My school uses a project-based system: you complete increasingly difficult projects, validate them, and then move on to the next one. I learned basic programming concepts from textbooks and online guides, but for most projects I have used AI extensively. I do not simply ask it to generate an entire program and submit it. Instead, I describe a specific feature I want, use its explanation or code as a starting point, adapt it to my project, and try to understand how it works.
I am wondering whether this is really comparable to finding an example in a textbook. For instance, if I do not know how to implement a stack, is asking an AI for example functions fundamentally different from reading a textbook example and applying it myself?
I feel somewhat fraudulent because I use AI so often. I believe I could recreate many of my projects with much less assistance now, but repeating every project would take a lot of time. I also plan to study more programming and language textbooks so I can become increasingly independent. Am I using AI in a reasonable way, or am I outsourcing too much of the learning process?
4 Answers
Using AI is not automatically wrong, but copying tailored solutions can remove the most important part of learning: figuring out how to apply general ideas to your own problem. Textbook examples usually teach a concept without solving your exact assignment, while AI can quietly do the design and problem-solving for you. Try solving the problem yourself first, then ask for a hint, an explanation of documentation, or a review of your approach rather than requesting the finished implementation.
A good rule is to treat AI output like code written by an inexperienced intern. It may be useful, but it can be incorrect, inefficient, or based on something it copied without understanding. You should be able to explain every part, test it with unit tests, and recognize when the answer does not fit your project. Also spend some regular time coding without AI so you are not helpless when it is unavailable.
The real question is whether you are learning to program or merely learning to operate an AI coding tool. If AI is deciding the architecture, breaking the project into tasks, and producing most of the code, then you are probably moving too fast for the learning goal. If you already understand the fundamentals and use it to clarify syntax, explain documentation, suggest alternatives, or review code you wrote, it is much less risky. You should be able to rebuild the core idea later without relying on the same answer.
Your approach can be productive if you change the order of operations. First write down the behavior you need and make several attempts yourself. If you get stuck, ask for a small hint or for the relevant concept, not the complete solution. Only ask to see an example after you have tried, and make the example sufficiently different that you still have to adapt it. That preserves the difficult thinking instead of turning the tool into a copy-and-paste machine.
That makes sense. I was mainly trying to save time, but I can see that asking for the exact implementation may be skipping the part I actually need to practice.