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Description
Geology and its tangential studies, collectively known and referred to in this thesis as geosciences, have been paramount to the transformation and advancement of society, fundamentally changing the way we view, interact and live with the surrounding natural and built environment. It is important to recognize the value and importance of this interdisciplinary scientific field while reconciling its ties to imperial and colonizing extractive systems which have led to harmful and invasive endeavors. This intersection among geosciences, (environmental) justice studies, and decolonization is intended to promote inclusive pedagogical models through just and equitable methodologies and frameworks as to prevent further injustices and promote recognition and healing of old wounds. By utilizing decolonial frameworks and highlighting the voices of peoples from colonized and exploited landscapes, this annotated syllabus tackles the issues previously described while proposing solutions involving place-based education and the recentering of land within geoscience pedagogical models. (abstract)
ContributorsReed, Cameron E (Author) / Richter, Jennifer (Thesis director) / Semken, Steven (Committee member) / School of Earth and Space Exploration (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
For as long as humans have been working, they have been looking for ways to get that work done better, faster, and more efficient. Over the course of human history, mankind has created innumerable spectacular inventions, all with the goal of making the economy and daily life more efficient. Today, innovations and technological advancements are happening at a pace like never seen before, and technology like automation and artificial intelligence are poised to once again fundamentally alter the way people live and work in society. Whether society is prepared or not, robots are coming to replace human labor, and they are coming fast. In many areas artificial intelligence has disrupted entire industries of the economy. As people continue to make advancements in artificial intelligence, more industries will be disturbed, more jobs will be lost, and entirely new industries and professions will be created in their wake. The future of the economy and society will be determined by how humans adapt to the rapid innovations that are taking place every single day. In this paper I will examine the extent to which automation will take the place of human labor in the future, project the potential effect of automation to future unemployment, and what individuals and society will need to do to adapt to keep pace with rapidly advancing technology. I will also look at the history of automation in the economy. For centuries humans have been advancing technology to make their everyday work more productive and efficient, and for centuries this has forced humans to adapt to the modern technology through things like training and education. The thesis will additionally examine the ways in which the U.S. education system will have to adapt to meet the demands of the advancing economy, and how job retraining programs must be modernized to prepare workers for the changing economy.
ContributorsCunningham, Reed P. (Author) / DeSerpa, Allan (Thesis director) / Haglin, Brett (Committee member) / School of International Letters and Cultures (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper considers what factors influence student interest, motivation, and continued engagement. Studies show anticipated extrinsic rewards for activity participation have been shown to reduce intrinsic value for that activity. This might suggest that grade point average (GPA) has a similar effect on academic interests. Further, when incentives such as scholarships, internships, and careers are GPA-oriented, students must adopt performance goals in courses to guarantee success. However, performance goals have not been shown to correlated with continued interest in a topic. Current literature proposes that student involvement in extracurricular activities, focused study groups, and mentored research are crucial to student success. Further, students may express either a fixed or growth mindset, which influences their approach to challenges and opportunities for growth. The purpose of this study was to collect individual cases of students' experiences in college. The interview method was chosen to collect complex information that could not be gathered from standard surveys. To accomplish this, questions were developed based on content areas related to education and motivation theory. The content areas included activities and meaning, motivation, vision, and personal development. The developed interview method relied on broad questions that would be followed by specific "probing" questions. We hypothesize that this would result in participant-led discussions and unique narratives from the participant. Initial findings suggest that some of the questions were effective in eliciting detailed responses, though results were dependent on the interviewer. From the interviews we find that students value their group involvements, leadership opportunities, and relationships with mentors, which parallels results found in other studies.
ContributorsAbrams, Sara (Author) / Hartwell, Lee (Thesis director) / Correa, Kevin (Committee member) / Department of Psychology (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Aside from uplifting and tearing down the mood of a young LGBTQ+ kid, journalistic media has the potential to alter the way audiences understand and react to individuals of the LGBTQ+ community. Looking at the rhetorical approaches, frameworks, and expanded narratives of news sources, this project engages with the concepts of same-sex marriage, lifestyles, bans, and children in education in order to attain an understanding of what media messages are being shared, how they are being communicated, and what the implications of such rhetoric are. Summary of the findings:
• Same-sex marriage as the win that cannot be repeated.
Infamously known as the central legal battle for the LGBTQ+ community, same-sex marriage finds itself in many political speeches, campaigns, and social commentaries. Interestingly, after being legalized through a Supreme Court decision in the United States, Same-Sex Marriage finds itself framed as the social inevitability that should not be repeated in politics or any legal shift. In other words, “the gays have won this battle, but not the war.”
• There are risks around the “LGBTQ+ lifestyle” and its careful catering to an elite minority and the mediation through bans.
The risks of the LGBTQ+ “lifestyle” date back far, with many connotations being attached to being LGBTQ+ (AIDS epidemics, etc.). In modern journalism, many media outlets portray LGBTQ+ individuals to be a tiny minority (.001% according to some) that demands the whole society to adhere to their requests. This framework portrays the LGBTQ+ community as oppressors and obsessed advocates that can never “seem to get enough” (ex: more than just marriage). The bans are framed as the neutralizing factor to the catering.
• LGBTQ+ children and topics in academic and social spaces are the extreme degree.
When it comes to LGBTQ+ issues and conversations as they revolve around children, media outlets have some of the most passionate opinions about them. Often portrayed as “the line that shouldn’t be crossed,” LGBTQ+ issues, as they find themselves in schools and other spaces, are thus portrayed as bearable to a certain degree, never completely. Claims of indoctrination are also presented prominently even when institutional efforts are to protect LGBTQ+ kids.
• Same-sex marriage as the win that cannot be repeated.
Infamously known as the central legal battle for the LGBTQ+ community, same-sex marriage finds itself in many political speeches, campaigns, and social commentaries. Interestingly, after being legalized through a Supreme Court decision in the United States, Same-Sex Marriage finds itself framed as the social inevitability that should not be repeated in politics or any legal shift. In other words, “the gays have won this battle, but not the war.”
• There are risks around the “LGBTQ+ lifestyle” and its careful catering to an elite minority and the mediation through bans.
The risks of the LGBTQ+ “lifestyle” date back far, with many connotations being attached to being LGBTQ+ (AIDS epidemics, etc.). In modern journalism, many media outlets portray LGBTQ+ individuals to be a tiny minority (.001% according to some) that demands the whole society to adhere to their requests. This framework portrays the LGBTQ+ community as oppressors and obsessed advocates that can never “seem to get enough” (ex: more than just marriage). The bans are framed as the neutralizing factor to the catering.
• LGBTQ+ children and topics in academic and social spaces are the extreme degree.
When it comes to LGBTQ+ issues and conversations as they revolve around children, media outlets have some of the most passionate opinions about them. Often portrayed as “the line that shouldn’t be crossed,” LGBTQ+ issues, as they find themselves in schools and other spaces, are thus portrayed as bearable to a certain degree, never completely. Claims of indoctrination are also presented prominently even when institutional efforts are to protect LGBTQ+ kids.
ContributorsNieto Calderon, Ramon Antonio (Author) / Himberg, Julia (Thesis director) / Sturges, Robert (Committee member) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Social-emotional learning (SEL) methods are beginning to receive global attention in primary school education, yet the dominant emphasis on implementing these curricula is in high-income, urbanized areas. Consequently, the unique features of developing and integrating such methods in middle- or low-income rural areas are unclear. Past studies suggest that students exposed to SEL programs show an increase in academic performance, improved ability to cope with stress, and better attitudes about themselves, others, and school, but these curricula are designed with an urban focus. The purpose of this study was to conduct a needs-based analysis to investigate components specific to a SEL curriculum contextualized to rural primary schools. A promising organization committed to rural educational development is Barefoot College, located in Tilonia, Rajasthan, India. In partnership with Barefoot, we designed an ethnographic study to identify and describe what teachers and school leaders consider the highest needs related to their students' social and emotional education. To do so, we interviewed 14 teachers and school leaders individually or in a focus group to explore their present understanding of “social-emotional learning” and the perception of their students’ social and emotional intelligence. Analysis of this data uncovered common themes among classroom behaviors and prevalent opportunities to address social and emotional well-being among students. These themes translated into the three overarching topics and eight sub-topics explored throughout the curriculum, and these opportunities guided the creation of the 21 modules within it. Through a design-based research methodology, we developed a 40-hour curriculum by implementing its various modules within seven Barefoot classrooms alongside continuous reiteration based on teacher feedback and participant observation. Through this process, we found that student engagement increased during contextualized SEL lessons as opposed to traditional methods. In addition, we found that teachers and students preferred and performed better with an activities-based approach. These findings suggest that rural educators must employ particular teaching strategies when addressing SEL, including localized content and an experiential-learning approach. Teachers reported that as their approach to SEL shifted, they began to unlock the potential to build self-aware, globally-minded students. This study concludes that social and emotional education cannot be treated in a generalized manner, as curriculum development is central to the teaching-learning process.
ContributorsBucker, Delaney Sue (Author) / Carrese, Susan (Thesis director) / Barab, Sasha (Committee member) / School of Life Sciences (Contributor, Contributor) / School of Civic & Economic Thought and Leadership (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
How do you convey what’s interesting and important to you as an artist in a digital world of constantly shifting attentions? For many young creatives, the answer is original characters, or OCs. An OC is a character that an artist creates for personal enjoyment, whether based on an already existing story or world, or completely from their own imagination.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
ContributorsCote, Jacqueline (Author) / Button, Melissa M (Thesis director) / Dove-Viebahn, Aviva (Committee member) / School of Art (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Leveraging Machine Learning and Wireless Sensing for Robot Localization - Location Variance Analysis
Description
Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic indoor or urban environments. Using recent improvements in the field of machine learning, this project proposes a new method of localization using networks with several wireless transceivers and implemented without heavy computational loads or high costs. This project aims to build a proof-of-concept prototype and demonstrate that the proposed technique is feasible and accurate.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
ContributorsChang, Roger (Co-author) / Kann, Trevor (Co-author) / Alkhateeb, Ahmed (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In the past ten years, the United States’ sound recording industries have experienced significant decreases in employment opportunities for aspiring audio engineers from economic imbalances in the music industry’s digital streaming era and reductions in government funding for career and technical education (CTE). The Recording Industry Association of America reports promises of music industry sustainability based on increasing annual revenues in paid streaming services and artists’ high creative demand. The rate of new audio engineer entries in the sound recording subsection of the music industry is not viable to support streaming artists’ high demand to engineer new music recordings. Offering CTE programs in secondary education is rare for aspiring engineers with insufficient accessibility to pursue a post-secondary or vocational education because of financial and academic limitations. These aspiring engineers seek alternatives for receiving an informal education in audio engineering on the Internet using video sharing services like YouTube to search for tutorials and improve their engineering skills. The shortage of accessible educational materials on the Internet restricts engineers from advancing their own audio engineering education, reducing opportunities to enter a desperate job market in need of independent, home studio-based engineers. Content creators on YouTube take advantage of this situation and commercialize their own video tutorial series for free and selling paid subscriptions to exclusive content. This is misleading for newer engineers because these tutorials omit important understandings of fundamental engineering concepts. Instead, content creators teach inflexible engineering methodologies that are mostly beneficial to their own way of thinking. Content creators do not often assess the incompatibility of teaching their own methodologies to potential entrants in a profession that demands critical thinking skills requiring applied fundamental audio engineering concepts and techniques. This project analyzes potential solutions to resolve the deficiencies in online audio engineering education and experiments with structuring simple, deliverable, accessible educational content and materials to new entries in audio engineering. Designing clear, easy to follow material to these new entries in audio engineering is essential for developing a strong understanding for the application of fundamental concepts in future engineers’ careers. Approaches to creating and designing educational content requires translating complex engineering concepts through simplified mediums that reduce limitations in learning for future audio engineers.
ContributorsBurns, Triston Connor (Author) / Tobias, Evan (Thesis director) / Libman, Jeff (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson’s would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson’s disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson’s disease dataset comprised of healthy-elderly, healthy-young and Parkinson’s disease patients.
ContributorsRahman, Farhan Nadir (Co-author) / Nawar, Afra (Co-author) / Turaga, Pavan (Thesis director) / Krishnamurthi, Narayanan (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In this project, the use of deep neural networks for the process of selecting actions to execute within an environment to achieve a goal is explored. Scenarios like this are common in crafting based games such as Terraria or Minecraft. Goals in these environments have recursive sub-goal dependencies which form a dependency tree. An agent operating within these environments have access to low amounts of data about the environment before interacting with it, so it is crucial that this agent is able to effectively utilize a tree of dependencies and its environmental surroundings to make judgements about which sub-goals are most efficient to pursue at any point in time. A successful agent aims to minimizes cost when completing a given goal. A deep neural network in combination with Q-learning techniques was employed to act as the agent in this environment. This agent consistently performed better than agents using alternate models (models that used dependency tree heuristics or human-like approaches to make sub-goal oriented choices), with an average performance advantage of 33.86% (with a standard deviation of 14.69%) over the best alternate agent. This shows that machine learning techniques can be consistently employed to make goal-oriented choices within an environment with recursive sub-goal dependencies and low amounts of pre-known information.
ContributorsKoleber, Derek (Author) / Acuna, Ruben (Thesis director) / Bansal, Ajay (Committee member) / W.P. Carey School of Business (Contributor) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05