[Sakos]

I find the analysis of the Codex group much more interesting and I feel further studies are necessary before drawing conclusions.

    Students frequently (n=501, 30%) copied the task description to generate the entire code with no prior manual coding attempts.

    Sometimes (n=197, 12%) students divided the task into multiple subgoals, and asked the AI to generate *only* the first subgoal instead of the entire task. 

    When decomposing the task into multiple subgoals, students sometimes (n=85, 5%) asked for code that was already in their editor. 

    Although rarely (n=16, 1%), but sometimes students generated code after having the solution to check and compare the AI's output with their own solution. 

    Students occasionally (n=89, 5%) wrote prompts that were similar to pseudo-code (e.g. "for num in numbers, if num > large, set large to num"). 

    Although most of the times students properly tested the AI-generated code before submitting, there were several (n=63, 4%) instances in which students submitted AI code without testing it. 

    Although rarely, but sometimes (n=30, 2%) students actively tinkered with the AI-generated code to properly understand the syntax and logic. 

    Similarly, sometimes students manually added code (like `print` statements) to the AI-generated code to help them verify that it works correctly.

Anecdotal evidence based on my own experience has suggested better recall of things I've engaged with and learned through ChatGPT than with standard learning through books or videos. I think the interactivity is an important aspect.