Chatbot applications and other LLMs
Lesson details
Learning outcome
I can describe the purpose of LLMs and explain why the output may not be trustworthy.
Key learning points
- LLMs are trained on large amounts of text data.
- The aim of LLMs and chatbot applications is to provide realistic conversations by predicting the next word or phrase.
- There is no guarantee that data used to train LLMs is accurate, unbiased and trustworthy.
- Bias is when the output of an AI model favours some things and deprioritises or excludes others.
Keywords
Language model - an AI system used to produce or complete written text based on patterns identified in training data
Prediction - an estimate of what might happen next based on patterns found in training data
Bias - when something is unfair towards or against something or someone
Trust - confidence that something will work as expected and produce reliable and fair results
Common misconception
Large Language Models (LLMs) understand what they’re saying, like a human does.
LLMs do not understand language or meaning. They generate responses by predicting the most likely next word based on patterns in the data they were trained on, not because they understand the content like a human does.
Teacher tip
Use real-world examples of LLM responses from AI writing tools and ask students to spot possible bias or unfairness. This encourages critical thinking and helps students see that LLMs don’t “understand” content — they generate text based on patterns in data, which may include biased information.
Licence
Lesson video
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Prior knowledge starter quiz
6 Questions
Q1.What is the main purpose of a predictive AI system?
Q2.Which task would a generative AI system be best at?
Q3.What is the term for the information given to an AI system so it can learn?
Q4.Put these actions in order for using predictive AI to forecast exam results:
Q5.Which keyword describes an AI system that can make new things like pictures or music?
Q6.Match each example to the correct keyword:
Assessment exit quiz
6 Questions
Q1.Put these steps in order for how an LLM creates a response:
Q2.What is a Large Language Model (LLM) mainly trained on?
Q3.What is the term for when the output of an AI model unfairly favours or excludes certain groups or ideas?
Q4.What is the main aim of a chatbot using an LLM?
Q5.Match each example to the correct keyword:
Q6.Which statement about the data used to train LLMs is true?
To help you plan your 10 computing lesson on: Chatbot applications and other LLMs, download all teaching resources for free and adapt to suit your pupils' needs...
To help you plan your 10 computing lesson on: Chatbot applications and other LLMs, download all teaching resources for free and adapt to suit your pupils' needs.
The starter quiz will activate and check your pupils' prior knowledge, with versions available both with and without answers in PDF format.
We use learning cycles to break down learning into key concepts or ideas linked to the learning outcome. Each learning cycle features explanations with checks for understanding and practice tasks with feedback. All of this is found in our slide decks, ready for you to download and edit. The practice tasks are also available as printable worksheets and some lessons have additional materials with extra material you might need for teaching the lesson.
The assessment exit quiz will test your pupils' understanding of the key learning points.
Our video is a tool for planning, showing how other teachers might teach the lesson, offering helpful tips, modelled explanations and inspiration for your own delivery in the classroom. Plus, you can set it as homework or revision for pupils and keep their learning on track by sharing an online pupil version of this lesson.
Explore more key stage 4 computing lessons from the Using data science and AI tools effectively and safely unit, dive into the full secondary computing curriculum, or learn more about lesson planning.