🤖 AI in Education

How AI Works & The Role of Machine Learning

Big Idea:
AI algorithms reflect and distort human patterns in educational data.

Essential Question:
How do machine learning algorithms mirror human patterns—and where do they distort them?

🔍 Today’s Learning Objectives

• Explain core machine learning concepts
• Analyze how AI systems learn from educational data
• Identify how AI can reflect or distort patterns
• Evaluate the impact of algorithm design in schools

⏳ Today’s Agenda

1. Opening Pattern Challenge
2. Machine Learning Lecture + Demos
3. Hands-On Zog Activities
4. ML Application Design Project
5. Algorithm Analysis (Formative Check)
6. Reflection & Preview

💡 Intro to Machine Learning

Key Terms:

• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning

ML ≠ Magic
It's pattern recognition — with flaws.

🔄 How Machines Learn from Data

Supervised:
Labeled examples → prediction

Unsupervised:
No labels → groupings & patterns

Reinforcement:
Trial and error → rewards

🔬 In Education, ML is Used To:

• Grade writing
• Recommend practice problems
• Detect disengagement
• Personalize learning paths

⚠️ But... patterns ≠ understanding

🔄 Activity Time: Zog Learning Simulation

Three Paths:

• 🟩 Supervised: Zogling Classification
• 🟨 Unsupervised: Alien Creature Clustering

Goal: Teach Zog using examples — then reflect
📄 Use the worksheet to document your process