Peer-reviewed manuscripts, conference presentations, and works in progress. Most current work sits at the intersection of generative AI, learning technologies, and equity in education. Items marked under review are out for peer review; please request a copy directly.
An education-side examination of how generative AI is reshaping who gets to learn what, and on what terms. The piece argues that access alone does not close the gap — it can widen it — and looks at what schools and policy can do when a powerful new tool is unevenly distributed and unevenly understood. Title and journal withheld pending review outcome; please email for the manuscript.
Built and evaluated a multiagent large language model system that distributes patient interaction, tutoring, checklist monitoring, and final feedback across specialized agents to scaffold simulated medical consultations. Preliminary findings: gains concentrated in communication quality — empathic expression and detailed information gathering — rather than diagnostic correctness.
Co-developing an instructional framework that treats generative AI errors not as failures to suppress, but as designed opportunities to strengthen learners' verification skills, evaluative judgment, and critical engagement. Integrates productive failure, cognitive friction, and AI-supported learning design.