Assuming there's more well-authenticated artifacts, you could use something like a causal-graph to identify where students may not have been honest in their tak

Assuming there's more well-authenticated artifacts, you could use something like a causal-graph to identify where students may not have been honest in their take-home work. If a 100% comprehension level of say, nested for-loops, suddenly becomes a 30% comprehension when the student is being watched, that's cause for concern, you'd just need to have infrastructure in place to trace those relationships. Another good option would be to ask for pseudocode, drawings, flowcharts instead of Python. I don't have access to see if Copilot can pseudocode things, but I don't think the mechanical task of literally writing code is the best way to test this sort of thing anymore or perhaps, it's a bad target/metric. Switching the course to some obscure graphical programming language might be another good option as well.