17 research outputs found
Cultivating Mathematical Affections through Engagement in Service-Learning
Why should students value mathematics? While extensive research exists on developing the cognitive ability of students, very little research has examined how to cultivate the affections of students for mathematics. The phrase mathematical affections is a play on the affective domain of learning as well as on the general notion of care towards something. Mathematical affections are more than a respect for the utility of the subject; the term is much broader and includes aesthetic features as well as habits of mind and attitude. This paper will analyze the findings from a research project exploring the impact of servic
What we can Learn from Process Theology: Integrating Faith and Mathematics
In the inaugural issue of The Journal of the Association of Christians in the Mathematical Sciences, James Bradley, the founding editor, suggests fourteen areas that need to be addressed by Christian mathematicians who are series about integrating their faith and their work. One of those areas is the topic of this paper. Bradly frames the question: “Some thinkers (perhaps influenced by process theology) have asserted the idea that God’s creation is not a finished work but that he creates new mathematical objects through mathematicians. Is this idea theologically sound? Is it helpful for our understanding of mathematics?” I copy Bradley’s exact phrasing because I believe he poses the questions in the appropriate order: first determining the theological validity of the process movement and then secondarily examining its influence on an understanding of mathematics.
There are two specific ways in which the process attempt fails. Its first fault lies in the presuppositions that are brought to the task of integrating mathematics with Christian faith. And second, even if the process assumptions are granted, flaws remain in the implementation of those beliefs in both theological reflection and mathematical practice. The paper will close with several suggestions of how Christian mathematicians might refine the integration their faith and their discipline in these areas where the process offering fails
Factors that Motivate Students to Learn Mathematics
What motivates some students to want to learn mathematics while others do not share similar motivation? Are these factors intrinsic, extrinsic, or a combination of both? To answer these questions, we adapted a survey originally developed by Tapia (1996) and later shortened by Lim and Chapman (2015). We administered the survey in multiple middle schools, a high school, and multiple colleges and universities. We obtained over 100 completed surveys for each of these educational levels. This presentation offers an analysis of these data, including descriptive statistics and confidence intervals for each educational level. For the college and university sample, we also provide comparisons among students majoring in mathematics or mathematics education, those majoring in elementary education, and those with a variety of other majors. In addition to the Likert scale items from the original survey, we explore qualitative data from a free response item. Join us to learn more about why students enjoy learning mathematics and later choose undergraduate majors in the discipline
Service-Learning Panel
Many of us have wanted to incorporate service experiences in courses, or are being asked by our institutions to do so. Service-learning is a way of looking at service as being a partner with and leading to learning for our students. But in math, there are not a lot of resources to use! Our panelists will present classroom-tested ideas from several different levels of course, and we will end with a short time for more brainstorming among all participants
Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma
SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine
The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma
We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) based on multidimensional and comprehensive characterization, including mitochondrial DNA (mtDNA) and whole genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared to other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT up-regulation in cancer distinct from previously-observed amplifications and point mutations
A Guide for Fitness Function Design
Fitness function design is often both a design and performance bottleneck for evolutionary algorithms. The fitness function for a given problem is directly related to the specifications for that problem. This paper outlines a guide for transforming problem specifications into a fitness function. The target audience for this guide are both non-expert practitioners and those interested in formalizing fitness function design. The goal is to investigate and formalize the fitness function generation process that expert developers go through and in doing so make fitness function design less of a bottleneck. Solution requirements in the problem specifications are identified and classified, then an appropriate fitness function component is generated based on its classifications, and finally the fitness function components combined to yield a fitness function for the problem in question. The competitive performance of a guide generated fitness function is demonstrated by comparing it to that of an expert designed fitness function
Coevolutionary Automated Software Correction
This paper presents the Coevolutionary Automated Software Correction system, which addresses in an integral and fully automated manner the complete cycle of software artifact testing, error location, and correction phases. It employs a coevolutionary approach where software artifacts and test cases are evolved in tandem. The test cases evolve to better find flaws in the software artifacts and the software artifacts evolve to better behave to specification when exposed to the test cases, thus causing an evolutionary arms race. Experimental results are presented on the same test problem employed in the published results on the previous state-of-the-art automated software correction system
Scalability of the Coevolutionary Automated Software Correction System
The Coevolutionary Automated Software Correction system addresses in an integral and fully automated manner the complete cycle of software artifact testing, error location, and correction phases. It employs a coevolutionary approach where software artifacts and test cases are evolved in tandem. The test cases evolve to better find flaws in the software artifacts and the software artifacts evolve to better behave to specification when exposed to the test cases, thus causing an evolutionary arms race. Experimental results are presented which demonstrate the scalability of the Coevolutionary Automated Software Correction system by establishing correlations between program size and both success rate and estimated convergence rate that are at most linear
Multi-objective Coevolutionary Automated Software Correction
For a given program, testing, locating the errors identified, and correcting those errors is a critical, yet expensive process. The field of Search Based Software Engineering (SBSE) addresses these phases by formulating them as search problems. The Coevolutionary Automated Software Correction (CASC) system targets the correction phase by coevolving test cases and programs at the source code level. This paper presents the latest version of the CASC system featuring multi-objective optimization and an enhanced representation language. Results are presented demonstrating CASC\u27s ability to successfully correct five seeded bugs in two non-trivial programs from the Siemens test suite. Additionally, evidence is provided substantiating the hypothesis that multi-objective optimization is beneficial to SBSE