Ages 9-12

AI Builders

Code, Create & Solve Real Problems

Kids use block-based coding to build chatbots, train machine learning models, and tackle ethical debates about AI's role in the world. Real tools, real projects, real skills.

6 Modules
36+ Activities
CSTA Aligned
AI Builders — kids ages 9 to 12 coding and creating with AI
my_chatbot.py
import chatbot

bot = chatbot.create("Wizi")

if bot.hears("hello"):
    bot.say("Hi there! 👋")
elif bot.hears("joke"):
    bot.say(get_joke())
else:
    bot.learn(message)

What Your Child Will Build

AI Builders module icons
💬

Chatbots

Build conversational AI using Scratch and IBM Machine Learning for Kids platform.

🧠

ML Models

Train image classifiers and text recognizers using Google Teachable Machine.

📊

Data Thinking

Understand how AI learns from data by collecting, labeling, and analyzing datasets.

⚖️

AI Ethics

Explore bias, fairness, and privacy through role-play scenarios and structured debates.

🎮

Game AI

Create AI-powered games with smart NPCs and adaptive difficulty levels.

🔬

Scientific Method

Apply hypothesis testing to AI experiments — predict, test, observe, conclude.

6 Builder Modules

Each module includes guided coding activities, collaborative projects, teacher lesson plans, and assessment rubrics.

01

What Is Artificial Intelligence?

Foundations

A deeper dive into AI concepts. Kids learn about narrow vs. general AI, how machines learn from data, and map out AI systems they use every day.

Activities

  • AI Timeline — history of artificial intelligence
  • Narrow vs. General AI sorting exercise
  • "AI Detectives" — find AI in apps & games
  • Build an AI Knowledge Map
  • Group debate: "Will AI replace teachers?"

Tools & Materials

  • AI Timeline poster (printable)
  • Knowledge map template
  • Debate prompt cards
  • Assessment worksheet
Module Project

"AI in Our World" Presentation — Teams research and present how AI is used in one industry (healthcare, gaming, sports, etc.)

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02

How Machines Learn

Machine Learning

Kids discover supervised learning by training their own image classifiers. They collect data, label it, train models, and test their accuracy.

Activities

  • Google Teachable Machine — train an image model
  • "Feed the AI" — understanding training data
  • Accuracy experiment: more data vs. less data
  • Build a rock-paper-scissors AI
  • Reflection: "What makes a good dataset?"

Tools & Materials

  • Google Teachable Machine (web)
  • Data collection worksheet
  • Accuracy tracker template
  • Teacher lesson plan
Module Project

"Trash Sorter AI" — Kids train a model to classify recyclables vs. trash using photos they take themselves.

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03

Build Your Own Chatbot

NLP & Coding

Using Scratch and IBM ML for Kids, students build their first conversational AI — a chatbot that understands text and responds intelligently.

Activities

  • Introduction to NLP concepts (simplified)
  • Set up IBM ML for Kids workspace
  • Train a text classifier with example phrases
  • Build chatbot logic in Scratch
  • Test & improve: make the bot smarter

Tools & Materials

  • IBM Machine Learning for Kids
  • Scratch (web)
  • Chatbot planning worksheet
  • Testing checklist
Module Project

"Homework Helper Bot" — Kids build a chatbot that answers questions about a subject they choose (science, math, history).

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04

AI Can See & Recognize

Computer Vision

Students explore computer vision in depth — building image classifiers, understanding how facial recognition works, and creating vision-powered Scratch projects.

Activities

  • How pixels become patterns (image data)
  • Train a pet classifier with Teachable Machine
  • Build a "magic wand" controller with webcam
  • Face filter experiment (how Snapchat works)
  • Discussion: "Should AI recognize faces?"

Tools & Materials

  • Google Teachable Machine
  • Scratch + ML extension
  • Webcam required
  • Ethics discussion guide
Module Project

"Emoji Controller" — Kids build a Scratch game controlled by facial expressions detected through their webcam.

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05

Is AI Always Fair?

Ethics & Bias

A deep dive into AI ethics. Kids explore real cases of AI bias, discuss privacy concerns, and role-play as AI policymakers to create their own "AI Bill of Rights."

Activities

  • Case study: biased AI in real life
  • "Biased Bot" simulation exercise
  • Privacy audit: what data do apps collect?
  • Role-play: "AI Policymakers"
  • Write your "AI Bill of Rights"

Tools & Materials

  • Case study handouts
  • Bias simulation cards
  • Privacy audit worksheet
  • Bill of Rights template
Module Project

"Fair AI Poster Campaign" — Teams create awareness posters about AI fairness and present them to the class.

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06

Your AI Future

Career & Capstone

Kids explore AI careers, take a career quiz, and complete a capstone project that combines everything they've learned into one showcase-worthy creation.

Activities

  • AI Career Explorer quiz
  • "A Day in the Life" of an AI professional
  • Capstone project brainstorming & planning
  • Build & test the capstone project
  • Present at the AI Builders Showcase

Tools & Materials

  • Career quiz worksheet
  • Project planning template
  • Presentation rubric
  • Printable certificate
Capstone Project

"My AI Solution" — Kids identify a real problem and build an AI-powered solution using all the tools they've learned.

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Ready to Start Building
with AI?

The first 2 modules are completely free — no credit card required!