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Walking through our computer science building, we can see ChatGPT on nearly every screen. Today, students can use AI at every stage of their learning process. For example, instead of struggling to figure out how to start a coding assignment, students can simply copy and paste the question into an AI model. Even if the solution doesn’t work perfectly out of the box, they can re-prompt the model with its own solution and an error description to receive a fixed solution.
We can’t help but compare this to our own experiences learning to program during undergrad. We remember the struggle of writing our first lines of code, the days spent debugging with friends at the student center, and the feeling of success after a night’s sleep when finally fixing the bug. We didn’t enjoy being stuck in the moment; but now, we look back and understand that going through these surmountable struggles was important for our learning. Our productive struggles not only helped us provide the correct solution in the short run, but also how to write stronger, less error-prone code in the long run….
