CS · Book pp. 481–492
Case study
Each exam session has its own case study, on technology beyond the syllabus. You research it for months, and then write about it in Paper 1.
What it is
The IB publishes a booklet with a scenario, the “challenges faced”, and a terminology list. Your teacher will give you the one for your exam session. It changes, so never revise from an old one.
| SL | HL | |
|---|---|---|
| Teaching time | 15 hours | 30 hours |
| Share of Paper 1 | 12 of 50 marks | 24 of 80 marks |
| Essay marks | 6 | 12 |
| “Challenges faced” in the booklet | 2 | 4 |
| Time for the essay | About 18 minutes | About 36 minutes |
The short questions test the terms and main ideas, with command terms such as define, outline and describe. The essay tests how far your research goes.
How to research
| Step | What to do |
|---|---|
| 1. Read | Highlight key points, and define every word in the terminology list. Quiz each other. |
| 2. Learn the technology | Find lectures and articles until you can explain how it works. No code is examined, but you need real technical understanding. |
| 3. Reread the scenario | What is it really about? What are the big issues? What still confuses you? |
| 4. Attack each challenge | Why is it hard here? What happens if it is not solved? What solutions exist? |
| 5. Look beyond the booklet | Find real-world examples for each challenge, and add them to a revision document. |
| 6. Practise | Guess the questions, write timed essays, and mark each other’s against the bands. |
Good sources
- Research papers: arXiv is free, but its papers are not peer-reviewed, so check them.
- Talks by engineers who build the technology.
- Visits and experts: ask your teacher about a company visit, or a university researcher.
- Real events: compare how the technology has been used over time.
- Each other: teach a challenge to your class, and take questions.
⚠️ Using AI to research
An AI tool can give you a starting list of issues, but it can also invent facts and papers. Check every claim against a real source, and write in your own words.
The essay
Here are the bands, in our own summary. Check your school’s copy of the markscheme for the exact wording.
| Band | SL | HL | Looks like |
|---|---|---|---|
| Basic | 1–2 | 1–3 | Little more than a list, with no real use of terms, the case study or research |
| Adequate | 3–4 | 4–6 | Descriptive, with limited terminology, analysis and research |
| Competent | 5–6 | 7–9 | Sound understanding, terms used correctly in places, with some analysis and research |
| Proficient | 10–12 | Detailed understanding, precise terms throughout, balanced analysis, linked conclusions and extensive research |
The SL top band is Competent, so its 5–6 marks already expect analysis, research and a conclusion.
A shape that works
- Plan for five minutes. Underline the command term, and pick your main points.
- Open by stating your position, using the scenario’s own terms.
- Build each paragraph from one claim: the technology behind it, a real example, then its limits.
- Weigh the two sides against each other, not one after the other.
- Conclude by answering the question, and saying what your answer depends on.
⚠️ Common mistakes
- Retelling the booklet.
- Using terms loosely. Examiners can tell.
- Inventing a citation.
- Arguing one side only.
- Writing all you know, and ignoring the command term.
- Trusting unofficial online forums without checking.
Past case studies
Examiners’ reports repeat the same lessons year after year. These come from the previous syllabus, and are summarized here in our own words.
| Topic | Years | Technology | What examiners noticed |
|---|---|---|---|
| Blockchain | 2020–21 | Digital ledgers, proof of work, Merkle trees | Good answers stayed on security and scalability. Many drifted into economics, and few knew sharding or layer 2. |
| Genetic algorithms | 2022 | Selection, crossover, mutation, convergence | Most answers described rather than evaluated, and few showed how the settings affect each other. |
| Recommendation systems | 2023 | Filtering, k-NN, matrix factorization | Many wrote about generic film apps, not the scenario. Few offered fixes for cold start or popularity bias. |
| Rescue robots | 2024 | Computer vision, vSLAM, pose estimation | Many wrote mostly about ethics, with little technical depth. The best weighed factors such as sensors and battery life. |
What do all four have in common?
Students who describe, stay generic or drift off the computer science do badly. Students who evaluate, tie their points to the scenario and cite real research do well.
Quick quiz
Practice
These are written for this site. The essay uses a made-up scenario, and is here for practising the structure. Open the mark points after you have written it.
-
Outline why repeating the case study booklet scores poorly. [2]
Mark points
- Examiners already know the booklet [1].
- Marks reward your research and analysis beyond it [1].
-
SL practice (our own scenario): a city plans cameras that adjust traffic lights using machine learning. To what extent will this reduce congestion? [6]
Mark points
- Explains how the system works, with correct terms [1].
- Gives a specific benefit, such as adapting to live flow [1].
- Gives a specific limit, such as poor data at night or in rain [1].
- Links to the scenario, not traffic in general [1].
- Uses a real example from research [1].
- Reaches a conclusion that follows from the points made [1].