Vibe Coding Course: Grading Rubrics & Assessment Criteria
Table of Contents
Overview
Total Points
Course Total: 300 points
- Assignment 1: 50 points
- Assignment 2: 100 points
- Assignment 3: 100 points
- Pro-level extensions: 50 points (bonus)
Grading Scale
| Points |
Letter Grade |
Description |
| 270-300 |
A |
Excellent understanding and execution |
| 240-269 |
B |
Good understanding with minor issues |
| 210-239 |
C |
Satisfactory with some gaps |
| 180-209 |
D |
Needs improvement |
| Below 180 |
F |
Insufficient work |
Assessment Focus
This course emphasizes:
- Process over perfection - Learning journey matters
- Understanding over originality - AI-generated code is expected
- Documentation over code - README and prompts are key
- Iteration over first attempt - Improvement is valued
Grading Philosophy
What We Assess
✅ Understanding:
- Can student explain what the code does?
- Can student modify and debug code?
- Does student understand the concepts?
✅ Process:
- Quality of prompts used with Cursor AI
- Iteration and improvement process
- Problem-solving approach
- Documentation quality
✅ Functionality:
- Does the code work as required?
- Are requirements met?
- Is the implementation clean?
What We Don’t Assess
❌ Code Originality:
- AI-generated code is expected
- Copying starter templates is fine
- Focus on learning, not originality
❌ Perfect Code:
- Minor bugs are acceptable if understood
- Code doesn’t need to be production-ready
- Learning process is more important
❌ Manual Coding Skills:
- Not testing ability to write code from scratch
- Testing ability to work with AI tools effectively
- Focus on modern development workflow
Assignment 1: Cursor Fundamentals Reflection
Total Points: 50
Rubric
| Criteria |
Excellent (45-50) |
Good (35-44) |
Satisfactory (25-34) |
Needs Improvement (0-24) |
| Question 1: Multi-file Reasoning (10 pts) |
Clear, detailed explanation with examples |
Good explanation, some examples |
Basic understanding shown |
Vague or incorrect |
| Question 2: Good Prompts (10 pts) |
Excellent examples, well-explained |
Good examples provided |
Basic examples |
Weak or missing examples |
| Question 3: Debugging Workflow (10 pts) |
Clear workflow, shows understanding |
Good workflow described |
Basic workflow |
Unclear or missing |
| Question 4: Iteration and Improvement (10 pts) |
Excellent iteration example, well-explained |
Good iteration example |
Basic understanding |
Unclear or missing |
| Question 5: Personal Benefits (10 pts) |
Thoughtful, specific reflection |
Good reflection |
Basic reflection |
Superficial or missing |
Quality Indicators
Excellent (45-50 points):
- All 5 questions answered thoroughly
- Examples are specific and relevant
- Shows deep understanding of concepts
- Iteration example is clear and practical
- Personal reflection is thoughtful
- Writing is clear and well-organized
Good (35-44 points):
- All 5 questions answered
- Examples provided
- Shows good understanding
- Iteration example provided
- Some depth in reflection
- Writing is clear
Satisfactory (25-34 points):
- Most questions answered
- Basic examples
- Shows basic understanding
- Basic iteration understanding
- Minimal reflection
- Writing needs improvement
Needs Improvement (0-24 points):
- Missing answers
- No examples
- Shows misunderstanding
- No iteration understanding
- No reflection
- Poor writing quality
Common Issues
- Vague answers: “It’s useful” without explanation
- Missing examples: Concepts explained but no concrete examples
- Copy-paste: Answers copied from documentation without understanding
- Incomplete: Not all 5 questions answered
- No iteration example: Question 4 answered without concrete scenario
Assignment 2: E2E Hello World
Total Points: 100
Rubric
| Criteria |
Excellent (90-100) |
Good (75-89) |
Satisfactory (60-74) |
Needs Improvement (0-59) |
| Functionality (40 pts) |
Everything works perfectly |
Minor issues, mostly works |
Some issues, partial functionality |
Major issues, doesn’t work |
| Code Quality (25 pts) |
Clean, well-organized, readable |
Good structure, mostly clean |
Basic structure, some issues |
Poor structure, hard to read |
| Documentation (20 pts) |
Excellent README, clear prompts |
Good README, some prompts |
Basic README, minimal prompts |
Poor or missing README |
| Process (15 pts) |
Clear workflow, good prompts |
Good workflow shown |
Basic workflow |
Unclear process |
Detailed Breakdown
Functionality (40 points)
Server (20 points):
- Server runs without errors: 5 points
- Endpoint
/api/hello exists: 5 points
- Returns correct JSON format: 5 points
- Returns correct message: 5 points
Client (20 points):
- HTML file exists and loads: 5 points
- Fetch API implemented: 5 points
- Message displays correctly: 5 points
- Error handling (basic): 5 points
Code Quality (25 points)
Structure (10 points):
- Proper file organization: 5 points
- Clear separation of concerns: 5 points
Readability (10 points):
- Meaningful variable names: 5 points
- Code comments where needed: 5 points
Best Practices (5 points):
- Follows language conventions: 3 points
- No obvious code smells: 2 points
Documentation (20 points)
README.md (15 points):
- Setup instructions: 5 points
- How to run: 5 points
- Screenshot of working app: 5 points
Prompt Documentation (5 points):
- Documents prompts used: 3 points
- Explains approach: 2 points
Process (15 points)
Workflow (10 points):
- Clear development process: 5 points
- Iteration and improvement: 5 points
Problem-Solving (5 points):
- Shows debugging process: 3 points
- Documents challenges: 2 points
Quality Indicators
Excellent (90-100 points):
- Everything works perfectly
- Code is clean and well-organized
- Excellent documentation
- Clear process and prompts documented
- Screenshot included
Good (75-89 points):
- Minor issues, mostly functional
- Good code structure
- Good documentation
- Process documented
- Screenshot included
Satisfactory (60-74 points):
- Some functionality issues
- Basic code structure
- Basic documentation
- Minimal process documentation
- May be missing screenshot
Needs Improvement (0-59 points):
- Major functionality issues
- Poor code structure
- Missing or poor documentation
- No process documentation
- Missing screenshot
Assignment 3: Mini Feature Implementation
Total Points: 100
Rubric
| Criteria |
Excellent (90-100) |
Good (75-89) |
Satisfactory (60-74) |
Needs Improvement (0-59) |
| Feature Implementation (40 pts) |
Feature works perfectly, well-integrated |
Feature works, minor issues |
Feature partially works |
Feature doesn’t work |
| Code Quality (25 pts) |
Clean, well-integrated, no breaking changes |
Good integration, minor issues |
Basic integration, some issues |
Poor integration, breaking changes |
| Documentation (20 pts) |
Excellent feature description, clear |
Good description |
Basic description |
Poor or missing |
| Creativity & Complexity (15 pts) |
Creative, appropriate complexity |
Good choice, moderate complexity |
Basic feature, simple |
Trivial or inappropriate |
Detailed Breakdown
Feature Implementation (40 points)
Functionality (25 points):
- Feature works as described: 15 points
- No breaking changes to existing code: 10 points
Integration (15 points):
- Well-integrated with existing code: 8 points
- Follows existing code patterns: 7 points
Code Quality (25 points)
Structure (10 points):
- Proper code organization: 5 points
- Maintains existing structure: 5 points
Quality (10 points):
- Clean, readable code: 5 points
- Appropriate complexity: 5 points
Testing (5 points):
- Feature tested: 3 points
- No obvious bugs: 2 points
Documentation (20 points)
Feature Description (15 points):
- Clear description of feature: 5 points
- How to use the feature: 5 points
- Screenshots/demos: 5 points
Code Documentation (5 points):
- Comments where needed: 3 points
- README updated: 2 points
Creativity & Complexity (15 points)
Feature Choice (10 points):
- Appropriate for assignment: 5 points
- Shows understanding: 5 points
Implementation (5 points):
- Creative approach: 3 points
- Appropriate complexity: 2 points
Quality Indicators
Excellent (90-100 points):
- Feature works perfectly
- Well-integrated, no breaking changes
- Excellent documentation
- Creative and appropriate feature
- Screenshots included
Good (75-89 points):
- Feature works with minor issues
- Good integration
- Good documentation
- Appropriate feature choice
- Screenshots included
Satisfactory (60-74 points):
- Feature partially works
- Basic integration
- Basic documentation
- Simple feature
- May be missing screenshots
Needs Improvement (0-59 points):
- Feature doesn’t work
- Poor integration, breaking changes
- Missing documentation
- Trivial or inappropriate feature
- Missing screenshots
Pro-Level Assignments
Total Bonus Points: 50
Rubric
| Assignment |
Points |
Criteria |
| Pro 1: Authentication |
10 |
Basic auth system implemented |
| Pro 2: WebSockets |
10 |
Real-time features working |
| Pro 3: Database |
10 |
Database integration functional |
| Pro 4: Deployment |
10 |
Deployed to production |
| Pro 5: Testing |
10 |
Comprehensive test suite |
Assessment
Each pro assignment:
- Works as described: 5 points
- Code quality: 3 points
- Documentation: 2 points
Bonus points are additive:
- Complete all 5: 50 bonus points
- Complete 3-4: 30-40 bonus points
- Complete 1-2: 10-20 bonus points
Common Mistakes
Assignment 1
- Vague answers: Not providing specific examples
- Missing understanding: Copying answers without comprehension
- Incomplete: Not answering all questions
Assignment 2
- Server not running: Forgetting to start server
- CORS issues: Not handling CORS for local development
- Missing documentation: Not documenting prompts or process
- No screenshot: Forgetting to include working app screenshot
Assignment 3
- Breaking existing code: Modifying code that breaks Assignment 2
- Trivial features: Choosing features that are too simple
- Poor integration: Not following existing code patterns
- Missing documentation: Not describing the new feature
General
- Late submissions: Not submitting on time
- Incomplete work: Not meeting all requirements
- Poor documentation: Missing or unclear README
- No process documentation: Not documenting prompts or workflow
AI-Generated Code Detection
Philosophy
AI-generated code is expected and encouraged. This course teaches students to use AI tools effectively.
What We Look For
✅ Positive Indicators:
- Student documents prompts used
- Student can explain the code
- Student can modify and debug code
- Student shows understanding through README
- Student iterates and improves
❌ Concerning Indicators:
- Code works but student can’t explain it
- No documentation of process
- Can’t modify or debug code
- No understanding shown in README
- No iteration or improvement
Assessment Strategy
Focus on understanding, not originality:
- Review README for prompt documentation
- Check code comments for understanding
- Evaluate debugging process
- Assess ability to modify code
- Review reflection and learning
Red Flags:
- Perfect code but no understanding
- No process documentation
- Can’t answer questions about code
- No iteration or improvement
Document History
| Version |
Date |
Author |
Changes |
| 1.0 |
2025-12-20 |
RepodIn Education Team |
Initial version |
| 1.1 |
2026-01-07 |
RepodIn Education Team |
Updated Assignment 1 rubric for 5 questions (added iteration) |
Next Review Date: 2026-03-20