Artificial intelligence curriculum for primary and secondary schools
AI in Informatics at the 1st level
Robot adventures in maze
Learning from Experience
Lessons 06
Learning from experience
The cat is lost and so Ju and Pi embark on an adventurous journey to find her! They discover a vast labyrinth of corridors under the city and find out where all the socks are disappearing to. But how to best navigate the maze? Is it better to use the left-hand rule or bread crumbs? But one thing is certain - robots, like humans, don't just learn from examples, but also from experience.
How the lesson works
The lesson begins with a story in which the robots Ju and Pi go into an underground maze in search of the lost cat Pussycat. The children consider how the robots might find their way out, and the teacher leads a discussion about different strategies they might use - for example, the left-hand rule, backtracking or path marking. This is followed by a hands-on activity where pupils work through the maze on the worksheet on their own, collecting socks and trying to avoid sock mice. During this activity they become aware of the principles of learning from experience (trial and error). The teacher then explains that artificial intelligence learns in a similar way - by repeating the task, receiving feedback and refining the strategy. Students watch a video in which AI agents gradually refine their running, and discuss how machines learn by getting rewards for correct actions. The lesson ends with a reflection where children share their strategies, discussing how robots can apply what they have learned to new situations. If there is time left over, they try the game Hexapawn, which illustrates the principle of learning from experience.
Information about lessons
Subsidies and years
45-90 minutes, grades 3-5 Elementary school
Aids
Teacher: Projection equipment and slides to show
Students: Writing materials, worksheets
Building stones
Machine learning from experience (reinforcement learning)
What pupils learn
Machines, like people, can learn from experience. They use trial and and error to do this, where they find the best solution for a given task through repeated testing.
Why is it taught
Understanding the principle of reinforcement learning is an important piece in the machine learning mosaic.
How do we know if they've learned
In their own words, they will describe the specific strategy that led them to success in a given problem.
Outputs of the RVP
Computer Science:
Algorithmization and Programming:
I-5-2-02 describe a simple problem, design and describe the steps of its solution
Digital competences
Contribution and development - understands the importance of digital technologies for human society, learns about new technologies, critically evaluates their benefits and reflects on the risks of their use.
Digital competences
Application: Students apply maze traversal strategies and trial and error to solve a problem.
Analysis: They analyze the success of different strategies and identify reasons for their effectiveness or ineffectiveness.
Evaluation: They evaluate the advantages and disadvantages of the strategies used and reflect on lessons learned.
Five Big Ideas
3-A-I people vs. machines
3-A-VI learning from experience
