Artificial Intelligence Unit for KS3 (AI)

This is a complete six-lesson KS3 Computer Science AI unit that covers the scientific concepts behind how AI works, as well as the ethics and risks that must be considered when using it. The unit is ready to teach straight out of the box, with all concepts simplified to make them accessible for students aged 11–14. It provides a programme of study lasting between 6–10 guided learning hours.

The unit consists of six lessons and a student assessment, supported by teacher presentations with embedded videos and accompanying worksheets. All materials can be printed as a booklet or used as individual sheets. The pack also includes a pre-assessment, a student progress checklist, a keywords evidence sheet, a knowledge organiser, and a set of challenge cards to further extend learning. The lessons feature a variety of practical, hands-on activities.

The intuitive structure of the presentations and worksheets eliminates the need for lengthy lesson plans. Each worksheet is designed to run alongside the teacher slides and contains all activities required to reinforce learning.

This tried-and-tested unit is being made available as proposed curriculum reforms aim to strengthen students’ understanding of artificial intelligence. Why wait until the new reform comes in. By which time most students wi ll be using Ai with out have the background knowledge of how it works. Get ahead of the game … and start teaching it now.

This tried-and-tested unit is particularly timely as curriculum reforms aim to enhance students’ understanding of AI. Don’t wait until the changes take effect—by then, many students may already be using AI without understanding how it works or when it’s appropriate to use it. Get ahead and start teaching them the fundamentals of AI today.

**NOTE: **Although the unit briefly covers how to use AI effectively, its core focus is on explaining how AI works at a technical level, enabling students to make informed decisions about when and how to use it.

Lesson titles:

1. Artificial Intelligence
2. Neural Networks
3. .Machine Learning
4. Generative AI
5. Ethics and Risks
6. Assessment (Summative)