1. Understanding how university academic programs and curricula create for students a sense of what “counts” as knowing and knowledge in STEM;
2. Documenting how students integrate interdisciplinary knowledge when solving problems in their courses;
3. Building rich theoretical accounts of how students learn computer programming and think about computation; and
4. Understanding how disciplinary knowledge, social identity, and feelings of alienation or belonging influence students’ decisions to remain in (or leave) STEM disciplines.
I have expertise in qualitative methods including clinical interviewing, discourse analysis, and ethnographic observational research, which I uses to study students both in and out of the classroom. Stemming from my work in David Hammer, Edward F. Redish, and Andrew Elby’s research group, I look for the productive cognitive resources students have for thinking about science, engineering, and computer programming.
I'm the principal maintainer of GranovaGG– an open-source add-on for R that provides advanced visualizations for quantitative analyses of variance. Brian also co-developed a system to automatically track changes to students’ programming code and visualize those changes over time, which allows researchers to see character-by-character changes in a student’s work.