🤖 How AI Agents Analyze Your Work
This assessment was created using an AI agent (Claude) that analyzed all 7 student repositories in about 30 seconds—a task that would take a human instructor hours to complete with the same level of detail.
What the AI agent did:
- Read through 14 markdown files (7 planning documents + 7 reflections)
- Identified patterns across all submissions
- Categorized poem themes, design choices, and AI tools used
- Analyzed common challenges and successes
- Generated insights about collective learning outcomes
Why this matters for you: Just as you're learning to collaborate with AI for creative tasks, instructors can use AI to provide faster, more comprehensive feedback. This same technology that helped you plan your poetry websites can help analyze patterns across entire classes, identify where students need support, and create personalized learning experiences.
Think of it as having a teaching assistant who can read everyone's work simultaneously and spot trends humans might miss!
Class Overview
Poem Selections & Themes
The class chose a diverse range of public domain poems, showing strong individual creative vision:
Nature & Tranquility (2 students):
- Student A: "Stopping by Woods on a Snowy Evening" - Robert Frost
- Student B: "The Lake Isle of Innisfree" - W.B. Yeats
Introspection & Identity (2 students):
- Student C: "The Soul selects her own Society" - Emily Dickinson
- Student D: "Hope is the thing with feathers" - Emily Dickinson
Power & Conflict (2 students):
- Student E: "The Charge of the Light Brigade" - Alfred, Lord Tennyson
- Student F: "Ozymandias" - Percy Bysshe Shelley
Creativity & Art (1 student):
- Student G: "Art" - Herman Melville
AI Tools & Collaboration
Key Learning Discoveries
✅ What Worked Well
- Learning to write specific, contextual prompts
- Getting excellent HTML structure and accessibility guidance
- Iterative refinement through follow-up questions
- Critical evaluation of AI suggestions
🔍 AI Limitations Discovered
- Generic initial responses requiring refinement
- Bias in poem recommendations (limited diversity)
- Context loss between conversations
- Subjective design choices not always matching intended mood
Technical Planning Patterns
HTML Structure Choices
- 6/7 students chose
<article>for poem container - Mixed approaches for stanzas:
<p>,<section>,<div class="stanza"> - All planned proper heading hierarchy and accessibility features
CSS Design Strategies
- 5 students chose muted/calming color palettes
- Serif fonts preferred for literary feel
- Mobile-first responsive design thinking
- Popular fonts: Merriweather, Georgia, Playfair Display
Implementation Readiness
Confidence Levels:
- 4 students: Highly confident and ready to code
- 3 students: Some uncertainty but feeling prepared
Most Confident About: HTML structure and semantic elements
Areas for Growth: CSS implementation details and responsive fine-tuning
Class Strengths
Outstanding Achievement Areas:
- 🎯 Critical thinking about AI suggestions
- 📚 Strong grasp of semantic HTML principles
- 🎨 Personal creative vision translated to coherent design
- 🤝 Evidence of improved AI collaboration skills
- 📝 Quality documentation of learning process
Moving Forward
This assignment successfully prepared you for the implementation phase. You've learned not just to use AI, but to collaborate with it critically and effectively. The skills you've developed—writing better prompts, evaluating suggestions, and maintaining creative vision—will serve you well in both the upcoming poetry website project and future development work.
Key Takeaway:
AI is a powerful collaborator, but your critical thinking, creativity, and ability to guide it toward your vision are what create meaningful results. Keep questioning, keep iterating, and keep your creative vision at the center of your work!