Barrett

Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

Displaying 1 - 2 of 2
Filtering by

Clear all filters

133597-Thumbnail Image.png

Reinforcing Empathy through Formalized Instruction

Description
This project is meant to measure and assess empathy through the Empathy Assessment Index (EAI) and Social Empathy Index (SEI) instruments. Researchers believe that empathy is an involuntary but dynamic aspect of people's affective and cognitive responses to emotional stimuli. This project used the EAI and SEI instruments to see…

This project is meant to measure and assess empathy through the Empathy Assessment Index (EAI) and Social Empathy Index (SEI) instruments. Researchers believe that empathy is an involuntary but dynamic aspect of people's affective and cognitive responses to emotional stimuli. This project used the EAI and SEI instruments to see whether a course taught at Arizona State University \u2014 PAF 300 \u2014increased empathy and its seven components within students. The results suggest that different modular interventions were effective in increasing four of the seven empathic components \u2014 affective response, perspective-taking, contextual understanding of systemic barriers, and macro self-other awareness/ perspective-taking \u2014 but that it was detrimental to two components, self-other awareness and affective mentalizing. Future studies are necessary to understand how aspects of a course curriculum can target and increase the seven components in individuals, as well as how these components relate to one another within the greater concept of empathy. Still, this research is important in the greater scheme of empathy as it seeks to understand and expand individuals' empathic levels in an increasingly bleak and desolate political climate.
ContributorsPirkl, Audrie Madison (Author) / Johnston, Erik W., 1977- (Thesis director) / Minrichs, Margaret (Committee member) / W.P. Carey School of Business (Contributor) / School of Public Affairs (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
133684-Thumbnail Image.png

Predicting the Outcome of UFC Fights Using Machine Learning Models

Description
Abstract: The Ultimate Fighting Championship or UFC as it is commonly known, was founded in 1993 and has quickly built itself into the world's foremost authority on all things MMA (mixed martial arts) related. With pay-per-view and cable television deals in hand, the UFC has become a huge competitor in…

Abstract: The Ultimate Fighting Championship or UFC as it is commonly known, was founded in 1993 and has quickly built itself into the world's foremost authority on all things MMA (mixed martial arts) related. With pay-per-view and cable television deals in hand, the UFC has become a huge competitor in the sports market, rivaling the popularity of boxing for almost a decade. As with most other sports, the UFC has seen an influx of various analytics and data science over the past five to seven years. We see this revolution in football with the broadcast first down markers, basketball with tracking player movement, and baseball with locating pitches for strikes and balls, and now the UFC has partnered with statistics company Fightmetric, to provide in-depth statistical analysis of its fights. ESPN has their win probability metrics, and statistical predictive modeling has begun to spread throughout sports. All these stats were made to showcase the information about a fighter that one wouldn't typically know, giving insight into how the fight might go. But, can these fights be predicted? Based off of the research of prior individuals and combining the thought processes of relevant research into other sports leagues, I sought to use the arsenal of statistical analyses done by Fightmetric, along with the official UFC fighter database to answer the question of whether UFC fights could be predicted. Specifically, by using only data that would be known about a fighter prior to stepping into the cage, could I predict with any degree of certainty who was going to win the fight?
ContributorsMoorman, Taylor D. (Author) / Simon, Alan (Thesis director) / Simon, Phil (Committee member) / W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05