Applying the scientific method to how we learn, build, and trust technical work as computing changes, with AI the driver today and QPUs and other advances on the horizon.
Each major advance in computing makes some hard-won skills routine and raises new questions about what to trust. AI is doing this now, and it won't be the last time. Collegeville treats this as something to study: we form hypotheses, test them, and share what holds up as papers, tools, skills, and games.
Senior capstone students at Saint John's University and the College of Saint Benedict have done research teamwork for over 25 years. Now we also build quizzes and puzzle games, like DataFables, that teach the basics AI can do quickly, so people keep the judgment to check its work.
Scientific software comes from small teams, shared libraries, and large ecosystems. We study which practices deliver real value, how testing and reproducibility earn trust, and how new tools and hardware reshape development, review, and maintenance.
We try new ways of working as technology arrives, from AI-assisted workflows and agent skills to emerging platforms such as quantum processors.
An archive of human skills, AI-assisted workflows and agent skills, grown out of the capstone course.
Visit CorpusA daily data-cleaning puzzle: find what's wrong with the table, or decide that nothing is.
Play DataFables More on the Games pageCollegeville grew out of decades of teaching and of leading scientific software efforts, including the Collegeville Workshops on Scientific Software and the US DOE Exascale Computing Project. Browse the Archived Collegeville site