Projects

College Enrollment Prediction

DataSAIL participants: Dr. Piotr Szczurek (faculty), Dr. Ray Klump (faculty), Daniel Ayala (faculty), Curt Lebensorger (student), and Lisa Nicoll (student)

The goal of this project is to study college enrollment data and make a predictive model which can be used to find effective recruitment strategies at Lewis University. We attempt to determine which types of students are most likely to respond to a marketing campaign and which of those will end up enrolling. This information can then be used to target particular kinds of students, which can result in increased enrollment.

Analysis of Microarray Data from Cancers with Mutations in D-Type Cyclins

DataSAIL participants: Dr. Sarah Powers (faculty)

Visualization of Intrusion Detection Data

DataSAIL participants: Dr. Ray Klump (faculty)

Analsys of Pedestrian Traffic Flows

DataSAIL participants: Dr. Ray Klump (faculty)

Determining Student Success

DataSAIL participants: Dr. Amanda Harsy (faculty), Jason Carlock (student)

Other participants: Betsy Langland (student), and Dylan Grostkreutz (student)

This research project will use data analysis, data mining, and ranking methods to determine what contributes to a student’s success in his/her major. We will explore questions like, “What contributes to a student’s perseverance in their degree?, Can we predict what types of students will succeed in a particular major?, What contributes to gainful employment after graduation?”, “What type of student is likely to attend and finish their degree at Lewis?”, and “How much impact does a major change in curriculum have for student success and recruitment?”. Answering these questions can help faculty members advise students and also suggest majors for undecided students. We may also be able to determine methods to help the university award scholarships and decide students we should pursue for our majors. Currently, we are collecting and using data from current and past Lewis Math majors. Questions that we hope to answer include but are not limited to, “Are there specific courses which can predict a student’s success in the math major?”, “Does commuting distance contribute to success in the math major?”, “Is there an optimal number of math classes one should take per semester?”, “How much of an impact do study habits have for a math major?”, “Does one’s progression through the major influence a student’s gpa?”, and “Does working while taking classes influence your success/perseverance in the major?”. We will also explore different demographics in the math major –male/female, commuter/resident, transfer/non-transfer, etc.