Patterns and Classification
Humans are great at spotting patterns; computers can learn to spot patterns too, but they need lots of examples; sorting and classification activities as the basis of machine learning
Keep a record of your learning
Save photos, notes, and attendance. Export a proof packet for compliance or portfolio reviews.
Learning resources
Reviewed external links that reinforce this concept. They do not replace Gakuva’s teaching approach.
AI for Oceans
Train and test a classifier on labeled examples—direct practice with patterns and classification (and what happens with new items).
Proof: Save a screenshot of training labels and a test result, plus a parent note of one correct and one confused classification.
Teachable Machine · Image
Adult-guided tool: create two or more image classes, train a quick model, and test new examples. Works best with a webcam and supervision.
Proof: Save a screenshot of at least two classes with training samples and one live test prediction.
Explore the learning path
1 before · 3 after
This concept
Check understanding
- Sort a set of items into categories and explain the rules they used
- Explain that computers learn patterns by looking at many examples
- Describe why a computer needs more examples than a human to learn the same pattern
“If you showed your child pictures of cats and dogs, could they explain how a computer could learn to tell them apart — and why it would need many more pictures than a person would?”
Curriculum record
- Type
- Conceptual
- Subject
- Computing
- Domain
- Artificial Intelligence
- Age range
- Ages 7–9