Understanding AI
Why not explore the AI glossary?
AI glossary of terms
Updated: 22 Sep 25
Updated: 22 Sep 25
Introduce students aged 11 to 14 to AI and machine learning in a clear and responsible way through this engaging 4-lesson module.
Updated: 13 Jan 26
Updated: 13 Jan 26
Updated: 13 Jan 26
Updated: 13 Jan 26
Updated: 13 Jan 26
Learners will be introduced to the term ‘artificial intelligence’ (AI) and complete activities to describe what AI is, what AI is not, and how AI systems can be used to benefit society. They will be encouraged to analyse the language that is used to describe AI and to use appropriate and technical terms.
In this lesson, learners will learn to describe the difference between data-driven and rule-based approaches to solving problems. They will explore how machine learning systems are created using a data-driven approach, including supervised learning.
Learners will explore how machine learning (ML) models are created with supervised learning. They will build their understanding of how labelled training data is used to train classification models by interacting with Quick, Draw!, an interactive AI tool. Finally, they will examine how confidence scores are used in ML model predictions.
Learners will explore how bias can appear in machine learning models due to the data used to train them. They will create their own machine learning model to classify images of apples and tomatoes, and discover how a limited dataset can lead to biased and inaccurate predictions. Finally, they will investigate two types of bias that can appear in training data.
