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- Creators: Barrett, The Honors College
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Description
There is still a major underrepresentation of females in STEM fields, with many girls beginning to lose interest as early as middle school. This is due to a variety of factors including lack of role models, stereotypes, ineffective teaching methods, and peer influence. A popular way to increase female interest is through day camps and other programs where girls complete a variety of activities related to science and engineering. These activities are usually designed around problem-based learning, a student-lead approach to teaching that requires students to work collaboratively and use background knowledge to solve some sort of given problem. In this project, a day camp for middle school girls was created and implemented to increase student interest in STEM through three problem-based learning activities. By analyzing survey data, it was concluded that the camp was successful in increasing interest and changing participants' attitudes towards science. This approach to learning could be applied to other subject areas, including mathematics, to increase the interest of both male and female students at the secondary level.
ContributorsVitale, Nathalie Maria (Author) / Walters, Molina (Thesis director) / Oliver, Jill (Committee member) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
To supplement lectures, various resources are available to students; however, little research has been done to look systematically at which resources studies find most useful and the frequency at which they are used. We have conducted a preliminary study looking at various resources available in an introductory material science course over four semesters using a custom survey called the Student Resource Value Survey (SRVS). More specifically, the SRVS was administered before each test to determine which resources students use to do well on exams. Additionally, over the course of the semester, which resources students used changed. For instance, study resources for exams including the use of homework problems decreased from 81% to 50%, the utilization of teaching assistant for exam studying increased from 25% to 80%, the use of in class Muddiest Points for exam study increased form 28% to 70%, old exams and quizzes only slightly increased for exam study ranging from 78% to 87%, and the use of drop-in tutoring services provided to students at no charge decreased from 25% to 17%. The data suggest that students thought highly of peer interactions by using those resources more than tutoring centers. To date, no research has been completed looking at courses at the department level or a different discipline. To this end, we adapted the SRVS administered in material science to investigate resource use in thirteen biomedical engineering (BME) courses. Here, we assess the following research question: "From a variety of resources, which do biomedical engineering students feel addresses difficult concept areas, prepares them for examinations, and helps in computer-aided design (CAD) and programming the most and with what frequency?" The resources considered include teaching assistants, classroom notes, prior exams, homework problems, Muddiest Points, office hours, tutoring centers, group study, and the course textbook. Results varied across the four topical areas: exam study, difficult concept areas, CAD software, and math-based programming. When preparing for exams and struggling with a learning concept, the most used and useful resources were: 1) homework problems, 2) class notes and 3) group studying. When working on math-based programming (Matlab and Mathcad) as well as computer-aided design, the most used and useful resources were: 1) group studying, 2) engineering tutoring center, and 3) undergraduate teaching assistants. Concerning learning concepts and exams in the BME department, homework problems and class notes were considered some of the highest-ranking resources for both frequency and usefulness. When comparing to the pilot study in MSE, both BME and MSE students tend to highly favor peer mentors and old exams as a means of studying for exams at the end of the semester1. Because the MSE course only considered exams, we cannot make any comparisons to BME data concerning programming and CAD. This analysis has highlighted potential resources that are universally beneficial, such as the use of peer work, i.e. group studying, engineering tutoring center, and teaching assistants; however, we see differences by both discipline and topical area thereby highlighting the need to determine important resources on a class-by-class basis as well.
ContributorsMalkoc, Aldin (Author) / Ankeny, Casey (Thesis director) / Krause, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Studies have shown that arts programs have a positive impact on students' abilities to achieve academic success, showcase creativity, and stay focused inside and outside of the classroom. However, as school funding drops, arts programs are often the first to be cut from school curricula. Rather than drop art completely, general education teachers have the opportunity to integrate arts instruction with other content areas in their classrooms. Traditional fraction lessons and Music-infused fraction lessons were administered to two classes of fourth-grade students. The two types of lessons were presented over two separate days in each classroom. Mathematics worksheets and attitudinal surveys were administered to each student in each classroom after each lesson to gauge their understanding of the mathematics content as well as their self-perceived understanding, enjoyment and learning related to the lessons. Students in both classes were found to achieve significantly higher mean scores on the traditional fraction lesson than the music-infused fraction lesson. Lower scores in the music-infused fraction lesson may have been due to the additional component of music for students unfamiliar with music principles. Students tended to express satisfaction for both lessons. In future studies, it would be recommended to spend additional lesson instruction time on the principles of music in order help students reach deeper understanding of the music-infused fraction lesson. Other recommendations include using colorful visuals and interactive activities to establish both fraction and music concepts.
ContributorsGerrish, Julie Kathryn (Author) / Zambo, Ronald (Thesis director) / Hutchins, Catherine (Committee member) / Division of Teacher Preparation (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Over the past few years, the issue of childhood trauma in the United States has become significant. A growing number of children are experiencing abuse, neglect, or some other form of maltreatment each year. Considering the stressful home lives of maltreated children, the one sure sanctuary is school. However, this idea requires teachers to be actively involved in identifying and caring for the children who need it most. Traumatic childhood experiences leave lasting scars on its victims, so it is helpful if teachers learn how to identify and support children who have lived through them. It is unfortunate that teachers will most likely encounter children throughout their career who have experienced horrendous things, but it is a reality. With this being said, teachers need to develop an understanding of what traumatized children live with, and learn how to address these issues with skilled sensitivity. Schools are not just a place where children learn how to read and write; they build the foundation for a successful life. This project was designed to provide teachers with a necessary resource for helping children who have suffered traumatic experiences. The methodology of this project began with interviews with organizations specializing in working with traumatized children such as Arizonans for Children, Free Arts for Abused Children, The Sojourner Center, and UMOM. The next step was a review of the current literature on the subject of childhood trauma. The findings have all been compiled into one, convenient document for teacher use and distribution. Upon completion of this document, an interactive video presentation will be made available through an online education website, so that distribution will be made simpler. Hopefully, teachers will share the information with people in their networks and create a chain reaction. The goal is to make it available to as many teachers as possible, so that more children will receive the support they need.
ContributorsHanrahan, Katelyn Ann (Author) / Dahlstrom, Margo (Thesis director) / Kelley, Michael (Committee member) / Division of Teacher Preparation (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Agent based models allow for complex results from simple parameters. The mobile agents in my model, the firms, are allocated an amount of capital, while the static agents, the workers, are allocated a range of wages. The firms are then allowed to move around and compete until they match with a worker that maximizes their production. It was found from the simulation that as competition increases so do wages. It was also found that when firms stay in the environment for longer that a higher wage is possible as a result of a larger window for drawn out competition. The different parameters result in a range of equilibriums that take variable amounts of time to reach. These results are interesting because they demonstrate that the mean wage is strongly dependent upon the window of time that firms are able to compete within. This type of model was useful because it demonstrated that there is a variation in the time dependence of the equilibrium. It also demonstrated that when there is very little entry and exiting of the market, that wage levels out at an equilibrium that is the same, regardless of the ratio between the number of firms and the number of workers. Further work to be done on this model includes the addition of a Matching Function so that firms and workers have a more fair agreement. I will also be adding parameters that allow for firms to see the workers around them so that firms are able to interact with multiple workers at the same time. Both of these alteration should improve the overall accuracy of the model.
ContributorsElledge, Jacob Morris (Author) / Veramendi, Gregory (Thesis director) / Murphy, Alvin (Committee member) / Department of Economics (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Cancer remains one of the leading killers throughout the world. Death and disability due to lung cancer in particular accounts for one of the largest global economic burdens a disease presents. The burden on third-world countries is especially large due to the unusually large financial stress that comes from late tumor detection and expensive treatment options. Early detection using inexpensive techniques may relieve much of the burden throughout the world, not just in more developed countries. I examined the immune responses of lung cancer patients using immunosignatures – patterns of reactivity between host serum antibodies and random peptides. Immunosignatures reveal disease-specific patterns that are very reproducible. Immunosignaturing is a chip-based method that has the ability to display the antibody diversity from individual sera sample with low cost. Immunosignaturing is a medical diagnostic test that has many applications in current medical research and in diagnosis. From a previous clinical study, patients diagnosed for lung cancer were tested for their immunosignature vs. healthy non-cancer volunteers. The pattern of reactivity against the random peptides (the ‘immunosignature’) revealed common signals in cancer patients, absent from healthy controls. My study involved the search for common amino acid motifs in the cancer-specific peptides. My search through the hundreds of ‘hits’ revealed certain motifs that were repeated more times than expected by random chance. The amino acids that were the most conserved in each set include tryptophan, aspartic acid, glutamic acid, proline, alanine, serine, and lysine. The most overall conserved amino acid observed between each set was D - aspartic acid. The motifs were short (no more than 5-6 amino acids in a row), but the total number of motifs I identified was large enough to assure significance. I utilized Excel to organize the large peptide sequence libraries, then CLUSTALW to cluster similar-sequence peptides, then GLAM2 to find common themes in groups of peptides. In so doing, I found sequences that were also present in translated cancer expression libraries (RNA) that matched my motifs, suggesting that immunosignatures can find cancer-specific antigens that can be both diagnostic and potentially therapeutic.
ContributorsShiehzadegan, Shima (Author) / Johnston, Stephen (Thesis director) / Stafford, Phillip (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This paper explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a degree of disregard for the risks accompanying these investments. As the former Citibank chairman, Walter Wriston articulated, "Countries don't go bust" (This Time is Different, 51). Still, unexpected negative externalities have shattered this idea as the majority of developing economies follow a cyclical pattern of default. As coined by Reinhart and Rogoff, sovereign governments that fall into this continuous cycle have become known as serial defaulters. Most developed markets have not defaulted since World War II, thus escaping this persistent trap. Still, there have been developing economies that have been able to transition out of serial defaulting. These economies are able to leverage debt to compound growth without incurring the protracted consequences of a default. Although the cases are few, we argue that developing markets such as Chile, Mexico, Russia, and Uruguay have been able to escape this vicious cycle. Thus, our research indicates that collaborative debt restructurings coupled with long term economic policies are imperative to transitioning out of debt intolerance and into a sustainable debt position. Successful economies are able to leverage debt to create strong foundational growth rather than gambling with debt in the hopes of achieving rapid catch- up growth.
ContributorsPitt, Ryan (Co-author) / Martinez, Nick (Co-author) / Choueiri, Robert (Co-author) / Goegan, Brian (Thesis director) / Silverman, Daniel (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
A growing number of jobs in the US require a college degree or technical education, and the wage difference between jobs requiring a high school diploma and a college education has increased to over $17,000 per year. Enrollment levels in postsecondary education have been rising for at least the past decade, and this paper attempts to tease out how much of the increasing enrollment is due to changes in the demand by companies for workers. A Bartik Instrument, which is a measure of local area labor demand, for each county in the US was constructed from 2007 to 2014, and using multivariate linear regression the effect of changing labor demand on local postsecondary education enrollment rates was examined. A small positive effect was found, but the effect size in relation to the total change in enrollment levels was diminutive. From the start to the end of the recession (2007 to 2010), Bartik Instrument calculated unemployment increased from 5.3% nationally to 8.2%. This level of labor demand contraction would lead to a 0.42% increase in enrollment between 2008 and 2011. The true enrollment increase over this period was 7.6%, so the model calculated 5.5% of the enrollment increase was based on the changes in labor demand.
ContributorsHerder, Daniel Steven (Author) / Dillon, Eleanor (Thesis director) / Schoellman, Todd (Committee member) / Economics Program in CLAS (Contributor) / Department of Psychology (Contributor) / Sandra Day O'Connor College of Law (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
In a dormant state, cancer cells survive chemotherapy leaving the opportunity for cancer cell relapse and metastasis ultimately leading to patient death. A novel aminoglycoside-based hydrogel ‘Amikagel’ developed in Dr. Rege’s lab serves as a platform for a 3D tumor microenvironment (3DTM) mimicking cancer cell dormancy and relapse. Six Amikagels of varying mechanical stiffness and adhesivities were synthesized and evaluated as platforms for 3DTM formation through cell viability and cell cycle arrest analyses. The impact of fetal bovine serum concentration and bovine serum albumin concentration in the media were studied for their impact on 3DTM formation. These experiments allow us to identify the best possible Amikagel formulation for 3DTM.
ContributorsGjertsen, Haley Nicole (Author) / Rege, Kaushal (Thesis director) / Grandhi, Taraka Sai Pavan (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can be used to understand the image better through recognizing different features present within the image. Deep CNNs, however, require training sets that can be larger than a million pictures in order to fine tune their feature detectors. For the case of facial expression datasets, none of these large datasets are available. Due to this limited availability of data required to train a new CNN, the idea of using naïve domain adaptation is explored. Instead of creating and using a new CNN trained specifically to extract features related to FER, a previously trained CNN originally trained for another computer vision task is used. Work for this research involved creating a system that can run a CNN, can extract feature vectors from the CNN, and can classify these extracted features. Once this system was built, different aspects of the system were tested and tuned. These aspects include the pre-trained CNN that was used, the layer from which features were extracted, normalization used on input images, and training data for the classifier. Once properly tuned, the created system returned results more accurate than previous attempts on facial expression recognition. Based on these positive results, naïve domain adaptation is shown to successfully leverage advantages of deep CNNs for facial expression recognition.
ContributorsEusebio, Jose Miguel Ang (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05