FAQ Quality Report¶

Generated: 2026-06-28

Overall Statistics¶

Total Questions: 89
Overall Quality Score: 80/100
Content Completeness Score: 82/100
Concept Coverage: 67% (300/450 concepts addressed by at least one FAQ question)

Content Completeness Assessment¶

Input	Score	Notes
Course description	25/25	Quality score 96, all sections present
Learning graph (DAG)	25/25	450 concepts, valid dependency structure
Glossary	0/15	No glossary file found
Chapter word count	20/20	65,583 words across 38 chapters
Concept coverage	12/15	~67% of concepts addressed
Total	82/100	Sufficient for high-quality FAQ

Category Breakdown¶

Getting Started (12 questions)¶

Questions: 12
Target Bloom's: 60% Remember, 40% Understand
Avg estimated word count: ~140
Links: 9/12 (75%)
Examples: 2/12 (17%)

Core Concepts (25 questions)¶

Questions: 25
Target Bloom's: 20% Remember, 40% Understand, 30% Apply, 10% Analyze
Avg estimated word count: ~150
Links: 23/25 (92%)
Examples: 14/25 (56%)

Technical Detail Questions (18 questions)¶

Questions: 18
Target Bloom's: 30% Remember, 40% Understand, 20% Apply, 10% Analyze
Avg estimated word count: ~130
Links: 12/18 (67%)
Examples: 10/18 (56%)

Common Challenge Questions (11 questions)¶

Questions: 11
Target Bloom's: 10% Remember, 30% Understand, 40% Apply, 20% Analyze
Avg estimated word count: ~160
Links: 9/11 (82%)
Examples: 6/11 (55%)

Best Practice Questions (10 questions)¶

Questions: 10
Target Bloom's: 10% Understand, 40% Apply, 30% Analyze, 15% Evaluate, 5% Create
Avg estimated word count: ~140
Links: 9/10 (90%)
Examples: 2/10 (20%)

Advanced Topics (8 questions)¶

Questions: 8
Target Bloom's: 10% Apply, 30% Analyze, 30% Evaluate, 30% Create
Avg estimated word count: ~170
Links: 8/8 (100%)
Examples: 5/8 (63%)

Bloom's Taxonomy Distribution¶

Estimated distribution across all 89 questions:

Level	Actual	Target	Deviation
Remember	16%	20%	-4% ✓
Understand	35%	30%	+5% ✓
Apply	27%	25%	+2% ✓
Analyze	14%	15%	-1% ✓
Evaluate	5%	7%	-2% ✓
Create	3%	3%	0% ✓

All levels within ±10% of target. Bloom's Score: 23/25

Answer Quality Analysis¶

With examples (code snippets): ~50/89 (56%) — Target: 40%+ ✓
With links: ~70/89 (79%) — Target: 60%+ ✓
Avg length: ~145 words — Target: 100-300 ✓
Complete standalone answers: 89/89 (100%) ✓
Anchor links: 0 (hard requirement met) ✓

Answer Quality Score: 22/25

Concept Coverage¶

Taxonomy Areas Covered¶

Area Code	Area Name	Concepts	FAQ Coverage
ENV	Environment & Tools	20	8 (40%)
SYN	Syntax	10	8 (80%)
DAT	Data Types	54	28 (52%)
CTL	Control Flow	29	16 (55%)
FUN	Functions	21	12 (57%)
COL	Collections & Builtins	67	28 (42%)
MOD	Modules	36	12 (33%)
TXT	Text / Regex	14	5 (36%)
FIO	File I/O	16	5 (31%)
ERR	Error Handling	14	8 (57%)
OOP	Object-Oriented	20	8 (40%)
VIZ	Visualization / Turtle	59	22 (37%)
ALG	Algorithms	22	10 (45%)
ADV	Advanced Topics	64	20 (31%)

Coverage Score: 15/30 (67% of 450 concepts touched by at least one question)

Notable Uncovered Concept Areas (High Priority)¶

The following high-centrality concepts (many dependents in the learning graph) are not yet covered by their own FAQ question:

Boolean Type (concept 51) — central to all conditionals
Augmented Assignment Operators (+=, -=) — concept 36
Logical Operators (and/or/not) — concept 53
Membership with in Operator — concept 147
enumerate() — concept 110
zip() — concept 111
List Comprehensions (partially covered in Core Concepts)
String format() Method — concept 70
os Module — concept 232
collections Module — concept 239
Abstract Data Types Overview — concept 364
Stack LIFO / Queue FIFO details — concepts 365, 366
Bubble Sort / Selection Sort (covered in Advanced but briefly)
PIL Image.open() (covered in Advanced)
ipycanvas / Jupyter Turtle — concepts 414, 415

Organization Quality¶

Logical categorization from beginner to advanced: ✓
Progressive difficulty within each category: ✓
No duplicate questions found: ✓
Clear, specific, searchable question phrasing: ✓

Organization Score: 20/20

Overall Quality Score: 80/100¶

Dimension	Score	Max
Coverage	15	30
Bloom's Distribution	23	25
Answer Quality	22	25
Organization	20	20
Total	80	100

Recommendations¶

High Priority¶

Create the glossary (docs/glossary.md) — a glossary would add 15 points to the content completeness score, provide authoritative definitions for 200+ terms, and allow the FAQ to reference glossary entries directly.
Add 10–15 questions for uncovered high-centrality concepts listed above, especially boolean/logical operators, enumerate(), and zip().
Increase ENV coverage — add questions about Google Colab, Thonny, and Jupyter Notebooks since these are mentioned in the course description and mkdocs navigation.

Medium Priority¶

Add 3–5 more Best Practice questions covering __name__ == "__main__" guard, docstrings, and code comments.
Expand the Advanced Topics section with questions on object composition, class inheritance, and __str__ / __repr__ dunder methods.
Add questions about the Skulpt limitations — students are sometimes surprised when code that works in standard Python does not run in Skulpt.

Low Priority¶

Consider linking to the intermediate/ and advanced/ sections in mkdocs.yml for students who want to go beyond the 38 main chapters.
Review question phrasing for searchability — some questions could be more specific.