KS2 Introduction to Machine Learning Lesson

In this lesson, students are introduced to machine learning by comparing it to how humans learn skills. Students act as the “AI” by sorting labelled alien images into categories, studying the features of each group, and identifying the patterns that define them. During the testing phase, they predict the category of new unseen aliens, helping them understand how machine learning models are trained and tested.

This  lesson is 5/10 in a unit plan that introduces how Artificial Intelligence works with a focus on face data. It incorporates MachineLearningForKids and Face Sensing blocks in Scratch. There are:

• 10 detailed lesson plans includes starter and plenary activities.
• 73 teaching slides.
• Unplugged actitivies include team physical games, system design, class presentations and ethical discussions.
• Digital activites includes interacting with a range of AI, developing a Machine Learning model and programming a game.

Students explore artificial intelligence by learning how face detection works and why it plays such an important role in many digital systems. Across the unit, they investigate how AI uses data to detect faces, respond to facial features, and support tools such as phone security, social media tagging, smart attendance systems, and interactive games. Students also examine the limitations of face detection by considering privacy, fairness, and the ways AI can make mistakes. Through discussion, hands-on activities, and Scratch projects, students build their understanding of machine learning and image recognition while designing, testing, and evaluating their own AI-inspired solutions.

The resources was written to align with the G3 - 5 AI priorities for K-12 curriculum. They would be suitable for a Year 6 or 7 student who is new to learning about how AI works.

Please contact sarah@codeavengers.com if you have any questions about the resource.