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@inthehands having examples of mediocrity is what is often missing in teaching and why I think being amongst other students (who are not perfect by definition) is one of the most valuable parts of learning at a school, imo.
Being able to bounce stuff off an ai when self learning is what I really value, because it teaches me what boring is, and it puts me in the teachers shoes to explain what it did wrong.
I often double down on that concept by having the ai explicitly take on that role.
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Paul Cantrell
While I imagine AI could be genuinely useful in the future for information discovery in research, it’s not clear that it served that function for any students this time around.
But it didn’t need to in order to be useful. Simply having this touchstone — “here is what mediocrity looks like for your topic” — challenged them to do better, and got them thinking about writing from the reader’s POV. They learned from their own reactions.
Paul Cantrell
Results of the experiment (having students generate and critique AI output as a writing exercise; see upthread):
Success! It seems to me the paper quality leveled up.
Hard to judge: not a controlled experiment, small N, subjective, etc., but gosh…the papers this year are more focused on content, more coherent, and less prone to rambling page-filler text.
Having “What does BS on my topic sound like?” as reference point really seems to have been helpful.
Paul Cantrell
• I want to prepare students for the future they’ll encounter — and help them identify what makes •them• valuable (for the job market, for the good of the world, for their own sense of purpose) in that future.
How will humans still matter in the face of automation?
I find the answer to that question often refocuses pedagogy where it should have been in the first place. Automatability correlates with BS teaching.
Paul Cantrell
Contextualizing thoughts on the goals of this assignment:
• I want students to think critically about AI, beyond all the hype juice, based on real experience.
• AI will likely become a useful assistive technology (just like web search). Students should learn it to use it _wisely_ (just like web search).
• Examples of bad writing are always useful. Now we can generate them!
• Humans are better at reacting than imagining. “That's not quite right!” is an excellent writing-sharpening thought.
Paul Cantrell
My favorite outcome so far: a student remarked (paraphrasing here) that she didn’t realize how much she had to say in her paper until she saw how wrong the AI was, how much it missed the point.
Observing her own reaction to BS about her topic made her realize she’d underestimated the extent of her own newly-forming knowledge. That…that is the sort of outcome an educator dreams of.
Paul Cantrell
Early returns are promising. Students got into the activity. Discussion took over half the last day of class.
This is a Programming Languages class, and discussion took an interesting turn: how would •languages• change in a world where we expect AI code generation to be a normal part of the development process, and the problem for humans shifts (even further) away from “How do I generate code?” and toward “Does the code I’ve generated actually do what I think? What I want?”
#proglang #ai
Paul Cantrell
OK, trying an experiment with my Programming Languages class!
• Have an AI generate some of your writing assignment.
• Critique its output. Call BS on its BS.
Assignment details in screenshots below. I’ll let you know how it goes.
(Here are the links from the screenshots:)
Raw AI Text:
https://gist.github.com/pcantrell/7b68ce7c5b2e329543e2dadd6853be21
Comments on AI Text:
https://gist.github.com/pcantrell/d51bc2d4257027a6b4c64c9010d42c32
(Better) Human Text
https://gist.github.com/pcantrell/f363734336e6063f61e451e2658b50a6
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