About HAP's Learning Lab
🔬 What I Learned
Computational thinking is a way of approaching problems that goes beyond just writing correct code. It's about breaking things down, recognizing patterns, focusing on what matters, and describing steps clearly.
Prof. Teeters taught me that these skills apply everywhere—not just in programming.
🎯 How I Practiced
I built the Secret Number Game from the ground up—first describing behavior in plain language, then writing pseudocode, then finding and fixing a hidden bug through tracing.
Then I practiced real developer workflows by contributing to a live project called Magic Quotes.
🎨 My Philosophy
Mistakes are data, not failures. Every bug I found taught me something. Every time I got confused, I discovered a gap in my understanding.
I share my mistakes openly because that's how we actually learn.
🤔 My Advice
Take your time at each station. Don't rush to the code—the thinking comes first. When something doesn't make sense, trace through it step by step.
And remember: if you can't explain it in plain words, you're not ready to code it.
Learning Stations
The Learning Journey
Stations 1-4: Computational Thinking Foundations
Through the Secret Number Game, you'll learn to think logically, communicate your logic, trace and debug, and recognize the Four Pillars of Computational Thinking. No code required—just clear thinking.
Stations 5-6: Real-World Practice
You'll shift from concepts to practice by working with Magic Quotes—a real, deployed project. Fork it, clone it, contribute to it, and learn to use AI as a responsible assistant. By the end, you'll have opened your first pull request.
🟠 HAP's Promise:
I won't pretend I know everything. I'm still learning too. What I can promise is that I'll share exactly what helped me—the mistakes, the breakthroughs, the moments when things finally clicked.
Prof. Teeters always says: "Understanding how to learn matters more than memorizing what to type." Let's figure this out together.