Research

My research program investigates how the structural design of physics education systems, including assessment practices, graduate admissions processes, and AI-enabled instructional technologies, shapes student learning and opportunity. I am a quantitative physics education researcher by training, specializing in machine learning and big data analysis, while increasingly incorporating qualitative methods into my work.

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The graduate admissions process in physics

Because physics is one of the least diverse STEM fields, increasing attention is directed toward the admission practices of graduate programs. I'm especially interested in how graduate applicants and programs evaluate each other. That is, how do applicants decide what programs to apply to and how do programs determine which applicants to admit.

My previous work has explored the impact of rubric-based holistic admissions processes, finding that these serve as a promising route to more equitable admissions without adding additional work to admissions committees. My current work examines how departments talk about their graduate programs and what aspects applicants especially care about.

Assessment in introductory physics

Introductory physics is a required course for students pursuing physical science and engineering majors. As such, a low grade can derail a student's career plans. I'm interested in how instructors assess student knowledge as well as grading practices they employ. I'm particularly interested in understanding how multiple-choice questions are used and how alternative formats may benefit learning. I'm also interested in how various grade weighting schemes influence student grades, and how faculty develop their assessment schemes.

AI-supported instruction

As an instructor, I'm especially interested in how AI can benefit my teaching and improve learning within my course. My work in this area examines how LLMs can automate time-intensive tasks such as responding to student questions and summarizing student feedback and how LLMs can support personalized learning at scale.