Machine learning for Grade 6 Computer Science is introduced through the relationship between training data, patterns, models, and predictions. This worksheet gives students structured practice with the core ideas behind how a machine learning model uses examples to find patterns and how changing those examples can affect what the model predicts.

From training examples to predictions

Students work with the vocabulary machine learning, training data, model, and pattern using accurate Computer Science terminology. The activities then move beyond definitions by asking students to explain how examples in training data help a model learn patterns over time.

A key focus is the effect of the data used for learning. Students identify ways a model can behave differently when its training data changes and use examples to describe what a machine learning model predicts. This gives students a concrete foundation for discussing AI systems without requiring advanced mathematics or programming concepts that are not part of the resource.

How students show what they know

The worksheet combines multiple-choice questions, true false items, short-answer responses, a dialogue, matching, a cloze passage, a labeled diagram, a reading passage, and an essay. This range allows students to recognise vocabulary, interpret ideas, connect concepts visually, and explain machine learning processes in written responses.

What is included

• Student worksheet covering machine learning, training data, models, patterns, and predictions.
• Separate Teacher Guide PDF with learning objectives, teaching tips, discussion questions, and common mistakes.

Useful across an introductory AI lesson

Teachers can use the worksheet after introducing machine learning vocabulary, during guided practice, or as independent review within an Artificial Intelligence unit. The labeled diagram and reading passage support students who benefit from visual and contextual explanations, while the short-answer and essay tasks provide opportunities to check whether students can explain the relationship between data and model behaviour in their own words.

The resource keeps attention on one important machine learning idea: models learn from examples in training data. By connecting training examples to patterns, changed data, and predictions, students practise the conceptual thinking needed to discuss how machine learning works at an age-appropriate Grade 6 level. The accompanying teacher guide also provides support for instruction, discussion, and addressing common mistakes.