Overview
I do science education research in Natasha Holmes’ lab. Building on my background in Physics and Astronomy, I apply quantitative methods to data on how we teach undergraduate science classes. My aim is to provide instructors with actionable, research-backed recommendations on classroom activities.
A large body of work has shown that lecture is less effective than active learning, and instructors are feeling the pressure to bring these active methods into their classrooms. The catch is that very little research has been done on which active learning methods are most effective and in which combinations. For example, is a completely flipped (no lecture) classroom better than one with half lecture and half active learning activities? The answer is unclear.
In my work, I find patterns between combinations of classroom activities and student learning outcomes in order to find the conditions under which students learn the most and the most equitably. This work has the potential to improve undergraduate science curriculum while removing some of the burden of curriculum design from instructors.
Previously, I studied cosmology in Nicholas Battaglia's group, where I focused on expanding simulations of large scale structure. I used machine learning to find the relationships between cosmological parameters and the evolution of galaxy clusters. The goal of this work is to better constrain the driving forces of structure formation and evolution, such as dark matter density and fluctuations in the early universe.
I graduated from UC Santa Cruz in 2020 with a degree in Astrophysics. While there, I researched the detection of primordial black holes, as well as the use of machine learning to measure weak lensing.
In my free time, you can find me crocheting, swimming, or spending time with my little dog.