EZ Template · Learning Resources

EZ Template Assistant

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The AI chat is disabled. This page does not accept or send chat messages. Use the debugging steps and EZ Template documentation below to continue learning.

🗺️ Flowchart — Prepare a useful debugging question

Try these self-debugging steps first. Bring specific symptoms and the relevant code when asking a teammate or mentor for help.

flowchart TD
    Start([Stuck on something
EZ-Template related]) --> Q1{Is the error
a compile error?}
    Q1 -->|"Yes"| Compile[Read the FULL error text
often the first line is enough.
Search EZ-Template docs.]
    Q1 -->|"No, runtime issue"| Q2{Robot behavior wrong?}
    Q2 -->|"Wrong distance/angle"| Tune[Try PID tuning workflow first
see ez-pid-tuning]
    Q2 -->|"Sensor not reading"| Sensor[Try test program:
read sensor in opcontrol
print to LCD]
    Q2 -->|"Other behavioral"| Ask[Now have specifics ready:
1. What you tried
2. What happened instead
3. The relevant code]
    Compile --> Q3{Fixed?}
    Tune --> Q3
    Sensor --> Q3
    Q3 -->|"Yes"| Done([Issue resolved])
    Q3 -->|"No"| Ask
    Ask --> Asst[Ask a teammate or mentor
with specifics]

    style Start fill:#1e293b,stroke:#22d3ee,stroke-width:2px,color:#e2e8f0
    style Done fill:#1e293b,stroke:#22c55e,stroke-width:2px,color:#e2e8f0
    style Q1 fill:#fbbf24,color:#0f172a,stroke:#fbbf24
    style Q2 fill:#fbbf24,color:#0f172a,stroke:#fbbf24
    style Q3 fill:#fbbf24,color:#0f172a,stroke:#fbbf24

Learning with outside code

AI may teach programming or provide outside starting-point code. Students still do the work: UNDERSTAND → ADAPT → TEST → CREDIT → EXPLAIN. A generated program is not finished team work. Credit outside code in the program itself; libraries may remain unchanged when students understand, explain, and credit their use.

Students write their own notebook. See the student ownership guidance and the GRSF Student-Centered Policy.

📖

OFFICIAL EZ TEMPLATE DOCUMENTATION

For the full API reference, tutorials, and example project

📚 EZ Template Docs → 🐙 Example Project →

⚙ STEM Highlight Computer Science: Large Language Models as Engineering Tools

AI coding assistants predict outputs from context. They can suggest code that looks plausible but uses the wrong API or does not match your hardware. Study the relevant documentation, predict the behavior, and test changes on your actual robot.

Reflection prompt: If your team used outside code, what did you adapt, what did testing show, and how did you credit the source? Explain your actual experience.

An outside example includes a chassis constructor. What is part of adapting and testing it?

⬛ Upload immediately — AI-generated config code is correct by design

⬛ Verify every port number matches your physical wiring and test drive direction before running any autonomous

⬛ Ask the assistant to verify its own output

📝

Notebook entry tip: Build & Program — Orange slide — Document significant AI-assisted coding decisions in your programming log: what you asked, what it generated, what you changed and verified, and what the final code does. Students write this record themselves. Credit outside code where it appears in the program and include applicable sources in the Credit Summary.