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Explain overfitting with the memorized-practice-test analogy
Practice: Saying who it's for. About 5 minutes.
About this exercise
Your AI and Society course (no programming) asks you to explain overfitting. Get exactly 3 numbered sentences using only the professor's practice-test analogy (what training data is, what overfitting is, why it fails on new data), then one line starting 'Check:' with a question to test yourself, under 80 words, plain text. No code, no math and none of the words 'parameters', 'loss' or 'variance'.
Common mistakes when you ask AI for this
- Asking the general question. The AI explains with technical terms like variance and loss, which your professor won't credit. Try: Say: "Use only the practice-test analogy from my notes."
- Not saying how many sentences. The AI picks its own number, and it usually picks more sentences than you need. Try: Be exact: "Exactly 3 numbered sentences."
- Not banning jargon. AI defaults to the textbook terms. Try: Add: "No code, math, parameters, loss or variance."
- No way to test yourself. The AI explains and stops, so you never check whether it stuck. Try: Add: "End with one line starting 'Check:' with a question, no answer."
- Trusting the AI to count words. AI is bad at counting. Ask for a total and it often lands 20% over. Try: Cap each sentence: "each under 20 words."
- Forgetting where it will be read. AI formats for a screen, with bold and headings that show up as stray symbols on the exam. Try: Say: "Plain text, no bold, no headings."
What a strong prompt includes
- Names the analogy
- Says how many sentences
- Bans jargon
- Asks for a check question
- Sets a length limit
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