Explain AI data, rules, reasoning and learning
Describe how input data and rules support decisions and how systems may adapt from data.
This sequence follows Cambridge IGCSE Computer Science 0478, 2026–2028 syllabus Version 6. It covers subject content sections 6.1–6.3 only. The separately published 2029–2031 syllabus is not mapped here. Practice is original, self-checked and does not award an official Cambridge grade. Full timed papers and human subject-teacher review remain outstanding.
Before you begin
- No programming language is required. Be comfortable with place value and multiplication; each lesson introduces the computer-science notation it uses.
Work on paper. Try each question before revealing help, and explain why your method works.
Quick readiness check
What does a rule tell an AI system?
What you will learn
- Identify data and rules in an AI system
- Explain reasoning as applying information to a decision
- Describe learning and adaptation
AI behaviour depends on information and methods
An AI system can use a collection of data and rules for using that data. It applies those rules or patterns to the input, reasons about possible results and produces a response.
Apply and check the rule
Some AI can learn and adapt: a program may change its processes or data based on examples or feedback. Learning quality depends on the data and rules provided. A system that adapts can still make errors, so its outputs need testing and suitable human oversight.
Pause and explain
Which is evidence of learning rather than applying one unchanged rule?
Worked example
An AI system classifies a support message using example messages and a rule for matching words. Identify data, rule and output.
Show the worked solution
- Example messages are the data.
- The word-matching instruction is a rule.
- The system applies it and returns a category.
Answer Data: example messages; rule: match specified words; output: a message category.
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Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.
In an AI system that recommends books from past ratings, identify a data source, a rule or pattern, and one output.
Give me a hint
Trace example information through a decision.
Compare my reasoning
- Past ratings and book descriptions are input data.
- A pattern links user preferences to book features.
- The output is a ranked list of suggestions.
Data: ratings and descriptions; pattern: matching preferences; output: ranked book recommendations.
Look for these in your work
- Data identified
- Pattern stated
- Output
A system receives corrected labels from a teacher and adjusts its future classifications. Which AI characteristic is shown?
Give me a hint
Look for a change after feedback.
Compare my reasoning
- The system receives examples with corrected labels.
- It changes its process or data based on those examples.
- This is learning and adaptation.
Learning and adaptation: the system changes how it classifies after feedback.
Look for these in your work
- Feedback source
- Change
- Characteristic
An AI classifier performs well on familiar examples but poorly on new cases. Explain one cause and one way to assess improvement.
Give me a hint
Consider the range and quality of training data.
Compare my reasoning
- The examples may not represent new cases.
- The rules or learned pattern may overfit familiar data.
- Test with representative unseen examples and compare results before changing the data or process.
Limited or biased examples can lead to weak generalisation. Evaluate it on representative unseen cases, then improve the data or method and retest.
Look for these in your work
- Cause
- Generalisation issue
- Evaluation
Common mistakes
- Saying AI reasoning guarantees a correct result
- Confusing a collection of data with the rules applied to it
What can you explain now?
What can machine learning do according to the syllabus?
Compare with the explanation
Automatically adapt its processes or data
Learning changes how a program operates or what data it uses.
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Make it stick
What roles do data, rules, reasoning and learning play in an AI system?
If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.