I'm honored to have received the NSF Graduate Research Fellowship (GRFP)! I'll be using this support to study whether connecting coursework to students' interests and lived experiences can improve learning.
About
I’m interested in making computing education more accessible and personally meaningful through Human-Computer Interaction (HCI) and AI. My interest in computing began in seventh grade when I started programming on my TI-84 calculator. At Temple University, I began researching how to help novice students understand programming concepts.
My work currently explores how large language models (LLMs) can generate analogies, explanations, and learning materials that reflect students' interests and backgrounds. I am passionate about making computing more inclusive, especially for students who don’t yet see themselves represented in technical spaces. In the fall of 2025, I began my PhD at the University of Michigan School of Information, where I am advised by Dr. Barbara Ericson. Go blue!
Research
My research focuses on using LLMs to personalize learning in computing education. I study how AI-generated explanations and analogies can be adapted to align with students’ interests, cultural backgrounds, and learning needs.
I combine LLMs with perspectives from HCI to better understand how to support intrinsic motivation and deliver adaptive feedback. This includes building interactive tools, analyzing student responses, and evaluating how personalized support affects comprehension. I’m focused on making sure these systems help students learn, not replace or mislead them.