Integrating Theory and Practice: Developing an Assessment Framework For Experiential Learning Programs at The College of Wooster
Student Researchers: Ashley Dawes, Ana Godonoga, Promise Kamanga
Faculty Advisor: Theresa Ford (Educational Assessment) and Dr. Amy Jo Stavnezer (Psychology)
This project involves the development of an assessment framework for theory-to-practice (also known as experiential learning (EL) experiences at The College of Wooster. One of the current strategic priorities at the College is “Integrating Theory and Practice” with the goal of increasing “opportunities for students to connect theory and practice through campus life and ‘real world’ projects and experiences that strengthen the quality of student learning”. Our study therefore provides an opportunity to identify where and how much “Integrating Theory and Practice” occurs on campus; to examine program similarities and differences in practices, goals, and outcomes; and to develop a broad assessment framework and an agile assessment plan of “Integrating Theory and Practice: Experiential Learning” (EL) experiences at the College.
Efficiency Analysis in MHD Workstations
Student Researchers: Andrew Licking, Huachen Li, Kemar Reid
Faculty Advisor: John David and R. Drew Pasteur (Mathematics)
The purpose of this AMRE project was to analyze, collect data for, and improve the workload model established by Bekaert’s corporate office. A further goal of our project was to observe operations and to determine what, if any, inefficiencies existed and to find a way to avoid these inefficiencies in the future. The AMRE team was contracted to study one area of the plant specifically – the Multi-Hole Drawers (MHD) section.
Pansophy Software Updates
Student Researchers: Trisha Fultz, Spencer Hall, Qisheng Li
Faculty Advisors: Denise Byrnes (Computer Science)
The Pansophy student contact management software was created by a previous AMRE team for the Dean of Students Office. Pansophy is used to keep a record of potential problems and important information concerning students at the College of Wooster. Some examples include a death in the family, low grades in a particular class, or a parent’s concerns about financial aid. Documenting these prospective issues helps prevent students from falling through the cracks. This summer, we were tasked with upgrading the software to fix bugs and add new features, such as a way to archive graduated students. Along with the new features, we updated the user help documentation to aid users in recognizing and understanding the new features.
College of Wooster Energy Usage Tracking
Student Researchers: Micah Caunter and Michael Janning
Faculty Advisor: Dr. Denise Byrnes (Computer Science) and Dr. Matt Mariola (Environmental Studies)
This project creates a website that provides access to information about the College’s various forms of energy consumption: electricity, water, and gas. The website allows an administrative user to analyze the college’s energy efficiency in these three areas on a building-by-building basis. The analysis can be used to improve the energy distribution on campus, conserve resources and save money. There are two components to the website: a public and a private section. The public area provides an interactive map of campus that can be used to pull recent energy usage history for campus buildings. There is also functionality to compare two buildings at the same time. The private section allows for administrative users to pull data from the website database in either report form or tabular form. The website is also maintained through the private section by uploading the most recent usage data from energy providers.
Surface Absorption of Selected Rubber Chemicals onto Model Surfaces
Student Researchers: Andrew Young and Norman Chamusah
Faculty Advisor: Sarah Schmidtke (Chemistry)
This project was developed as a computational chemistry project to compute the relative sorption energies and model the structures of selected rubber chemicals on filler surfaces. The compounds are used in the vulcanization process for producing tires. The chemicals have an effect on the rubber crosslink density, filler surface and aging characteristics of the rubbers. The main goal was to use the sorption energies to make predictions of the relative strengths and favorability of the interactions between the given chemicals and fillers. A series of milestones were accomplished in this study: chemicals were optimized on new filler surfaces and protocols were developed to minimize computational cost for this step, energies were evaluated at different levels of theory to capture primary components of the interactions energies for the two different types of fillers, and results were analyzed to gain a deeper molecular level understanding of the impact of chemical structure on sorption properties.
Absolute Characterization of Crosslink Density
Student Researchers: Alexandra Kuzmishin and Adam Trontz
Faculty Advisors: Sarah Schmidtke (Chemistry)
The experimental chemistry team worked this summer to develop a method to directly measure the crosslink density of rubber samples. The strategy was to adapt a common biochemical technique to measure disulfide bonds, the chemical bonds that link polymer units in the rubber, through a reaction with Ellman’s reagent. This reagent produces a chromophore upon reaction with disulfide bonds, which can be visualized using UV-VIS spectroscopy to quantify the number of disulfide bonds that reacted. A key difficulty in this adaptation is the organic nature of rubber, relative to the aqueous matrix necessary for the Ellman’s reaction. Some of the milestones accomplished in this project were: determination of co-solvent buffer system allowing for the Ellman’s reagent reaction and solubilizing the rubber, obtaining a linear calibration curve for the cysteine standard in the co-solvent system, development of a purification and reduction method for the rubber sample, qualitative proof of principle that the technique works for solid rubber samples, and preliminary quantitative data yielding concentration of disulfides within the anticipated order of magnitude for tire rubber.
Translation of two-dimensional information from microscopy images to realistic three-dimensional representations
Student Researchers: Bennjamin Snyder, Joshua Thomas, Ruth Steinhour
Faculty Advisors: John David (Mathematics) and Denise Byrnes (Computer Science)
This AMRE team developed a new image analysis tool for Goodyear Tire and Rubber Company. This project had two main goals. The first was to develop a three-dimensional rendering of particles from a two-dimensional sample image. The second goal was to produce a three-dimensional rendering of cylinders from a two-dimensional image featuring ellipses and non-spherical particles. Several properties of a given rubber sample, such as the rubber’s toughening efficiency and impact resistance, are related to particle size, shape, and location. This tool enables Goodyear to analyze two-dimensional images of rubber samples more effectively by providing new insight into the samples’ three-dimensional characteristics.
Wooster Mathematics Knot Theory Research
Sarah Smith-Polderman and David Freund
Faculty Advisors: Jennifer Bowen and John Ramsay (Mathematics)
We continued previous research in the study of Klein links. We drew and untangled 48 distinct Klein links to provide a catalogue from which to observe patterns in their construction and the resulting links. We also created digital versions of a small subset of these links and wrote a paper that will be used to introduce the Klein links to future researchers. Lastly, we proved a number of theorems, including a result that allows us to count the number of components in an arbitrary Klein link, and have prepared our results for publication.
Analysis of Actuarial Data Supporting Rate Changes
Student Researchers: Ashley Stopka, Ian Sharp, Hannah Roberts
Faculty Advisors: Jennifer Bowen and John Ramsay (Mathematics)
The project consisted of analyzing filings that an insurance company is required to submit to each state’s Department of Insurance (DOI) whenever the company changes its rates or rules. The first part of the project involved reading through filings and making observations based on what is included, what is changed, methodology and objections from the DOI. The second part involved focusing on the average number of claims and the size of the payouts for these claims in Pennsylvania. We collected data from the files to determine how Progressive ranks among their competitors in terms of the frequency and severity of claims within different coverage types. The largest focus in the second part of the project was to look at data about Personal Injury Protection (PIP) claims in Kentucky to determine. Progressive has seen evidence of increasing fraudulent PIP claims in Kentucky. We looked to determine whether or not other companies are seeing similar trends in PIP fraud.
Sports Prediction Using Neural Networks
Student Researchers: Andrew Blaikie and Gabriel Abud
Faculty Advisors: John David and Drew Pasteur (Mathematics)
This project was a continuation of a 2010 AMRE/HHMI project dealing with artificial neural networks (ANNs) as a tool for predicting NFL football games. We built multiple ANN models to predict both college and professional football games. ANNs have many uses in today’s scientific fields and are an efficient way to model complicated systems. We devised our most efficient model by analyzing several years of game statistics, using methods including correlation, principal component, derivative-based, and linear regression analysis. Predicting college football was a more difficult problem due to the wide variety of team abilities and schedule strengths, so the results were not as accurate as they were for the NFL model. Additionally, we collected large amounts of data on other sports for future research.