Course Content
Lesson 1: Where is AI in My Life?
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Introduction
Purpose of the Lesson
Learning Outcomes
Key Concepts and Definitions
Theory: How AI Works Around You
Activity – Spot the AI Around You
Conclusion
Quiz
Extension Project – “AI Around My School”
Lesson 2: Can AI Think Like Me?
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Introduction
Purpose of the Lesson
Learning Outcomes
Key Concepts and Definitions
Theory: How Humans and AI Think Differently
Activity – Who Decides Better?
Conclusion
Quiz
Extension Project – “Human + AI Teamwork”
Lesson 3: How Does AI Learn?
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Introduction
Purpose
Learning Outcomes
Key Concepts and Definitions
Theory: How Machine Learning Works
Analogy – AI as a Student
Activity – Train a Teachable Machine
Observation Questions
Conclusion
Quiz
Extension Project – “Teach the Machine Better”
Lesson 4: Fair or Not? (AI Bias and Ethics)
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Introduction
Purpose
Learning Outcomes
Key Concepts and Definitions
Activity – Find the Bias
Why Ethics Matter
Activity – Find the Bias
Conclusion
Quiz
Extension Project – “Fairness Check”
Lesson 5: Build an AI Idea
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Introduction
Purpose
Learning Outcomes
Key Concepts and Definitions
Theory: How AI Can Help Society
Activity – Design an AI App for Good
Conclusion
Quiz
Extension Project – “AI for My Community”
Lesson 6: AI and My Future
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Introduction
Purpose
Learning Outcomes
Key Concepts and Definitions
Theory: How AI is Changing Careers
Activity – Explore AI Careers
Conclusion
Quiz
Extension Project – “My Dream AI Career”
C8: AI Basics – How Machines Learn and Help Us

By the end of this lesson, students will be able to:

  1. Define bias and explain how it appears in AI systems.

  2. Understand the link between data quality and AI fairness.

  3. Recognize that humans are responsible for making AI fair.

  4. Suggest ways to reduce bias in AI through diverse and balanced data.

Reflect on ethical responsibilities in developing and using AI.

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