RUME 25
2023
Omaha, Nebraska
Developing Network Modeling and Analysis Methods for First-Year Mathematics and STEM Student Course-Taking Sequences
Page: 1018
Student success is typically measured by grades in coursework and 6-year graduation rates (York, Gibson, & Rankin, 2015). The purpose of this exploratory data analysis is to develop statistical methods that will provide a deeper understanding of student success, specifically success in first-year mathematics (FYM) prerequisite courses as well as the STEM courses they serve. We consider the many possible student course-taking sequences (paths) as a complex network system. We model the paths that students take with a network of vertices (courses) and edges (links between courses) by using 10 years of registrar data to generate vertex and adjacency matrices, and associated graphical representations (e.g., heat maps and network graphs). We also will conduct relevant exploratory data analysis to determine the importance of certain mathematics courses and transitions to overall student success.