LLM Programming Exercises

What do you do when teaching programming with LLMs that isn’t in this list? Critically review AI output. Have the LLM answer a programming question or explain a concept, then ask learners to review its response collectively for correctness, clarity, and omissions, testing claims against examples or documentation. Predict, solve, and compare. Have learners predict what code an LLM will generate for a problem (or solve it independently), then compare their work with the AI-generated solution and explain the differences. Debug and minimally repair code. Give learners a deliberately flawed program, tell them it was generated by AI (even if it wasn’t), and ask them to identify, explain, and find the smallest possible fix for each bug without initially asking the AI for help. Compare and rank multiple solutions. Have the LLM generate several different solutions to the same programming problem, then have learners compare them for correctness, readability, and efficiency. Guided discovery.…