Use GitHub Copilot to Promote Deep Learning

Contributed by: Rizèl Scarlett

Difficulty level: Easy

During conversations with my developer friends, the issue of GitHub Copilot generating flawed code often arises. They argue that this can mislead beginners and teach them poor programming practices. I won’t lie. Mindlessly trusting incorrect code generative code can mislead beginners. However, I believe that encountering imperfect code is an integral part of the learning process, regardless of whether GitHub Copilot is involved. When exploring a new programming language, especially at the beginning of my career, I often resort to copying code from StackOverflow, skimming through documentation, and pasting code snippets haphazardly. Sometimes, the code I copy doesn’t even work, but it still provides a starting point and helps me grasp the problem at hand. With time, I learn better practices and approaches, gradually refining my skills.

The same principle applies to GitHub Copilot. In the Shortcut “Use GitHub Copilot to Learn Syntax For a New Framework or Programming Language”, GitHub Copilot attempted to generate an ice cream cone with a light pink scoop and a cherry on top. However, the generated triangle for the cone had the pointy part facing upward, whereas cones typically have the pointy part facing downward. While it could be argued that GitHub Copilot misled me, I wouldn’t have known how to create a triangle without its guidance. This presents an opportunity for me to debug ...