Data Science Institute

I'm interested in various facets of how people learn and use formal systems. My current focus is computing education, where I'm looking at models and representations for explaining program behavior (notional machines) and how to leverage contrasts between concrete examples to teach computing concepts. I've been developing a course (and textbook) on teaching computing through a data-centric lens (data science + data structures). I am also one of the faculty leading the design and assess of our department-wide effort on integrating socially-responsible computing across all four years of our CS curriculum. Through this project, I'm trying to understand how people learn to perceive and reason about social systems. I've also worked on diagrammatic logics for hardware design (late 1990s), modular verification of feature-oriented programs (early 2000s), and reasoning about access-control and privacy policies (mid-late 2000s). Those projects emphasized formal systems over human reasoning. My work in computing education tilts the balance, but is part of the same broad theme.

I have been heavily involved in outreach for K-12 computing education since the late 1990s.

Almost all of my work is done in collaboration with two terrific teams: the Brown Computing Education Research group and Bootstrap (K-12 outreach).