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Oak ComputingTest · Computing

Bias and accuracy in machine learning

The starter and exit quiz of the lesson “Bias and accuracy in machine learning”, from the unit “Using data science and AI tools effectively and safely” (Year 10 Computing) by Oak National Academy.

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Oak National Academy

12 questions

  1. What do we call the message or instruction you give to a large language model to get a response?
  2. Why is it important to make your prompt specific when using an LLM?
  3. What can happen if your prompt to an LLM is too vague?
  4. Match the keyword to its definition.
  5. Why is it important to check LLM responses for bias?
  6. Why should you critically evaluate the responses from an LLM?
  7. Which statement about machine learning (ML) models is correct?
  8. Put these steps in order for training an ML model fairly.
  9. Why do ML models need both training data and separate test data?
  10. What does it mean if data is “unrepresentative”?
  11. What is one effect of bias in an ML model?
  12. Match the keyword to its definition.

License: OGL

Bias and accuracy in machine learning · Examplary