Quiz Question Generator
Generate a diverse set of quiz questions at multiple difficulty levels for any topic, with answer keys and explanations.
Prompt Template
You are an assessment designer. Generate quiz questions for the following: Subject: [subject] Topic: [specific topic] Audience: [who is being assessed] Number of questions: [total] Question types: [multiple choice / true-false / short answer / fill-in-the-blank / mix] Difficulty distribution: [e.g., 40% easy, 40% medium, 20% hard] Learning objectives tested: [what knowledge or skills] For each question provide: - The question - Answer options (for MC) or the correct answer - Correct answer marked - Brief explanation of why it's correct (and why distractors are wrong for MC) - Difficulty label
Example Output
Quiz: Introduction to Machine Learning — 10 Questions
Q1 [Easy] Multiple Choice
What does 'supervised learning' mean?
A) The model learns without any data
B) The model learns from labeled training examples ✅
C) A human supervises the model in real-time
D) The model supervises other models
*Explanation: Supervised learning uses input-output pairs (labeled data) to train models. 'B' is correct. 'C' is a common misconception about what 'supervised' means in this context.*
Q2 [Medium] True/False
A model with very high training accuracy and very low test accuracy is likely underfitting.
**Answer: False** ✅
*Explanation: This describes overfitting — the model memorized training data but fails to generalize. Underfitting would show low accuracy on both sets.*
Q3 [Hard] Short Answer
Explain the bias-variance tradeoff in 2-3 sentences.
*Model answer: High-bias models are too simple and underfit the data. High-variance models are too complex and overfit. The goal is to find the sweet spot where both are minimized...*
Tips for Best Results
- 💡Ask for 'plausible distractors' in multiple choice — the wrong answers should require actual knowledge to eliminate
- 💡Request questions at Bloom's Taxonomy level 3+ for questions that test application, not just recall
- 💡Add your actual course content as context — generic questions are less useful than topic-specific ones
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