Using LLMs strategically for learning (13-16)

Across five lessons, learners explore how large language models work, how to write strong prompts, and how to evaluate the reliability of AI-generated outputs. Co-developed by the Raspberry Pi Foundation and Google DeepMind.

Why not explore the AI glossary?

AI glossary of terms

Updated: 8 Jul 24

Lessons

Unit overview

Updated: 24 Sep 26

Learning graph

Updated: 22 Aug 26

Lesson 1: What are large language models?

Learners will explore what large language models (LLMs) are and how they generate output through predictions.

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Lesson 2: Learning with LLMs

Learners will explore the different types of learning interactions called ‘feedback types’: telling, guiding and challenging.

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Lesson 3: Writing prompts

Learners explore how to prompt a large language model (LLM) to get clearer, more useful LLM responses.

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Lesson 4: Evaluating prompts

Learners will use a large language model (LLM) to write and refine their prompts, compare strong and weak examples, and learn to evaluate LLM outputs by checking for accuracy, bias, and usefulness for their learning.

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Lesson 5: My responsible use of LLMs

Learners will reflect on the risks of over-relying on LLMs and how this may impact their long-term learning and skill development.

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