My research interests lie at the intersection of data science, machine learning, and education. Specifically, I focus on:
- Applications of Data Science and Machine Learning in Educational Contexts
- Quantitative Survey Methodologies for Educational Assessment
- Large Language Models as a Tool for Educational Research
- STEM Education Research
University of Michigan
Grasping Rationality and Instructional Practices (GRIP) Lab
As the lead graduate student researcher in the GRIP Lab, I contributed to the Geometry for Teachers (GeT) Support Project, focusing on:
- Item-response theory analysis of MKT assessments.
- Coding qualitative data and using machine learning models.
- Developing and analyzing psychometric survey instruments.
College and Beyond II Project
In this project, I conducted statistical analyses to study the effects of liberal arts education on life outcomes, including:
- Analyzing results from pilot surveys.
- Providing readability statistics for essay responses.
- Employing structural equation modeling.
Wolverine Pathways Curriculum Development Project
My role involved developing mathematics curriculum materials with a social justice orientation for a summer bridge program.