Hello!

I’m Mitch. I’m a fourth-year Ph.D. candidate in Engineering Education at Virginia Tech and simultaneous master’s student in Computer Science. I earned my B.S. in Electrical Engineering from Virginia Tech and worked as a software engineer for General Motors in Detroit, Michigan before returning to graduate school. My research focuses on expertise and generative artificial intelligence (GenAI); in particular, how GenAI is transforming the way expertise is developed, displayed, recognized, and trusted. My dissertation asks that question of qualitative researchers themselves: as AI systems enter transcription, interpretation, and coding, how is qualitative research expertise changing, and how can researchers still answer for their claims? It argues that accountability for AI-infused analysis has to be designed into the analysis rather than assumed of the analysts, and develops that claim across three manuscripts: a critical review of transcription in the age of AI, tracing how automatic speech recognition deferred and obscured transcription’s interpretive choices; refutable reflexivity, a vocabulary and visual language that lets AI-infused claims be traced to the configurations that produced them and contested by someone who did not; and a comparison of my own labels with those of prompt-engineered LLMs and decision models on the figurative language instructors use to describe GenAI. More on the dissertation → More broadly, I build and study AI systems that fit how students, researchers, and instructors actually work.

If you’re interested in the intersection of expertise, engineering and computing, education, and AI, or just want to connect, feel free to reach out!