Using Python and Tableau to Build an Interactive Student Success Model

Thursday, May 22, 2025

10:45 AM – 11:30 AM East Coast USA Time

Location: Panzacola F2

Institution Type: 4-year institutions

Target Audience: Expert/Advanced

Presenter(s)

SM

Salma Mirza, PhD, MBA

Associate Director and Senior Data Visualization Specialist
Southern Methodist University (SMU)
ALLEN, Texas, United States
CM

Cayden McDonald, PhD

Statistician and Data Scientist
Southern Methodist University (SMU), United States
AP

Aishwary Pawar, PhD

Statistician
University Decision Support Office, Southern Methodist University

Session Abstract: Student success is a multidimensional concept that can be influenced by a wide range of factors including academic performance, socioeconomic background, and extracurricular engagement. In this session, we will walk through the process of building an interactive student-success model using Python for predictive analytics and Tableau for dynamic visualization and exploration. By combining the power of Python for model building and Tableau for interactive visualization, this session will guide participants through the process of creating a tool that dynamically responds to model inputs and presents predictions for selected subgroups.

Keywords: Tableau, integrating Python with Tableau, student success, predictive models, statistics in Tableau