Fox Curriculum
The longer arguments.
Research agenda and position writing that runs past the length of an essay.
Human judgment gets more valuable, not less.
Artificial intelligence is reshaping the cognitive landscape across K-12 classrooms, college campuses, and adult learning environments simultaneously, and it is moving faster than schools can adapt. The foundations of how education uses these tools are being set right now, and I intend to help set them. My future research agenda is organized around three intersecting questions.
Does AI adoption accelerate or erode reasoning?
How is AI adoption affecting the development of analytical reasoning across educational levels, and does it accelerate or erode the higher-order thinking that rigorous coursework and professional environments demand?
What makes instruction AI-resilient?
What instructional frameworks are most effective at developing critical thinking that is both AI-augmented and AI-resilient, from secondary through postsecondary and into workforce training?
What are the equity implications?
What are the equity implications of differential AI access across school types, income levels, and demographic groups, and how do those disparities compound existing gaps in college and career readiness?
"My thesis about AI and curriculum is specific: human judgment about what matters goes up in value, not down, when AI is in the production loop, because the thing that degrades fastest is the ability to distinguish content that looks like teaching from content that actually teaches. Encoding that distinction into systems that scale it is curriculum work."
Statement on AI in Education and Work
The full long-form statement: why corporate and classroom AI are two ends of one pipeline, why adult and adolescent learners should not be handed the same assistant, and what it takes to test whether any of it worked.