Service Learning is a semester-long course in which students will work with a team on a project that provides service for a nonprofit organization.
In addition to applying what they have learned in their coursework to complete the project, the student teams will meet regularly with their client to understand the project parameters, present their progress, and make directional revisions as necessary. This client-team communication and planning helps build the soft skills employers are looking for in future employees.
2020-21 Service Learning Projects
Techniques to Improve Lab Exercises in Object Elementary & Data Structures
The task of creating an effective lab exercise for computer science students can be considered a continuous learning process & very time-consuming. There are computer science students who struggle to complete their labs without serious help from teacher assistants to explain major concepts they may have overlooked, specify ambiguous directions, & more. The problem being, some students are unable to complete their labs in the effective or timely manner expected of them. In order to solve these problems, Dr. Mood has assigned my team a variety of Objects Elementary & Data Structures lab assignments, in which we are to improve in ways we believe will effectively help the struggling students comprehend the material.Once our improvement to these labs are made & others with similar problems, students who have previously struggled will have a better understanding of the lab goal, program direction, & a higher self-confidence in themselves to complete these exercises with less help.
Data Structures Lab Assignment Improvement Project
The purpose of this project is to analyze four of Dr. Mood’s labs for the course CSC 1054 and then make changes to improve the overall efficiency of the assignments. By doing this, the labs are more student-friendly and have a higher knowledge retention rate. The main process used in this project is utilizing four old labs previously given in the class by rewriting them, implementing them, and then revising and reviewing the lab afterwards. This process includes more specific methods such as improving instruction clarity, adding new portions to the assignment, and ensuring each lab has a well-defined objective. These methods resulted in labs that are straightforward, beneficial for the students learning, and an accurate depiction of the students knowledge and ability. Considering these results, this approach to analyzing and improving a lab is certainly a beneficial process to follow. This strategy for formulating lab assignments ensures the students can improve their programming skills in a way that implements the intended course topics.
Improving Labs for Objects and Elementary Data Structures
Without exceptional programming labs, it may be difficult for students to understand a language and code in it. Sometimes, a lab can lack a purpose, good problems, quality explanations, or a combination of these. Missing these elements can lead to confusion or frustration, and the material students must learn will not be conveyed. Because of this issue, the labs will not help the students meet the class's assessment goals and expected learning outcomes. This issue has been asked regarding labs from Objects and Elementary Data Structures (CSC1054) at Point Loma Nazarene University (PLNU). To address this issue, previous labs from the class were looked over and edited where applicable. As a result, edits were made to reflect the topics students learn and explain their significance. These new labs will significantly help students meet the expected learning outcomes and eliminate any confusion or frustration.
Compass: Frigate Optimization
Secure multiparty computation (SMC) research has grown to rely on efficient compilers. Frigate is a SMC compiler that has increased efficiency and accuracy compared to its predecessors. As the input programs of Frigate increases, the number of boolean gates and functions increases, which causes the computation times to rise. This has caused excessive compile times when running the compiler on large inputs. Therefore, computational efficiency within the compiler has grown in importance. In this paper, we aimed to increase the efficiency of the outputted file from the Frigate circuit compiler. The optimizations and time saved is accomplished by removing extraneous boolean gates and copy functions in the outputted file. Our results show that by optimizing the file, we were able to reduce the amount of boolean gates used. Therefore, improving the practical use of the Frigate compiler.
Compass- a Boolean Circuit Optimizer
Security, whether encryption, passwords, or even a bank vault, always comes with a tradeoff for speed. This is true especially in the world of Secure Multiparty Computation. Frigate is a compiler that hopes to lessen that tradeoff of speed for security. It extends previous work in Secure Multiparty Computation and outpaces other comparable circuit compilers with speeds up to 447x faster. Although Frigate has made considerable process in the field in accomplishing its intended goal, the generated circuits are far from optimized. This is problematic if Frigate is to be employed in a more practical context. We present Compass: an integrated modification and extension of Frigate’s interpreter that optimizes generated circuits and converts them from Frigate’s unique output format back to a usable input format. To remove extraneous gates and restructure suboptimal circuit paths we read the generated circuit into a graph data structure and then, as we traverse the graph, we algorithmically subtract redundancies and bypass unnecessary nodes. By utilizing published logic circuit optimization algorithms, we reduced the number of inefficient gates by 35%. This program creates more efficient circuits that direct Frigate in the right direction for practical application.
3D Graphics Curriculum Using JavaFX
Graphics are becoming more prevalent in many programming languages. At PLNU, 2D Java graphics have been an important part of lower level Java classes. The challenge is how to incorporate a curriculum that can help professors teach 3D graphics through Java packages, specifically JavaFX. This will be accomplished through 2 labs assignments split into multiple parts. The first lab will be designed to be completed in a single week of class and will have students follow step-by-step instructions to learn the basics of JavaFX. The second lab will consist of multiple parts that will be designed to be completed over the course of multiple lab sessions. Each of the parts will build off each other and gradually increase in difficulty of the core concepts. After these labs are completed, students will have a strong understanding of how to create 3D objects on a 3D plane (X, Y, Z axis), other various JavaFX objects such as camera and light objects, layouts, control components, scene graphs, scenes, and stages. Additionally, students will be able to apply this knowledge to future programs and be better equipped for future projects in and out of college that might require 3D graphics.
Teaching 3D Graphics
Although PLNU’s MCIS department offers a multitude of different software development curriculum, there is a clear lack of courses teaching 3D graphics or software development involving graphics in general. Currently, PLNU offers courses such as Software Engineering and Intro to Java which give students the opportunity to practice 2D graphics techniques, however there are no courses or specific labs that give students the opportunity to create anything in 3D. Our goal was to create introductory and multi-part lab that covered the basics of 3D graphics using the JavaFX library through which students were able to gain a foundation of 3D graphics, and basic animation. We found the best way to do this was through creating two labs. The first would teach students the basics of 3D graphics such as creating shapes in 3D space, adding a light source, and setting up JavaFX. The next, project-based lab would involve taking those concepts, and adding more difficult content such as animation, collision, and character movement. Now students will be able to gain the knowledge of 3D graphics when leaving PLNU and can apply the skills learned into whatever field they desire.
Compass – Frigate Optimizations
The Frigate Compiler was a great step towards optimizing secure multiparty computation to the best of its ability, simplifying the gates required and producing compile times up to 447x faster than the current alternative SMC compilers. By means of global optimization & the creation of a graphical interpretation of the logic gates outputted by Frigate, Compass will be able to decrypt whether or not specific gates can be removed that have not been by means of visual interpretation of the nodes making up the circuit. We plan to further increase compile times to give developers another option when it comes to utilizing SMC, with a goal of 1.5x that of Frigate, increasing on their already extremely optimized complier. Compass will further enhance the methods utilized within past compilers & Frigate as well in order to increase performance and efficiency when circuits are being validated.
Educational Ethics Within the Fields of Biology and Mathematics
The observation of all life on earth has always been delightful to most. Biology, being the study of living things, has progressed immensely, along with other fields, over the thousands of years humans have inhabited the earth. It along with mathematics are two of the many main sciences that are integral to study and learn from. With any department, whether it be a science or something such as business, there are many controversial methods used. Since the world is mainly driven by the success of individuals, and the cascades to benefit or hurt others, many people will try to shortcut success. Many would agree that the act of shortcutting is unethical, which it most certainly is, and that there should be more knowledge when it comes to properly. Biology and mathematics are very good places to study ethical and unethical approaches whether it be in data collection or basic procedures. Through the study of these ethical issues, humans can better understand why they are ethical, or unethical, and use them to educate future generations of biologists, psychologists, mathematicians, or any other individuals in different fields of study.
Ethics in Mathematics & Computational Science
The fields of mathematics and computational science have often been thought of by many as fields that are truly objective, fields removed from any sense of emotional bias, where ethical dilemmas do not exist. However, ethical dilemmas exist in every field where decisions are being made, and viewing the sciences as innately objective removes the responsibility of the scientist, data scientist, or mathematician to cognizantly make the most morally right decisions, resulting in disasterously unethical outcomes. In this project, by studying the ethical issues in the disciplines of mathematics and biology, as well as four helpful frameworks for ethical decision making, we created six modules to address various ethical issues in the classroom. In these modules, ethical issues in mathematics and computational science are formed into educational modules for various college-level courses within these fields, in order to educate the future professionals in these fields on how to introduce ethical action into their work. The modules are lesson plans for teachers, designed to help students think through each ethical dilemma using ethical frameworks discussed within the lesson in order to help students make the most objectively ethical decisions. Through these modules, professors can easily integrate ethics into their curriculum, ensuring that students graduate with the frameworks necessary to cultivate ethical action in their own respective occupations.
Tangible Computational Applications in Scientific Research
Computational techniques bring more opportunities to grasp the importance of many areas of research that words alone cannot provide. Typically associated in disciplines of mathematics and engineering, these methods are surprisingly versatile in their application, providing tremendous support in areas such as biology and chemistry. Although they are welcome in practically any area of research, these techniques are rarely exposed to researchers as they seem intimidating, even when they offer more timely solutions than those currently used. In this paper, we assessed the presence of computational techniques or the lack thereof in the current research of professors at Point Loma Nazarene University. Interviews with professors provided detailed information about difficulties within their unique research projects and helped guide the selection of a technique to assist in alleviating these problems. The computational technique, Labstep, was selected to address the common issues of data collection, management, and collaboration that were revealed in the interviews. The online platform brings together useful features in one location to provide an efficient and organized workspace for research. The easy-to-use application reveals that there are available computational techniques that can strengthen work efficiency and have yet to be fully exploited.
Computational Techniques for Scientific Research
Computational techniques are computer-based methods used to solve problems in areas such as mathematics, engineering, and science. We explored the computational background of researchers at Point Loma Nazarene University, and found that there is a wide range of research performed that could be made more efficient. Some computational methods currently applied in the fields they work at include the use of R, Python, VBA and JASP. We interviewed six professors via zoom, in order to learn more about their research and understand the difficulties they are dealing with in regards to data collections or analysis. Based on what we found we proposed the implementation of a flexible research environment that allows for collaboration, called Labstep. In conclusion, our project gave an insight into how computational techniques can be rather simple, and straightforward to use. Applying them can make a project more manageable, efficient and organized for any scientist regardless their background in computer science. Therefore their significance should not be neglected.
Identifying Computation Techniques that can Benefit Scientific Research
For thousands of years science has been evolving and developing to increase knowledge around the world. This growth has been expedited forward with the advancement of technology. Even though it may look like computational science and scientific research work together smoothly this is not truly the case. It has been identified that computational scientists have a limited knowledge on scientific research and the techniques and data that is gathered. The same is true for the opposite where biology and chemistry researchers have limited to now knowledge on computational techniques unless their research specifically calls for a technique to be used. Through our research we are trying to create a bridge between the two so that scientific researchers can be aware of certain basic but useful computational techniques that can benefit their research. For this project we started by interviewing different professors who were currently conducting research at the university. A total of six professors were interviewed, three were from the biology department and three were from the chemistry department. Having professors from different departments allows us to find possible solutions for many different parts of scientific research. After the interviews we proceeded with our project by collecting our information gathered in the interviews and used the information to collect possible computational techniques that could benefit the research being done. Once a few computational techniques were identified to be the most beneficial for certain research practices we then created modules or informational programs that will teach the professors how to use these computational techniques to benefit and streamline their research techniques.
Developing Ethical Modules in Mathematics
Morals determine the actions each person makes in their everyday lives. It is important, then, to understand ethics, or issues of morality, and how these ethical issues interact with vocation and stewardship. For this reason, since institutions of post-secondary education strive to prepare students for the jobs they may have in their lives, it is also important for those institutions to make their students aware that every job has ethical issues to confront by providing a curriculum that helps students's understanding and awareness of the ethical dilemmas present in their field of study. To that end, we created modules for the purpose of outlining ethical issues for students in the area of mathematics, which follow a simple and flexible design so that they can fit into the regular curriculum of classes. They confront students with ethical questions and provide them with activities to enhance their understanding of ethical dilemmas in their fields of study and potential work. These modules, along with previously existing modules, will help make the work force more conscientious in their jobs, and this, in turn, can help make the world a better place.
2019-20 Service Learning Projects
Mammalian Image Classification Using TensorFlow and a Convolutional Neural Network
Savannah R. Bolock and Amanda E. Timmons
The purpose of this project was to develop a machine learning program that can identify 15 specific mammals in Costa Rica from images taken in the field. Using Tensor-flow, an open source machine learning software library that runs on Python, a pretrained convolutional neural network model was developed to classify the images. The model was trained and tested on over 12,000 labeled mammal images. The resulting model overfitted to the training images and poorly classified the test images. Upon further investigation, the given set of image data was determined to not have been labeled correctly, significantly skewing the results of the model. Future goals of this project include relabeling the given set of image data, using the classifications of the images to move the image files into the correct species folder, further adjustment of the weights of the pretrained model, and developing a graphical user interface (GUI) for ease of use.
PLNU Faculty Contract Automation
Nicholas Dela Cruz, Steven Dols and Jackson Jones
At Point Loma Nazarene University, every faculty member receives their payment determined by their contract. The process for calculating each salary has been completed by hand by an individual. Moving forward, this project aims to replace the current process for faculty contract generation in a way that both increases the efficiency of the process, and the ease of use for the individual in charge of the process. Through the use of Microsoft Excel, our team will condense information from multiple spreadsheets into a single spreadsheet, and include formulas that will automatically calculate each faculty members salary. To make the process easier for the operator of the system, we will include an interface which allows for the addition or removal of faculty members, as well as persistent members whose employment status changes. This is all going to be done in an effort to reduce the amount of time and stress that have burdened the individual in charge of the current system, as well as implement a system that is less prone to errors.
EDF Energy Wind Data Cleaning Project
Alec Bothwell and Tai Eubank
Large-scale wind farms require reliable data to maintain efficiency and long-term improvement. The necessary process of identifying erroneous wind tower sensor data is currently done manually. In order to automate this process, we developed and implemented an Artificial Neural Network machine learning model. This model was designed to accommodate many different categorical and quantitative features. In addition to including the original data, we calculated dozens of new data features based on potentially useful patterns found in the data. The results indicate that “Icing”, a major type of error, was able to be predicted on test data with 96.59% Accuracy, a True Positive Rate of 44.78%, and 86.41% Precision. This demonstrates that it is possible for wind tower sensor errors to be automatically identified. However, more work is needed to improve accuracy, predict all types of errors, and generalize certain aspects of the machine learning model to accommodate any similar dataset.
First Church of the Nazarene Giving Trends
Clarissa Burrola and Madison Kurtz
We were given the task of analyzing donation data for the First Church of the Nazarene located on the Point Loma Nazarene University campus. We analyzed data that contains donation amounts along with the date they were given, the age of the person who gave and the zip code where that person lives. Specifically, we looked at the zip codes that continued to give the most each year, the changes in giving participation from year to year, and the months that saw the highest amounts of donations. We analyzed the data to find trends that connected to these characteristics of the church members. The ultimate goal of the project was to give Senior Pastor Dee Kelley advice on how to keep donations flowing into the church in the next couple of years, since donations are the only source of income they receive.
Using 915MHz LoRa Antenna System for Wi-fi Grid Network Creation in the Costa Rican Rainforest
Abigail Christensen and Isaac Hughes
This study, “Creating a wifi grid network for use in imaging Costa Rican native species”, focuses on the LoRa peer-to-peer communication method of creating a grid network for camera systems to use in remote areas of the Costa Rican forest. Through the LoRa peer-to-peer communication method researched in this study, it is found that a large network can be created by the cameras themselves to aid in the transfer of data, maximizing the amount of data storage space on each camera at any given time. In testing, a LoRa peer-to-peer communication network is easily modified and adapted with a “switch” code, allowing a single LoRa system to at 915MHz, receive and send data at the same time. This creates for a successful, yet at times unreliable, data transfer between modules placed in succession, tested at various distances, with various obstacles. With this immediate transfer of data, potentially vital information and images won’t have as large of an opportunity to become lost.
Ryan Library Data Analysis
Robyn Conner and Jared Lechien
Ryan Library aims to ensure that all students are receiving a service that exceeds students’ expectations and instills confidence in users that use its various services. In Spring 2019, Ryan Library conducted a survey in which 1722 undergrad students, grad students, professors, and faculty participated in. Using LibQUAL+ as a service to conduct the survey and analyze the results, Ryan Library received some insight on how they can improve the library’s services. However, LibQUAL+ doesn’t concisely tell Ryan Library what survey items they should focus on improving. We addressed this issue by giving Ryan Library tools that simplify the process of screening, interpreting, and visualizing LibQUAL+ data.
2018-19 Service Learning Projects
Trained Peer Evaluator Scheduling
Cameron Gilbert, Jared Lechien, and Andrew Ross
Science Programming Labs
Whitney Featherston, Braden Hulse, and Robyn Conner
ITS Cell Service Project
Christopher Kleint, Marisa Ruch, and Darren Sagucio
Mail Services Efficiency
2017-18 Service Learning Projects
ITS Cell Service Project
Griffin Aseltine, Kai Gustafson, and Kelvin Dean
Point Loma Nazarene University has inconsistent cell service across its campus. Information Technology Services has not had the resources necessary to complete testing to determine where the dead spots were for the various service providers. This service learning project provided students to take cell service strength readings in dormitories, key buildings, and other locations on campus and then provide analysis as to which providers performed best (and worst) in the various locations. ITS will use this information to improve service across PLNU.
Tumor Image Processing with R
Haylie Everett, Kaitlyn Purington, Michael Wheelock, and Erik Siles
PLNU professor, Dr. Mike Dorrell, conducts research on treatments to combat malignant tumors. The effectiveness of the treatments can be determined, in part, by analyzing before treatment and after treatment images of the vascularization of the tumors. This is a tedious and imprecise process to complete by hand. This service learning project created a GUI-based
application, written in R, that can process batches of these images and capture the percent of vascularization. It can then produce reports to guide the researchers' future efforts.
Trained Peer Evaluator Scheduling
Logan Douglass, Keith Rodriguez, and Jorge Garcia Salazar
Periodically, Point Loma Nazarene University uses Trained Peer Evaluators (TPEs) to evaluate the performance of its professors. There are a number of rules associated with who can perform the evaluation for a particular professor. Rules include: TPEs should perform no more than 2 evaluations per semester, TPEs are preferably not in the same department as the person to be evaluated, the TPE chosen should not have a teaching conflict with the class time during which the evaluation is to be performed. Trying to match TPEs with those to be evaluated had become a cumbersome process. This service learning project created a GUI-based application to help the deans center identify the TPEs that would best fit the person to be evaluated.
2016-17 Service Learning Projects
Student Survey Data Analysis
Albert Serna, Abdel Farha, and Joel Bradley
Students from PLNU take several surveys over the course of their time here and even after they graduate. Last summer 2 students aggregated the data from those files into one flat file. Several columns of that file had yet to be analyzed. This group cleaned the data and used statistical analysis to find correlations student behaviors and student success.
Art and Computing Project
Erik Gaustad, Andrew Taylor, Brady Kilpatrick, and Ben Khoshaba
Laudato Si: On Care for Our Common Home is an Encyclical Letter of Pope Francis. It is an important work on sustainability, but not widely read by young people. The goal of this project was to transform the content of the book into a more engaging form for this audience using technology. The team approached it by creating word clouds from each chapter of the text, and then incorporating them into a geocaching adventure.
Jack Higgins, Hudson Bundschuh, and Maryn Wunderly
In the process of genetic research, the scientist would like to find DNA sequences that potentially contain genes. These sequences are called Open Reading Frames (ORFs). Once the ORFs are determined, they are sent to alignment programs which determine if these sequences closely match other sequences whose functions have already been discovered and documented. Generally, the alignment programs are accessed over the internet and the procedure is slow. The goal of this project was to streamline this practice by making remote processes run locally and to find other optimizations that increase speed without compromising correct results.
2015–16 Service Learning Projects
Sensory Signal Recovery Project
Ryan Bieber, Liam Oliver-Mallory, and Lindsay Watson
The signal recovery problem is one in which a number of measurements at various times can be used to calculate a transformation that can be used to predict future changes given other conditions. This paper details the techniques used to create such a transformation, ways to calculate with limited data, and how to improve performance of the algorithm.
Center for Pastoral Leadership Database
Brandon Colchin and Randy Hiroshige
The purpose of this Service Learning project is to provide an online database that contains the pastoral contact list for the Center for Pastoral Leadership (CPL). This database was requested by the CPL in the hopes of creating a central database available for use by all CPL staff. This tool will help the CPL as it organizes communication and maintains relationships with pastoral contacts on both a local and broader scale. The database of contacts is hosted as a MySQL instance through Amazon Web Services. Database access occurs through a website hosted as an EC2 application instance through Amazon Web Services. The website uses the Drupal platform, and the database access functionality was coded in PHP as a Drupal module.
Pre-Health Student Database and Data Importing
Sarah Elwin, Austin Krieghoff, and Ethan Soch
This paper reports on the processes relating to the implementation of a pre-health student database for the head of the chemistry department, Dr. Sara Choung. Topics include the design consideration for the database, the development of a user-interface to facilitate faculty interactions with the database, and the design and implementation of a computer program to aid the importation of preexisting data.
The Genome Comparison Project
Tim Little, Tristan Oliver-Mallory, Katelyn Ortiz, and Hannah Quinn
This project compared bacteria genomes and created visual representations of these comparisons. The bacteria genomes were first separated into each individual gene and these genes were compared against one another using an online comparison database called the Basic Local Alignment Search Tool. Bacteria genomes that were being compared were represented using tracks, with individual arrows used to represent each individual gene. These bacteria genome representations were drawn parallel to each other. The results from comparing the gene in the two genomes were represented by drawing red cross-links connecting similar genes represented by their arrow on each track.
Will DeCino, James Morar, and Will Schumacher
The three students worked in collaboration with Dr. Maloney, Dr. Botts, and Dr. Jimenez, to assist Dr. Maloney with her research of Sarcophyton Glaucum. The first sections of the paper describe Dr. Maloney's work with the soft corals. This includes the importance of researching the corals and the current process used in the collection and classification of them. The middle sections of the paper mention the mathematical methods used to analyze the data collected from Sarcophyton Glaucum. This includes principal component analysis, hierarchical clustering, and linear discriminant analysis. The last sections of the paper present the output of the mathematical analyses. This includes a description of what the data is saying and a conclusion of the final results.
2014–15 Service Learning Projects
Locating Antibiotic Resistant Gene in Bacterial DNA
Lillian Duffey, Tyler Maskiewicz, Claire Mathews, and Clara Welcome
A client of Dr. Botts is a company wishing to create a more efficient waste treatment process by making use of the naturally developing biofilm to break down the waste, thus saving water in the process. Before this biofilm process becomes the next sewage technique, more information on the bacterial DNA is needed. This project was to begin the process in determining the location (plasmid or chromosome) of antibiotic-resistant genes in a sample of biofilm bacteria. The direct purpose was to begin the process of creating a database of DNA sequences that seem to be found only in plasmids as well as beginning to streamline that reassembly process.
Building a Student Survey Database Using Microsoft Access
Michael Bench, Craig Hollensbe, and Henry Teegarden
Over the last decade, PLNU has followed cohorts of students through their undergraduate studies by administering to them a series of standardized surveys. The results of these surveys were compiled into several large Excel files. This Service Learning group was responsible for creating a database that effectively organized this information so it could be used for data mining purposes by PLNU staff. By effectively organizing survey data, the database makes it significantly easier to answer important questions regarding student behavior. This makes it an incredibly powerful statistical tool. For example, by pulling data regarding grades and chapel attendance, one can begin to determine whether or not academic success and spirituality are correlated. For this project, the focus was on creating a database that organized data from two of the surveys taken in the last 10 years: NSSI 2005 and NSSE 2010.
2013–14 Service Learning Projects
Electrostatics Android Application
Brian Bufford, Troy Carmichael, Brendan Heldman, and Blake Herrington
This interdisciplinary team created an Android app that calculated and illustrated electrostatic point charges. The user is presented with an empty axis in which charges and sensors can be plotted with their corresponding parameters. A user can access a menu to add a sensor or charge, remove a sensor or charge, or view the list of all points and their corresponding calculation values currently present in the environment. After any update, all points are automatically plotted on the axis and the electrostatic fields created by these points are demonstrated. This tool is anticipated to be used in an education setting by students and professors.
Brooke Apffel, Joanna Borgona, Tim Dixon, Aaron McKinstry, and Ally Takeda
Antibiotic resistance is spreading rapidly and is a global health concern. It is necessary to understand the genes encoding these resistances to have hope for the future of effective antibiotics. To properly annotate and analyze the genes behind antibiotic resistance, advanced and efficient programs are necessary. The aim of this project was to enhance the open-source, free software SeqTrace to be better equipped to handle genomic data. Two things were accomplished: 1) creating an automated function that trims primers from given sequences, allowing users to input the specific primers they want to trim, allowing for slight variation on the primer sequences, and 2) creating a function that automates the process of data cleaning. Adding these functions to SeqTrace allows users to work with and manipulate DNA sequences within a free software.
Vicente Chiquete, Jacob Rivera, Ericka Rule, and Keith Thompson
When relocating, new residents must find a variety of services. For many, a church where the family will feel comfortable is one of the most challenging things to find. This project aimed to create an online service, based on the R language, that would allow users to select the desired criteria for a church and see the offerings in the neighborhood presented both in text and on a map. Prior to creating the application and associated database, a survey was constructed and administered to gain the information with which to populate the database.
2012–13 Service Learning Projects
Dustin Ansley, Wileen Chiu, Joshua Lam, and Amanda Olson
Computer science is a potential college major few high school students are aware of. Yet, it is a major that leads to lucrative and satisfying jobs. The students involved in this Service Learning project contacted counselors, principals, and mathematics and science teachers at 26 local high schools, asking which of six different resources would be most helpful for introducing high school staff and students to the field of computer science. The top requests were for posters, brochures, and a short video. After studying papers on research regarding what influences the choice of a major, what characteristics make a good computer scientist, and the job prospects for computer science majors, the students produced and disseminated the posters, brochures, and video.
2011–12 Service Learning Projects
Videos to Support Learning in Elementary Statistics
Aimee Bird, Katherine Graham, Adam Kenyon, Colin Lowry, and Kevin Schick
For the MICS tutorial video project, students endeavored to create tutorial videos for a statistics class. The ultimate goal of the videos is to convey statistical concepts in a clear and concise manner. To complement this basic understanding of a particular statistical concept, the videos are also intended to provide students with a degree of intuition regarding each topic. Thus, students will understand why it would be important to use the statistical concept given a particular situation. Along with these videos, a functional, user-friendly website was also constructed during the course of this project. The website provides various sample questions and answers with each statistical concept. Having these resources available will permit students to practice and develop their ability to solve problems, and it's hoped this project will provide the foundation for constructing statistical competency.
Nursing Project 2011-2012: Determining the Value of TEAS
Alex Buttweiler, Evan Grove, and Walter Wagner
The nursing project is attempting to solve fundamental problems related to the low math and reading scores for nursing students observed over the past few years. The goal of this project is to predict retention and pass/fail for the NCLEX, which is the national exam to become a registered nurse, by analyzing grades from biology, chemistry, major nursing courses, TEAS reading/math scores, and their overall GPA. Binary logistic regression is the primary statistical method used to give predictions for the data. The outcome was that the TEAS exam had very little effect on predicting which students will pass or fail the NCLEX. The only significant factor in determining which students will be successful was GPA.
Political Science Assessment Analysis Project 2012
Alex Buttweiler, Evan Grove, and Walter Wagner
The main objective of this paper is to present the trends the Service Learning team discovered when analyzing the collection of entrance and exit surveys taken by students who are political science and international relations majors. Frequency counts were used to analyze the data; the survey answers were categorized and then analyzed based on the percentages of students responses. This paper will provide the Department of History & Political Science at PLNU with the conclusions drawn from the data given in this survey format. The outcome was that overall, students felt they were considerably better off than they were when they entered the major. The only negative outcome was that students did not feel like they were as well prepared as students from other schools overall.
Analysis of Factors Relating to Retention within PLNU’s Biology Department
Cosette Tiguila and Ethan Wade
In an average year, the biology department at PLNU adds 50 to 60 new students who can be sustained by the department’s current resources. Entering the 2011 – 2012 academic school year, there were nearly 100 new students, which exceeds the long-term sustainability of the department’s resources; therefore, an analysis of factors that contribute to student retention was performed to determine what traits, if any, predict a student’s success in the biology department. The results of this study will assist in determining how best to address the rise in the number of students. The data used for the study was from students enrolled in the following majors from 2005 – 2011: Biology – B.A., Biology – Chemistry, Biology – B.S., Environmental Science, Biology – Cell & Molecular B.A., Biology – Organismal B.A., Biology – Cell & Molecular B.S., and Biology – Organismal B.S. Due to a lack of time, no definitive analysis was accomplished, but there appears to be a correlation between a student’s weighted high school GPA; English and math ACT percentile; and raw math, writing, and verbal SAT scores and whether the student switched or graduated from the biology department. Future studies are needed to determine the accuracy of this finding and also address other possible predictive factors such as college GPA, advanced placement tests taken prior to being admitted, student career goals, and extracurricular involvement.