Artificial Intelligence Curriculum for Primary and Secondary Schools
AI in Computer Science in Elementary Schools
Robots at the Cat Exhibition
Learning from Examples
Lesson 05
Learning from Examples
Ju and Pí found themselves at a cat show and were amazed! So many breeds, colors, and sizes! How are they supposed to recognize a cat when each one looks different? To learn how to recognize cats properly, robots need to see a lot of them. Let’s see how well they do – and who they’ll take home from the show.
Lesson Overview
The lesson begins with a story in which the robots Ju and Pí visit a cat show and try to figure out which animals are actually cats. Students reflect on how people recognize objects around them and how computers do the same. The teacher leads a discussion about how machines learn to recognize things based on examples provided by humans – and how the more examples they have, the more accurate their recognition becomes. In a practical activity, students analyze various images and look for common features of cats, learning the importance of having a diverse training dataset. They then discuss how computers can make recognition errors – for example, by confusing a chihuahua with a chocolate muffin. The lesson continues with demonstrations of how AI learns from examples, such as recognizing handwritten numbers or using apps like Quick, Draw! Finally, students reflect on what they’ve learned and identify other examples of where object recognition using AI could be applied, such as in autonomous vehicles or healthcare.
Lesson Overview
Recommended Age, Lesson Length
Children aged 8-11, 45—90 minutes.
Tools
Teacher: Presentation to be shown.
Students: Writing supplies, possibly printed worksheets.
Building Blocks
Supervised learning (learning from examples).
What Are the Students Learning?
Computers can learn to recognize different things based on examples prepared by humans.
Why Are They Learning This?
Understanding the principle of supervised learning is an important piece in the mosaic of machine learning.
How Do We Know They Have Learned It?
In their own words, students explain how computers learn from examples and what kind of examples they need.
Digital Competence
Facilitating Learners' Digital Competence.
Bloom's Taxonomy
Remembering: Students recall and identify key characteristics
of objects.
Understanding: Students compare and sort objects based on set criteria.
Analyzing: Students recognize situations where recognition might go wrong and identify possible sources of errors.
Five Big Ideas
1-B-I Processing (Sensing vs. Perception).
1-C-I Domain Knowledge (Types of Domain Knowledge).
3-A-I Nature of Learning (Humans vs. machines).
