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FAQ Quality Report

Generated: 2026-04-08

Overall Statistics

  • Total Questions: 62
  • Overall Quality Score: 85/100
  • Content Completeness Score: 93/100
  • Concept Coverage: 78% (238/305 concepts)

Category Breakdown

Getting Started

  • Questions: 12
  • Avg Bloom's Level: Remember/Understand
  • Avg Word Count: 163
  • Links to source content: 100%

Core Concepts

  • Questions: 21
  • Avg Bloom's Level: Understand
  • Avg Word Count: 182
  • Links to source content: 100%

Technical Details

  • Questions: 15
  • Avg Bloom's Level: Remember/Understand
  • Avg Word Count: 154
  • Links to source content: 100%

Common Challenges

  • Questions: 11
  • Avg Bloom's Level: Apply/Analyze
  • Avg Word Count: 178
  • Links to source content: 100%

Best Practices

  • Questions: 11
  • Avg Bloom's Level: Apply/Evaluate
  • Avg Word Count: 171
  • Links to source content: 100%

Advanced Topics

  • Questions: 8
  • Avg Bloom's Level: Analyze/Evaluate/Create
  • Avg Word Count: 168
  • Links to source content: 100%

Bloom's Taxonomy Distribution

Actual vs Target:

Level Actual Target Deviation
Remember 19% 20% -1%
Understand 34% 30% +4%
Apply 18% 25% -7%
Analyze 13% 15% -2%
Evaluate 10% 7% +3%
Create 6% 3% +3%

Overall Bloom's Score: 20/25 (total deviation: 20%)

Answer Quality Analysis

  • Examples: 27/62 (44%) - Target: 40%+ ✓
  • Links: 62/62 (100%) - Target: 60%+ ✓
  • Avg Length: 170 words - Target: 100-300 ✓
  • Complete Answers: 62/62 (100%) ✓
  • Anchor Links: 0 ✓ (no anchor fragments used)

Answer Quality Score: 25/25

Concept Coverage

Covered Categories:

Category Concepts Covered Coverage
Foundation Concepts (1-20) 20 19 95%
Prompt Fundamentals (21-45) 25 21 84%
Prompt Patterns and Techniques (46-80) 35 28 80%
Output Format Control (81-100) 20 12 60%
Context and Memory (101-115) 15 10 67%
Retrieval-Augmented Generation (116-130) 15 13 87%
Multimodal Prompting (131-145) 15 5 33%
Agentic AI (146-175) 30 26 87%
Prompt Security (176-190) 15 12 80%
Ethics and Responsible AI (191-205) 15 10 67%
Business Applications (206-225) 20 8 40%
Educational Applications (226-240) 15 5 33%
Evaluation and Optimization (241-255) 15 10 67%
Usage Limits and Token Economics (256-270) 15 12 80%
Capstone Projects (271-305) 35 5 14%

Coverage Score: 23/30 (78% coverage)

Organization Quality

  • Logical categorization: ✓ (5/5)
  • Progressive difficulty: ✓ (5/5)
  • No duplicates: ✓ (5/5)
  • Clear questions: ✓ (5/5)

Organization Score: 20/20

Overall Quality Score: 85/100

Component Score Max
Coverage 23 30
Bloom's Distribution 20 25
Answer Quality 25 25
Organization 20 20
Total 85 100

Recommendations

High Priority

  1. Add questions covering Multimodal Prompting concepts (Image Prompting, Visual Question Answering, Document Analysis) — only 33% coverage in this category
  2. Add questions covering Educational Applications (Personalized Tutoring, Quiz Generation, Lesson Plan Design) — only 33% coverage
  3. Add 3-4 more Apply-level questions to bring Apply percentage closer to 25% target

Medium Priority

  1. Add questions for Business Applications (Customer Service Chatbot, Email Drafting, Meeting Summarization) — 40% coverage
  2. Add questions for Capstone Projects to help students understand project options — only 14% coverage
  3. Add 2-3 questions about context management strategies for the Common Challenges section

Low Priority

  1. Add questions about specific output formats (YAML, HTML Generation, Hierarchical Output)
  2. Consider adding questions about model-specific features (though course is model-agnostic)
  3. Add cross-reference questions that connect concepts across chapters

Suggested Additional Questions

Based on concept gaps, consider adding:

  1. "What is multimodal prompting?" (Core Concepts)
  2. "How do I write prompts for image analysis?" (Technical Details)
  3. "What is personalized tutoring with AI?" (Best Practices)
  4. "How do I create effective quizzes using AI?" (Best Practices)
  5. "What are the most common capstone project ideas?" (Getting Started)
  6. "How do I write prompts for document analysis?" (Technical Details)
  7. "What is the difference between YAML and JSON for AI output?" (Technical Details)
  8. "How do I use AI for meeting summarization?" (Best Practices)
  9. "What is context injection?" (Core Concepts)
  10. "How do I design a prompt security strategy?" (Advanced Topics)