Research

I am a quantitative physics education researcher specializing in machine learning and big data analysis. My research interests include student learning and outcomes in introductory courses and graduate students in physics.

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Using big data to understand educational outcomes

With nearly everything aspect of a student's time at a university documented in a database, there is an excited opportunity to study educational outcomes for college students. Yet, how to work with such data and obtain useful insights from it is an ongoing area of inquiry. As a postdoc at the University of Michigan, my research focused developing tools for researchers and instructors to understand the data generated by their students and how to apply the results.

I'm also conducting work on complex-multiple choice questions to see if those might unfairly penalize students. These questions are claimed to be harder, but harder for who? I'm trying to figure that out in the context of introductory physics using data from Problem Roulette.

Understanding the graduate admissions process in physics

As physics has remained one of the least diverse STEM fields, increasing attention is directed toward the admission practices of graduate programs. There are many components to a quality graduate application and I am interested in how those components of the application influence whether the admission committee will accept or reject the student.

As part of this research, I've investigated how rubric-based holistic admissions might provide a route to make admissions more equitable. Using machine learning methods to compare how our program admitted applicants before and after the implementation of the rubric, I found that rubrics-based admissions does appear to be a promising path forward.

As part of this work, I've also investigated whether the physics GRE helps applicants who might be missed in the admissions process stand out as it is often claimed to do. The results suggest the opposite! For many of the applicants who might be able to benefit from a high score, they didn't actually benefit. Further, some otherwise competitive applicants had lower chances of admission due to their scores.