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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

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
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Description
Covering subsequences with sets of permutations arises in many applications, including event-sequence testing. Given a set of subsequences to cover, one is often interested in knowing the fewest number of permutations required to cover each subsequence, and in finding an explicit construction of such a set of permutations that has

Covering subsequences with sets of permutations arises in many applications, including event-sequence testing. Given a set of subsequences to cover, one is often interested in knowing the fewest number of permutations required to cover each subsequence, and in finding an explicit construction of such a set of permutations that has size close to or equal to the minimum possible. The construction of such permutation coverings has proven to be computationally difficult. While many examples for permutations of small length have been found, and strong asymptotic behavior is known, there are few explicit constructions for permutations of intermediate lengths. Most of these are generated from scratch using greedy algorithms. We explore a different approach here. Starting with a set of permutations with the desired coverage properties, we compute local changes to individual permutations that retain the total coverage of the set. By choosing these local changes so as to make one permutation less "essential" in maintaining the coverage of the set, our method attempts to make a permutation completely non-essential, so it can be removed without sacrificing total coverage. We develop a post-optimization method to do this and present results on sequence covering arrays and other types of permutation covering problems demonstrating that it is surprisingly effective.
ContributorsMurray, Patrick Charles (Author) / Colbourn, Charles (Thesis director) / Czygrinow, Andrzej (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2014-12
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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

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
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
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Description
In many systems, it is difficult or impossible to measure the phase of a signal. Direct recovery from magnitude is an ill-posed problem. Nevertheless, with a sufficiently large set of magnitude measurements, it is often possible to reconstruct the original signal using algorithms that implicitly impose regularization conditions on this

In many systems, it is difficult or impossible to measure the phase of a signal. Direct recovery from magnitude is an ill-posed problem. Nevertheless, with a sufficiently large set of magnitude measurements, it is often possible to reconstruct the original signal using algorithms that implicitly impose regularization conditions on this ill-posed problem. Two such algorithms were examined: alternating projections, utilizing iterative Fourier transforms with manipulations performed in each domain on every iteration, and phase lifting, converting the problem to that of trace minimization, allowing for the use of convex optimization algorithms to perform the signal recovery. These recovery algorithms were compared on a basis of robustness as a function of signal-to-noise ratio. A second problem examined was that of unimodular polyphase radar waveform design. Under a finite signal energy constraint, the maximal energy return of a scene operator is obtained by transmitting the eigenvector of the scene Gramian associated with the largest eigenvalue. It is shown that if instead the problem is considered under a power constraint, a unimodular signal can be constructed starting from such an eigenvector that will have a greater return.
ContributorsJones, Scott Robert (Author) / Cochran, Douglas (Thesis director) / Diaz, Rodolfo (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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Description
Previous research discusses students' difficulties in grasping an operational understanding of covariational reasoning. In this study, I interviewed four undergraduate students in calculus and pre-calculus classes to determine their ways of thinking when working on an animated covariation problem. With previous studies in mind and with the use of technology,

Previous research discusses students' difficulties in grasping an operational understanding of covariational reasoning. In this study, I interviewed four undergraduate students in calculus and pre-calculus classes to determine their ways of thinking when working on an animated covariation problem. With previous studies in mind and with the use of technology, I devised an interview method, which I structured using multiple phases of pre-planned support. With these interviews, I gathered information about two main aspects about students' thinking: how students think when attempting to reason covariationally and which of the identified ways of thinking are most propitious for the development of an understanding of covariational reasoning. I will discuss how, based on interview data, one of the five identified ways of thinking about covariational reasoning is highly propitious, while the other four are somewhat less propitious.
ContributorsWhitmire, Benjamin James (Author) / Thompson, Patrick (Thesis director) / Musgrave, Stacy (Committee member) / Moore, Kevin C. (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2014-05
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Description
Grade inflation in modern universities across the United States has been documented since the 1960's and shows no signs of disappearing soon. Responses to this trend have ranged from mild worry to excessive panic. However, is the concern justified? How significant are the effects, if any, of grade inflation on

Grade inflation in modern universities across the United States has been documented since the 1960's and shows no signs of disappearing soon. Responses to this trend have ranged from mild worry to excessive panic. However, is the concern justified? How significant are the effects, if any, of grade inflation on students? Specifically, does grade inflation on the aggregate level have any effect on how much an individual will learn from their courses? This is precisely the question my project hoped to address. Grade inflation in U.S. colleges has played a central role in student-teacher relationships and the way university classrooms run. Through teacher interviews, student surveys, and a literature review, this paper investigates the nuanced effects grade inflation is having on student motivation and learning. The hypothesis is that the easier it is for a student to obtain their desired grade, the less they will end up engaging in and learning from a given course. Major findings of the literature include: grade inflation has robbed grades of their signaling power, grade inflation has helped create students are too grade-oriented, student evaluations of teaching have prompted higher grades, higher expectations for high grades induce greater study times, and open dialogue can help reverse grade inflation trends. The student surveys and faculty interviews agreed with much of the literature and found that professors believe grade inflation is real but do not believe its effects are significant, students admit to being primarily motivated by grades, and students find grades critically important to their future. The paper concludes that grade inflation is not as detrimental to student outcomes as ardent critics argue and offers practical ways to address it.
ContributorsGregory, Austin Scott (Author) / Ruediger, Stefan (Thesis director) / Goegan, Brian (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this

Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and coating materials for engineering or programmable cells for medical uses. Previous research using this model has focused on shape formation and other spatial configuration problems, including line formation, compression, and coating. In this work we study foundational computational tasks that exceed the capabilities of the individual constant memory particles described by the model. These tasks represent new ways to use these self-organizing systems, which, in conjunction with previous shape and configuration work, make the systems useful for a wider variety of tasks. We present an implementation of a counter using a line of particles, which makes it possible for the line of particles to count to and store values much larger than their individual capacities. We then present an algorithm that takes a matrix and a vector as input and then sets up and uses a rectangular block of particles to compute the matrix-vector multiplication. This setup also utilizes the counter implementation to store the resulting vector from the matrix-vector multiplication. Operations such as counting and matrix multiplication can leverage the distributed and dynamic nature of the self-organizing system to be more efficient and adaptable than on traditional linear computing hardware. Such computational tools also give the systems more power to make complex decisions when adapting to new situations or to analyze the data they collect, reducing reliance on a central controller for setup and output processing. Finally, we demonstrate an application of similar types of computations with self-organizing systems to image processing, with an implementation of an image edge detection algorithm.
ContributorsPorter, Alexandra Marie (Author) / Richa, Andrea (Thesis director) / Xue, Guoliang (Committee member) / School of Music (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
A working knowledge of mathematics is a vital requirement for introductory university physics courses. However, there is mounting evidence which shows that many incoming introductory physics students do not have the necessary mathematical ability to succeed in physics. The investigation reported in this thesis used preinstruction diagnostics and interviews to

A working knowledge of mathematics is a vital requirement for introductory university physics courses. However, there is mounting evidence which shows that many incoming introductory physics students do not have the necessary mathematical ability to succeed in physics. The investigation reported in this thesis used preinstruction diagnostics and interviews to examine this problem in depth. It was found that in some cases, over 75% of students could not solve the most basic mathematics problems. We asked questions involving right triangles, vector addition, vector direction, systems of equations, and arithmetic, to give a few examples. The correct response rates were typically between 25% and 75%, which is worrying, because these problems are far simpler than the typical problem encountered in an introductory quantitative physics course. This thesis uncovered a few common problem solving strategies that were not particularly effective. When solving trigonometry problems, 13% of students wrote down the mnemonic "SOH CAH TOA," but a chi-squared test revealed that this was not a statistically significant factor in getting the correct answer, and was actually detrimental in certain situations. Also, about 50% of students used a tip-to-tail method to add vectors. But there is evidence to suggest that this method is not as effective as using components. There are also a number of problem solving strategies that successful students use to solve mathematics problems. Using the components of a vector increases student success when adding vectors and examining their direction. Preliminary evidence also suggests that repetitive trigonometry practice may be the best way to improve student performance on trigonometry problems. In addition, teaching students to use a wide variety of algebraic techniques like the distributive property may help them from getting stuck when working through problems. Finally, evidence suggests that checking work could eliminate up to a third of student errors.
ContributorsJones, Matthew Isaiah (Author) / Meltzer, David (Thesis director) / Peng, Xihong (Committee member) / Department of Physics (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
Millennial involvement levels in the stock market are startlingly low. But what has caused this disconnect between America's younger generation and the financial sector? Stress from past financial crises, distrust of Wall Street, corporate greed, or a dislike of capitalism could surely all be viable culprits. Through our mutual experiences

Millennial involvement levels in the stock market are startlingly low. But what has caused this disconnect between America's younger generation and the financial sector? Stress from past financial crises, distrust of Wall Street, corporate greed, or a dislike of capitalism could surely all be viable culprits. Through our mutual experiences and research, however, we have found that most millennials aren't cynical anarchists avoiding the stock market in an attempt to fight against the system. Rather, they are individuals who have the desire to learn about investing but are clueless as to where/how to start. We both began investing in the stock market early in our college careers by opening online brokerage accounts and developing investment portfolios based on knowledge we learned within our Finance degrees and through independent research. Word of our involvement in the stock market began to spread in our social circles and people would consistently approach either of us and ask a variety of questions regarding investing. Questions such as: Can you sit down and help me open up an account and pick some stocks? What type of things do you invest in? How do I get started? How much money have you made? (always a favorite). Pre-med students, engineers, business, science, and technology majors alike all showed interest in the stock market. The more and more we talked to people, the more we realized that the problem was not a lack of desire or a lack of intellect. The problem was a lack of logically presented information, and barriers to entry that were far too high. We want to fix that. Investnet will be an online educational platform that will teach anyone the basics of investing, in plain, easy to understand terms. Whether the individual has absolutely zero knowledge of finances, or has some familiarity with investing, Investnet will provide them with the knowledge and confidence necessary to start investing in the stock market (or choose not to, but at least they'll know how).
ContributorsMcKenzie, Connor (Co-author) / Shatila, Jordan (Co-author) / Budolfson, Arthur (Thesis director) / Hoffman, David (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05