Universal Basic Income is a proposed policy where the government would regularly pay all citizens in cash. The idea of a Universal Basic Income (UBI) has had a resurgence in recent years because of popular figures like Andrew Yang and Elon Musk, but its history and potential implications go deep into the structure of human society. This thesis delves into how a basic income would transform social concepts of work and disrupt the personal economic model. With the bargaining power and freedom granted by a basic income, workers would find themselves in a position of work freedom and choice that has never existed in human history. With new freedom to do as they wish, the place of work in people’s lives needs to be reimagined as a source of fulfillment instead of an unlikeable but necessary part of everyday life. Workers will be given the choice to leave unfair or unfulfilling work and decide for themselves how they want to contribute within society. From increasing mental and economic well-being for most Americans to serving as a response to unemployment trends in the automated future, to encouraging greater business innovation, there are myriad ways in which basic incomes have the potential to benefit society. Framed by Martin Luther King Jr. and Franklin Delano Roosevelt as the only policy capable of abolishing poverty forever, Universal Basic income will be an important feature of transformative innovative policy advocacy until it is adopted by a major world government at which point the effects in practice will become clear.

This paper outlines a responsible innovation framework to evaluate technologies designed for education. Traditionally, technologies being implemented for development of education come from foreign nations with less cultural understanding of the needs of the country they are trying to serve. This framework outlines categories that impact the success or failure of an educational technology. The framework is explained and then applied to the SolarSPELL case; an offline digital library designed to bring information to resource constrained areas around the world. The purpose of this research is to explore the factors determining success and failure of educational technology projects and design a framework that can be used moving forward to assess projects prior to the final implementation stage to encourage more successful projects. The framework designed in this research proved useful for evaluating educational technology designed for resource constrained areas.

Natural Language Processing (NLP) techniques have increasingly been used in finance, accounting, and economics research to analyze text-based information more efficiently and effectively than primarily human-centered methods. The literature is rich with computational textual analysis techniques applied to consistent annual or quarterly financial fillings, with promising results to identify similarities between documents and firms, in addition to further using this information in relation to other economic phenomena. Building upon the knowledge gained from previous research and extending the application of NLP methods to other categories of financial documents, this project explores financial credit contracts, better understanding the information provided through their textual data by assessing patterns and relationships between documents and firms. The main methods used throughout this project is Term Frequency-Inverse Document Frequency (to represent each document as a numerical vector), Cosine Similarity (to measure the similarity between contracts), and K-Means Clustering (to organically derive clusters of documents based on the text included in the contract itself). Using these methods, the dimensions analyzed are various grouping methodologies (external industry classifications and text derived classifications), various granularities (document-wise and firm-wise), various financial documents associated with a single firm (the relationship between credit contracts and 10-K product descriptions), and how various mean cosine similarity distributions change over time.

For my Barrett the Honors College senior thesis project, I decided to utilize my knowledge of curriculum design to create a set of learning Modules. I was influenced by my involvement in the Next Generation Service Corps to create these Modules around college student community impact. In the end I developed 6 Modules, each with 4-5 lessons and activities that focused on topics such as volunteerism, civic engagement, and meaningful careers. With interviews rolling through during the design process, I was able to iterate my design as I built it. The design was tested with 14 college students with positive feedback and engagement during the week-long period that it was available. Through this research and design, I found that such a collection of Modules could be beneficial to students to excite them about their potential and educate them about the opportunities that exist for them to take advantage of. This research could serve as a useful tool within the ASU community as an opportunity for the students to build up meaningful skills to create impact. ASU is passionate about education translating into real world applications and creating “changemakers”, and this collection has the opportunity to do just that.

As Big Data becomes more relevant, existing grouping and clustering algorithms will need to be evaluated for their effectiveness with large amounts of data. Previous work in Similarity Grouping proposes a possible alternative to existing data analytics tools, which acts as a hybrid between fast grouping and insightful clustering. We, the SimCloud Team, proposed Distributed Similarity Group-by (DSG), a distributed implementation of Similarity Group By. Experimental results show that DSG is effective at generating meaningful clusters and has a lower runtime than K-Means, a commonly used clustering algorithm. This document presents my personal contributions to this team effort. The contributions include the multi-dimensional synthetic data generator, execution of the Increasing Scale Factor experiment, and presentations at the NCURIE Symposium and the SISAP 2019 Conference.

Design Thinking is a popular topic and problem-solving method that is gaining attention and being used more and more often across disciplines in recent years such as “IT, Business, Education and Medicine” (Dorst, 2011). Its ability to address wicked problems, problems that are inherently complex and socially layered, has branded it an attractive and useful problem-solving method for a wide range of industries and consequently a wide range of problems. Its human centered and empathetic approach to addressing problems also paints design thinking to be an action-based method that works well with interdisciplinary teams in which all members have the same desired end. More recently, its use has expanded to the field of education and is being cited as a way to develop 21st century learners and redefine the field of education as a whole. This paper intends to examine design thinking in the context of the Mary Lou Fulton Teachers College of Arizona State University specifically. The goals of this paper are to define design thinking for the educational field, examine and analyze the methods of it use, as well as determine the purpose for exposing undergraduate education students to the process. Through expert interviews of faculty and staff members that were analyzed for common themes and other consistencies, an understanding of how the Mary Lou Fulton Teachers College defines design thinking is obtained, as well as the various uses and applications of design thinking skills and process for the field of education. The paper describes multiple areas in which design thinking is being implemented internally, externally, and within teacher preparation curriculum through the Mary Lou Fulton Teachers College and details the four main reasons for exposing future teachers to design thinking practices and principles.

Cosmic horror distinguishes itself from standard horror in large part because of the things that it finds horrifying. Cosmic horror, like any horror, attaches itself to external experience. Powerful technologies’ ability to reshape our perspective are the ideal choice for this anchor point. Beyond the Wall of Sound is a podcast that seeks to unify the existential dread and scientific imaginings inherent in cosmic horror and weird fiction, with dystopian visions of technological futures. The podcast uses the strange and horrifying mind of HP Lovecraft, as revealed through his short stories, to shed light on the horrifying, revealing and absurd imaginaries that drive and emerge unintentionally from current pursuits in science and technological innovation. In this essay, I describe the roots of horror and its relevance and therefore applicability to human experience. I then exemplarily relate the practical mode of thought that created one of the podcast’s episodes, which take’s Lovecraft’s The Thing on the Doorstep and the authors fears of the future as a lens to discuss and reflect upon the technology of body switching. The podcast is presented as an important piece of science communication in the face of increasing misinformation and a rolling technological wave. The project is affected by the strength of Lovecraft’s influences over time, and ultimately is itself a vehicle for and a deconstruction of that influence. Ultimately, the purpose of this podcast is not to horrify, but to inspire people to do good and remain educated despite the horrors of a pessimistic and uncaring existence.

This project focuses on using Neutral Gas and Ion Mass Spectrometer (NGIMS) density data for carbon dioxide, oxygen, carbon monoxide, and nitrogen during deep dip campaigns 5, 6, and 8. Density profiles obtained from NGIMS were plotted against simulated density profiles from the Mars Global Ionosphere-Thermosphere Model (MGITM). Averaged temperature profiles were also plotted for the three deep dip campaigns, using NGIMS data and MGITM output. MGITM was also used as a tool to uncover potential heat balance terms needed to reproduce the mean density and temperature profiles measured by NGIMS.

This method of using NGIMS data as a validation tool for MGITM simulations has been tested previously using dayside data from deep dip campaigns 2 and 8. In those cases, MGITM was able to accurately reproduce the measured density and temperature profiles; however, in the deep dip 5 and 6 campaigns, the results are not quite the same, due to the highly variable nature of the nightside thermosphere. MGITM was able to fairly accurately reproduce the density and temperature profiles for deep dip 5, but the deep dip 6 model output showed unexpected significant variation. The deep dip 6 results reveal possible changes to be made to MGITM to more accurately reflect the observed structure of the nighttime thermosphere. In particular, upgrading the model to incorporate a suitable gravity wave parameterization should better capture the role of global winds in maintaining the nighttime thermospheric structure.

This project reveals that there still exist many unknowns about the structure and dynamics of the night side of the Martian atmosphere, as well as significant diurnal variations in density. Further study is needed to uncover these unknowns and their role in atmospheric mass loss.

Within our current educational infrastructure, there’s a lack of substantial preventive care knowledge present among elementary schoolchildren. With education cuts occurring statewide, many schools are left impoverished and schools are incapable of implementing various programs to benefit their local communities. This endeavor aims to visit public and charter elementary schools in the Phoenix Valley to educate youth regarding easily avoidable health risks by implementing healthy eating habits and exercise. Project BandAid will immerse students ages 7-9 in hands-on activities to enhance their knowledge on hygiene, healthy eating habits, and safety. This project incorporated funding from the Woodside Community Action Grant and Barrett, the Honors College as well as the help from Alpha Epsilon Delta (AED) volunteers.

This project examined the relationship of science teachers' knowledge about the laws relating to the teaching of creationism/evolution in public schools using multiple demographic factors. Overall, teachers correctly identified only 7 out of 10 "yes" or "no" answers about the laws, this score is only slightly better than the expected 5 out of 10 that would be obtained from guessing. Statistically significant results in differences in the overall score on the survey were found for three major variables. Teachers who say creationism should be taught in the classroom have a lower score than those who say it should not be taught in the classroom, with a large effect size. Teachers who teach biology or a life science had significantly higher scores than those who do not, with a small/medium effect size. Older teachers had significantly higher scores than younger teachers, with a small effect size. Identifying the demographic variables that effect teacher knowledge about the laws is the first step to determining how to educate teachers on the legality teaching of creationism/evolution in public school classrooms to avoid violations of the First Amendment.