Computational Thinking & Prompt Engineering

Have you ever talked to a computer or AI? To get the best results, you need to ask questions in just the right way! This is called prompt engineering - and it's like learning a new language for talking to computers!

What You'll Learn:

• 💬 How to write clear, specific prompts
• 🧩 How to break big problems into smaller pieces
• 🎨 How to describe what you want in detail
• ✨ How to improve your prompts to get better results

Get ready to become a prompt master! 🚀

A prompt is like giving instructions to a friend - the clearer you are, the better the result!

Good prompts include:

• ✅ Clear subject - What are you asking about?
• ✅ Specific details - Colors, sizes, styles
• ✅ Context - Background or setting
• ✅ Style - How should it look? (cartoon, realistic, etc.)

Example:

The more details you include, the better the AI can understand what you want! 🎯

Big problems can seem scary, but if you break them into smaller pieces, they become much easier! This is called decomposition.

Example: Making a sandwich

1. Get bread
2. Get fillings (cheese, meat, etc.)
3. Put fillings on bread
4. Put top slice on
5. Cut in half

Each step is simple! When writing prompts, think about breaking your request into clear steps or parts.

Try it: Instead of "make a game," try "create a character, add obstacles, add scoring, add controls" - much clearer!

Writing the perfect prompt takes practice! The best way to learn is to compare different prompts and see which ones work better.

Prompt scoring:

• 📊 Specificity - How detailed is it? (More details = better)
• 🎨 Visual elements - Does it describe colors, shapes, styles?
• 📝 Context - Does it explain the setting or background?
• ✨ Style - Does it specify the artistic style?

Use the prompt analyzer to see how your prompts score. Try adding more details and watch your score improve! 📈

Pro tip: Compare two prompts side-by-side to see which one gives better results. This helps you learn what works!