Research
Doctoral Research
I’m a doctoral candidate at National University, working toward a design-based research study of AI literacy pedagogy in secondary computer science.
The shape: build and iterate an AI literacy unit inside a running high school CS course, then consolidate what the design cycles teach into principles that transfer. The intended contribution is the validated design principles under a rural single-teacher constraint, not the unit itself. The methodology is not settled until my committee meets in 2027, so read that as the direction rather than a finished claim.
Focus areas:
- How CS educators adapt practice when AI becomes a legitimate tool for student programming work
- Balancing foundational skill development with AI-augmented workflows
- Assessment design in AI-augmented learning environments
- What AI literacy instruction looks like when one teacher is the entire CS department
Timeline: Dissertation proposal in progress. Committee formation June 2027, defense targeted December 2027.
ORCID: 0009-0001-4704-3601
Publications
“Distrust the Machine” — ACM Inroads. Submitted July 2026, under review. Generative AI in the CS classroom demands productive skepticism rather than prohibition or uncritical adoption, with a four-phase classroom scaffold for building it.
Applied Work
NASEM foundational competencies coverage analysis — four course builds scored against the seven data-and-computing competencies named in the 2026 National Academies consensus study, read against the lesson files rather than the unit titles. Method and limits stated; the ratings are analytic judgment, not a validated instrument.
Standards crosswalk auditor — tooling that audits five CS courses against their required standards and reports genuine coverage gaps.
Service
AP Computer Science Principles Reader, College Board, since 2020.
Interested in collaboration or want to learn more? Contact me to discuss my research.