Curriculum Design
I design curriculum that balances foundational CS skills with emerging literacies like AI fluency and academic integrity in an AI-augmented world. Five pathways at Dayton High School, each authored in-house, each verified against its standards by tooling rather than by assertion.
Everything below is built and readable. Where a claim can be checked, there is a link to check it with.
Standards Crosswalk & Curriculum Audit Tool
An interactive audit of five CS course builds against the standards each one is required to teach: Advanced CS I, Web Development & Design I, Digital Game Design I, Computer Education Technology, and AP Computer Science Principles. Pick a course and it shows you, standard by standard, which specific lesson teaches it, and which standards nothing teaches yet.
I built it because I kept asking the question by hand. Its first honest run told me a course I believed was 77% aligned was actually at 54%. I rebuilt all seventeen units around what it found. The gaps are still shown on purpose.
Open the auditor · Browse the curriculum map
NASEM Foundational Competencies: Coverage Analysis
In 2026 the National Academies named seven foundational data-and-computing competencies for K–12. I scored four of my course builds against them, reading the actual lesson files rather than the unit titles or the crosswalk sheets, and published the result with its method and its limits stated.
Six of seven hold in the flagship course. The one that does not is the more interesting finding, and I argue in the analysis that the course should stop at six rather than reach for a competency that belongs to a statistics class. A declared partial is more credible than a full row of checkmarks.
Case Study: Replacing a Proprietary Platform
A vendor curriculum stopped meeting Nevada’s standards, so I wrote the replacement: a complete course covering all 51 Appendix A indicators, backwards-designed, with a robotics spine and its own assessments and scoring materials. The case study covers the method rather than the course, because the transferable part is the method.
AI Literacy Across the Pathway
A four-phase classroom progression — awareness, bounded practice, critical evaluation, synthesis — running through a full-year course, with the earlier courses feeding the flagship rather than each teaching AI literacy from scratch.
The argument behind it is that generative AI in the CS classroom demands productive skepticism rather than prohibition or uncritical adoption. That article, “Distrust the Machine,” is under review at ACM Inroads.
I also write about this as it develops, including the parts that do not work, at willbumgardner.substack.com.
Interested in the underlying lesson materials, or in this work as professional development? Get in touch.