Barrett, The Honors College Thesis/Creative Project Collection
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 - 10 of 57
Description
This study was conducted in order to create a brief task that more efficiently studies the memory of young and old dogs compared to previous dog radial arm mazes. The hypotheses were older dogs would perform worse than younger dogs, brief tasks with longer delays and the presence of an occluder would produce worse results, and the brief task with the longest delay period without an occluder would be most correlated to the radial arm maze. 45 dogs were tested from a previous sample that had participated in a radial arm maze experiment. The dogs were tested in their owner's homes and watched the researcher place a treat behind one of two boxes. Dogs then waited during different delay periods, of 15, 30, or 45 seconds, and with or without an occluder, which was a curtain. Then, the dog was released to see if it could still remember which box the treat was behind. The results supported all the hypotheses, except the 45-second brief task with an occluder was most correlated the radial arm maze. Additionally, the dogs that had to be excluded from the radial arm maze still had a similar range of results on the brief tasks as dogs that were able to complete the radial arm maze. These results confirm the radial arm maze is very difficult and strenuous on dogs, but the brief task is correlated and probably much more effective at studying memory without these issues. This study can help researchers perfect this simple task in order to study many dogs much quicker and collect more information on dogs' memory. Future studies could overcome limitations including dogs that were not motivated by treats or that were too old to stand up. Specific breeds could be tested or longitudinal studies could be conducted to find differences in memory over time. In the future, this can hopefully relate to human cognitive decline knowledge, as dogs show similar cognitive decline to humans, and help find treatments for cognitive diseases.
ContributorsGlomski, Marissa (Author) / Wynne, Clive (Thesis director) / Presson, Clive (Committee member) / Brewer, Gene (Committee member) / Department of Psychology (Contributor) / School of Social and Behavioral Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Fiddlevent is an event searching website written in Ruby on Rails. Fiddlevent enables any person to go online and find local events that interest him. Fiddlevent also enables merchants to post their events online. Fiddlevent explores all challenges of website development, such as project management, database design, user interface design, deployment and the software development lifecycle. Fiddlevent aims to utilize best practices for website and software development.
ContributorsThornton, Christopher Gordon (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Hurst, Charles (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Understanding categories and the way in which individuals classify and distinguish between these categories is vital to a number of cognitive functions. The present study introduced a new approach to dimensional identification by using identifiable properties rather than of ill-defined patterns. Although replication of studies that utilize well-defined features is necessary, the results of the study could potentially indicate some interesting findings regarding learning.
ContributorsShropshire, Jessica Lee (Author) / Homa, Donald (Thesis director) / Presson, Clark (Committee member) / Brewer, Gene (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor) / Department of Psychology (Contributor)
Created2013-05
Description
An introduction to neuroscientific thought aimed at an audience that is not educated in biology. Meant to be readable and easily understood by anyone with a high school education. The first section is completed in its entirety, with outlines for the proposed final sections to be completed over the next few years.
ContributorsNelson, Nicholas Alan (Author) / Olive, M. Foster (Thesis director) / Brewer, Gene (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-05
Description
Web-application development constantly changes \u2014 new programming languages, testing tools and programming methodologies are often proposed. The focus of this project is on the tool Selenium and the fairly new technique known as High Volume Automated Testing (HVAT). Both of these techniques were used to test the Just-in-Time Teaching and Learning Classroom Management System software. Selenium was used with a black-box testing technique and HVAT was employed in a white-box testing technique. Two of the major functionalities of this software were examined, which include the login and the professor functionality. The results of the black-box testing technique showed parts of the login component contain bugs, but the professor component is clean. HVAT white-box testing revealed error free implementation on the code level. We present an analysis on a new technique for HVAT testing with Selenium.
ContributorsEjaz, Samira (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Wilkerson, Kelly (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
We created an Android application, Impromp2, which allows users to search for and save events of interest to them in the Phoenix area. The backend, built on the Parse platform, gathers events daily using Web services and stores them in a database. Impromp2 was designed to improve upon similarly-purposed apps available for Android devices in several key ways, especially in user interface design and data interaction capability. This is a full-stack software project that explores databases and their performance considerations, Web services, user interface design, and the challenges of app development for a mobile platform.
ContributorsNorth, Joseph Robert (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Faucon, Philippe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
My proposed project is an educational application that will seek to simplify the<br/>process of internalizing the chord symbols most commonly seen by those learning<br/>musical improvisation. The application will operate like a game, encouraging the<br/>user to identify chord tones within time limits and award points for successfully<br/>doing so.
ContributorsOwens, Kevin Bradyn (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
DescriptionStudy invetsigated impacts of TDCS of the trigeminal region of the face, which resulted in improved reaction times and numerically, though not significantly, larger pupil diameters, indicating increased arousal.
ContributorsPope, Ben Alexander (Author) / Corbin, William (Thesis director) / Brewer, Gene (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Behavioral economics suggests that emotions can affect an individual’s decision making. Recent research on this idea’s application on large societies hints that there may exist some correlation or maybe even some causation relationship between public sentiment—at least what can be pulled from Twitter—and the movement of the stock market. One major result of consistent research on whether or not public sentiment can predict the movement of the stock market is that public sentiment, as a feature, is becoming more and more valid as a variable for stock-market-based machine learning models. While raw values typically serve as invaluable points of data, when training a model, many choose to “engineer” new features for their models—deriving rates of change or range values to improve model accuracy.
Since it doesn’t hurt to attempt to utilize feature extracted values to improve a model (if things don’t work out, one can always use their original features), the question may arise: how could the results of feature extraction on values such as sentiment affect a model’s ability to predict the movement of the stock market? This paper attempts to shine some light on to what the answer could be by deriving TextBlob sentiment values from Twitter data, and using Granger Causality Tests and logistic and linear regression to test if there exist a correlation or causation between the stock market and features extracted from public sentiment.
Since it doesn’t hurt to attempt to utilize feature extracted values to improve a model (if things don’t work out, one can always use their original features), the question may arise: how could the results of feature extraction on values such as sentiment affect a model’s ability to predict the movement of the stock market? This paper attempts to shine some light on to what the answer could be by deriving TextBlob sentiment values from Twitter data, and using Granger Causality Tests and logistic and linear regression to test if there exist a correlation or causation between the stock market and features extracted from public sentiment.
ContributorsYu, James (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This autoethnography is the culmination of years of migraine research and self-experimentation with alternative medicine to treat Hemiplegic Migraine (HM). HM is a rare phenomenon that is commonly misdiagnosed as a stroke or epilepsy disorder since the symptoms can include partial unilateral paralysis or weakness, visual disturbances, unilateral headache, vomiting, and trouble speaking. There is no known cure for HM, and current migraine medications can be accompanied by adverse side effects at an expensive cost. Alternative medicine, such as dietary supplementation, meditation, and positive thinking are potential options for working in relationship with HM episodes. This thesis explores HM as a personally transformative experience by learning to grow from pain.
ContributorsSchramm, Emily (Author) / Cloutier, Scott (Thesis director) / Brewer, Gene (Committee member) / School of Life Sciences (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05