I am a PhD candidate in the Computer Science department at University of Illinois Urbana-Champaign with a focus on computing education research and human computer interaction, advised by Dr. Katie Cunningham.
I explore two key questions in my research:
How can we support students who are non-CS majors as they learn programming? 💻
How do educators design instructional content, and how can we design creativity support tools informed by their design process? ✏️
Recent Updates
Sep 2, 2026
🤖 I was selected as a Future Leader for the ACM AI Summit!
I had the opportunity to participate in the ACM AI Summit and the Future Leaders of AI doctoral consortium, discussing challenges around AI and societal impact.
July 29, 2026
✍️ I attended PPIG 2026 in London!
I presented our short paper “Towards Supporting Novice Programmers’ Web Search Skills for Using Unfamiliar Libraries and APIs” with Jinyoung Hur, Alex Atcheson, Claire Zheng, and Kathryn Cunningham at the 37th Annual PPIG Workshop in London, UK.
June 2, 2026
💰 Our grant proposal on supporting computing education for non-CS majors was awarded funding by the Grainger College of Engineering!
Our proposal, “Building a community of practice to support programming education across engineering departments,” was awarded funding as part of the Strategic Instructional Innovations Program (SIIP).
April 18, 2026
🏙️ I attended Illinois CS Education Meetup at UIC!
I had the chance to catch up with researchers and practitioners working on CS education from several Illinois instituions at this inaugural event.
April 1, 2026
🎊 Our paper ''Leveraging Human-AI Collaboration for a Passage-Based Question Authoring Tool'' is accepted at AIED 2026!
This work investigates how human-AI collaboration can support passage-based question authoring for high-stakes educational testing with collaborators from ACT.
March 1, 2026
✍️ I attended SIGCSE 2026!
I attended SIGCSE 2026 in St Louis, MO, and had the chance to share our work on purpose-first tutorials for helping novices learn authentic programming applications in a general education computing course. Read the paper here.
I am working with the Digital Science team to explore innovative ways of supporting content specialists and subject matter experts, and discovering design opportunities for supporting question authoring for ACT.
April 15, 2025
🎊 Our paper ''Generating Planning Feedback for Open-Ended Programming Exercises with LLMs'' is accepted at AIED 2025!
This work is about an exploratory pipeline to generate high-level planning feedback for open-ended programming exercises that are traditionally evaluated with test cases. Our work provides a new dimension of feedback in addition to correctness by detecting if the students are trying to implement the right approach, even in syntactically or semantically incorrect submissions. Preprint here.
Feb 1, 2025
🎊 Our paper ''PLAID: Supporting Computing Instructors to Identify Domain-Specific Programming Plans at Scale'' is accepted at CHI 2025!
In this work, we identified instructor needs for developing instruction for application-focused computing domains through interviews and design workshops, designed PLAID as an interface for navigating and refining LLM-generated content to address these needs, and evaluated it through an user study. Preprint here.
Dec 8, 2024
✍️ I attended SIGCSE Virtual 2024!
I had the pleasure of moderating a panel on teaching planning and decomposition skills with valuable panelists Dr Eliane S. Wiese, James Finnie-Ansley, Dr Rodrigo Silva Duran, and Dr Kathryn Cunningham. I also presented at the doctoral consortium organized by Dr Lauri Malmi and Dr Colleen Lewis.
🎊 Our paper ''Validating, Refining, and Identifying Programming Plans Using Learning Curve Analysis on Code Writing Data'' is accepted at ICER 2024!
In this paper, we focused on programming plans as a potential knowledge component model with my co-authors Max Fowler, Nicole Hu, and Katie Cunningham. Our analysis provides a tool to visualize students’ plan acquisition process and evaluate plans on how well students can apply them to solve new problems. Preprint here.
May 15, 2024
🎊 Our paper ''Reexamining Learning Curve Analysis in Programming Education: The Value of Many Small Problems'' is accepted at EDM 2024!
In this work, we replicated Kelly Rivers et al.’s 2016 paper with my co-authors Max Fowler and Katie Cunningham. Surprisingly, we found that AST nodes can model skill acquisition to a promising extent, contrary to prior findings, especially in courses with many short programming exercises. Our preprint is available here.
