Artificial Intelligence Curriculum for Primary and Secondary Schools
AI in Computer Science in Secondary Schools
Reinforcement Learning
Card 04 – Machine Learning Deck
Reinforcement Learning
Reinforcement learning is a method that allows a program to learn how to make the right decisions through trial and error. It tries different strategies and identifies which ones lead to the best outcome. In this lesson, students first work with a decision tree and then train a program to play the game Hexapawn.
Lesson Overview
Lesson Length
45 minutes
Recommended Age
Children aged 11–15
Tools
Teacher: Projector, presentation.
Students: Computer, laptop, or tablet (except iOS or Android tablets) — one per group, plus worksheets.
Building Blocks
Reinforced learning.
What Are the Students Learning?
Reinforcement learning is a type of machine learning where machines learn through trial and error.
Why Are They Learning This?
To develop analytical thinking and understand decision-making processes in games.
How Do We Know They Have Learned It?
They’ll be able to explain how computers use machine learning algorithms to adjust their strategies.
Bloom's Taxonomy
Understanding: Students understand the decision-making processes
of a machine learning algorithm in a simple game.
Applying: They apply their understanding of the algorithm while playing the game.
Analyzing: They analyze game strategies.
Digital Competence
Communication and Collaboration.
Five Big Ideas
3-A-VI Nature of Learning (Learning from Experience).
