Socratic inquiry
Questions reveal assumptions, causal claims, missing evidence, and competing explanations.
Academic Model
AI-forward Socratic learning, grounded in evidence and human judgment.
Technology expands the space of inquiry. It does not replace the student’s responsibility to reason, verify, interpret, and act ethically.
Overview
The method
Students begin with questions rather than prepackaged conclusions. Faculty and AI systems help expose assumptions, generate alternatives, locate evidence, test models, and refine outputs. The student remains accountable for source quality, methodological choice, interpretation, and final claims.
AI-assisted iteration
Use AI for comparison, simulation, critique, coding, visualization, and structured exploration.
Verification discipline
Trace claims to primary evidence and document uncertainty, limitations, and disagreement.
Product-throughline
Move from inquiry to an output that can be read, tested, used, or challenged.
Human responsibility
The student is not the passenger.
AI can increase speed and range while also increasing the risk of plausible error, shallow synthesis, and outsourced judgment. Courses therefore require source inspection, methodological notes, decision records, and explicit disclosure of AI-supported work.
View programs
Every course should include
Shared academic expectations
Question record
What changed as the inquiry developed and why?
Evidence map
Which sources, measurements, and observations support each important claim?
Method note
How was the work performed and what are its limits?
Public output
What durable artifact demonstrates the learning?
Next step
Use advanced tools without surrendering intellectual agency.
Explore current courses and future certificate pathways.