Matching Items (51)
Filtering by
- All Subjects: Economics
- All Subjects: Education
- All Subjects: Cancer
- Creators: School of Mathematical and Statistical Sciences
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
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper explores how marginalist economics defines and inevitably constrains Victorian sensation fiction's content and composition. I argue that economic intuition implies that sensationalist heroes and antagonists, writers and readers all pursued a fundamental, "rational" aim: the attainment of pleasure. So although "sensationalism" took on connotations of moral impropriety in the Victorian age, sensation fiction primarily involves experiences of pain on the page that excite the reader's pleasure. As such, sensationalism as a whole can be seen as a conformist product, one which mirrors the effects of all commodities on the market, rather than as a rebellious one. Indeed, contrary to modern and contemporary critics' assumptions, sensation fiction may not be as scandalous as it seems.
ContributorsFischer, Brett Andrew (Author) / Bivona, Daniel (Thesis director) / Looser, Devoney (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Department of English (Contributor)
Created2014-12
Description
Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants. Debate is used as a testing ground for competing economic theories of taste-based and statistical discrimination, applied to a higher education context. The study finds persistent disparities in participation and success for female participants. Judges are more likely to vote for debaters who share their gender. There is also a significant disparity in the participation of racial and ethnic minority debaters and judges, as well as female judges.
ContributorsVered, Michelle Nicole (Author) / Silverman, Daniel (Thesis director) / Symonds, Adam (Committee member) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor)
Created2014-12
Description
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
According to the Tax Policy Center, a joint project of the Brookings Institution and Urban Institute, the Earned Income Tax Credit (EITC) will provide 26 million households with 60 billion dollars of reduced taxes and refunds in 2015 \u2014 resources that serve to lift millions of families above the federal poverty line. Responding to the popularity of EITC programs and recent discussion of its expansion for childless adults, I select three comparative case studies of state-level EITC reform from 2005 to 2013. Each state represents a different kind of policy reform: the creation of a supplemental credit in Connecticut, credit reduction in New Jersey, and finally credit expansion for childless adults in Maryland. For each case study, I use Current Population Survey panel data from the March Supplement to complete a differences-in-differences (DD) analysis of EITC policy changes. Specifically, I analyze effects of policy reform on total earned income, employment and usual hours worked. For comparison groups, I construct unique counterfactual populations of northeastern U.S. states, using people of color with less than a college degree as my treatment group for their increased sensitivity to EITC policy reform. I find no statistically significant effects of policy creation in Connecticut, significant decreases in employment and hours worked in New Jersey, and finally, significant increases in earnings and hours worked in Maryland. My work supports the findings of other empirical work, suggesting that awareness of new supplemental EITC programs is critical to their effectiveness while demonstrating that these types of programs can affect the labor supply and outcomes of eligible groups.
ContributorsRichard, Katherine Rose (Author) / Dillon, Eleanor Wiske (Thesis director) / Silverman, Daniel (Committee member) / Herbst, Chris (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor)
Created2015-05
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
A thorough understanding of the key concepts of logic is critical for student success. Logic is often not explicitly taught as its own subject in modern curriculums, which results in misconceptions among students as to what comprises logical reasoning. In addition, current standardized testing schemes often promote teaching styles which emphasize students' abilities to memorize set problem-solving methods over their capacities to reason abstractly and creatively. These phenomena, in tandem with halting progress in United States education compared to other developed nations, suggest that implementing logic courses into public schools and universities can better prepare students for professional careers and beyond. In particular, logic is essential for mathematics students as they transition from calculation-based courses to theoretical, proof-based classes. Many students find this adjustment difficult, and existing university-level courses which emphasize the technical aspects of symbolic logic do not fully bridge the gap between these two different approaches to mathematics. As a step towards resolving this problem, this project proposes a logic course which integrates historical, technical, and interdisciplinary investigations to present logic as a robust and meaningful subject warranting independent study. This course is designed with mathematics students in mind, with particular stresses on different formulations of deductively valid proof schemes. Additionally, this class can either be taught before existing logic classes in an effort to gradually expose students to logic over an extended period of time, or it can replace current logic courses as a more holistic introduction to the subject. The first section of the course investigates historical developments in studies of argumentation and logic throughout different civilizations; specifically, the works of ancient China, ancient India, ancient Greece, medieval Europe, and modernity are investigated. Along the way, several important themes are highlighted within appropriate historical contexts; these are often presented in an ad hoc way in courses emphasizing technical features of symbolic logic. After the motivations for modern symbolic logic are established, the key technical features of symbolic logic are presented, including: logical connectives, truth tables, logical equivalence, derivations, predicates, and quantifiers. Potential obstacles in students' understandings of these ideas are anticipated, and resolution methods are proposed. Finally, examples of how ideas of symbolic logic are manifested in many modern disciplines are presented. In particular, key concepts in game theory, computer science, biology, grammar, and mathematics are reformulated in the context of symbolic logic. By combining the three perspectives of historical context, technical aspects, and practical applications of symbolic logic, this course will ideally make logic a more meaningful and accessible subject for students.
ContributorsRyba, Austin (Author) / Vaz, Paul (Thesis director) / Jones, Donald (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Many fear that the growth of automation and artificial intelligence will lead to massive unemployment since human labor would no longer be needed. Although automation does displace workers from their current jobs, it is unclear the total net effect on jobs this period of advancement will have. One possible solution to help displaced workers is a Universal Basic Income. A Universal Basic Income(UBI) is a set payment paid to all members of society regardless of working status. Compared to current unemployment programs, a Universal Basic Income does not restrict participants in how to spend the money and is more inclusive. This paper examines the effects of a UBI on a person's motivation to work through a study on current college students. There is reason to believe that a Universal Basic Income will lead to fewer people working as people may become dependent on a base payment to meet their basic needs and not look for work. In addition, some people may drop out of their current jobs and rely on a UBI as their main form of income. The current literature does not offer a consensus opinion on this relationship and more studies are being completed with the threat of mass unemployment looming. This study shows the effects of a UBI on participants' willingness to work and then applies these results to the current economic model. With these results and new economic model, a decision about future policies surrounding a UBI can be made.
ContributorsAgarwal, Raghav (Author) / Pulido Hernadez, Carlos (Thesis director) / Foster, William (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
DescriptionThis project examines the television industry today, especially the field of educational programs. It includes the detailed implementation of one such show, a 30-minute demonstration of life skills, split into 3 segments. The pilot episode is also included.
ContributorsKesting, Amanda Jean (Author) / Alvarez, Melanie (Thesis director) / Snyder, Brian (Committee member) / Glaser, Ann (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor)
Created2013-05