Computer Science Lesson Plan
Class: 3rd - Lesson: 13 Code.org Ocean Activity - Understanding AI Systems

Purpose: To develop an AI model that classifies sea objects, and to understand machine learning, the importance of accurate data, bias in AI systems, and their social impact.

No. of Classes

One class.

Material Required

Code.org.

Curriculum Content
  • 5.4) Data
  • 7.1) What is AI
    •
    Prior Knowledge

    Students should know:

  • How to identify a piece of rubbish and a fish.

    • Exercise

    Exercise 1


    1. Use data by listening to sounds, viewing pictures and answering questions.

    Exercise 2


    Step 1: Help the AI bot classify the objects it finds in the ocean.

    • Click here to go to the code.org Ocean activity page.
    • Help the AI bot identify whether an object in the ocean is trash or a fish.
    • Help the AI bot identify different sea creatures, including fish.
    • Help the AI bot categorise features such as a fish's mouth, dorsal fin and colour.
    • Observe how biased ideas can lead to biased or prejudiced data.

    Step 2: Learn what happens when incorrect data is given to an AI system, and how this affects future predictions.

    Solutions



    Teacher Instructions
    1. Teachers should explain to the students how to play the game.
    2. Play the videos that appear within the code.org activity as well - do not skip them. They explain how the AI is trained, what training data is, and how bias occurs, and the students need this to understand the activity.
    3. Sign up for a teacher account and keep it open in another tab before using the code.org exercise.
    4. Help students find any problems in their work and fix them until the AI model classifies correctly.
    5. POINTS TO PONDER: Can AI learn only if we explicitly train it with labelled data, or can it learn on its own?
    6. POINTS TO PONDER: What is more important for AI learning - the number of examples, or the variety of examples?