement team to the Barrett Polytechnic community. Literature on student retention and attrition, inside and outside of an honors curriculum, was reviewed to better understand likely factors contributing to an increase of attrition rates. The primary question in focus is: “What are the benefits student engagement poses for Barrett Poly students?” followed by the secondary question of: “How can the student engagement team best support Barrett Poly students?” Data from the past five semesters has been collected and analyzed to determine the general trends and the strengths and weaknesses within each of the six engagement pillars. As the position of Student Engagement Assistant requires a fair amount of training for short-term employment (can be held until graduation from ASU), it is beneficial to have a training manual in place for workers to reference. The project has been made available in a hybrid format to best accommodate future changes in procedures and resources. A summary of the additional materials has been included at the end of this report.

ContributorsGriffin, Kiley (Author) / O'Flaherty, Katherine (Thesis director) / Albin, Joshua (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor)
Created2022-05