Introduction: Bridging the Gap

Welcome! If you have reached this chapter, you already know that the IB Computer Science course isn't just about memorizing definitions—it’s about using those concepts to solve real problems. In Paper 1, you will encounter the case study, a specific real-world scenario issued by the IB.

The secret to scoring high marks is learning how to look at that case study through the "lens" of Theme A: Concepts of computer science. We aren't just talking about computers in general; we are talking about how this specific system in the case study works. In these notes, we will break down how to connect your knowledge of hardware, networks, databases, and machine learning to any scenario the IB throws at you.

The "Theme A" Lens: What are we looking for?

When you read the case study, you should be acting like a systems analyst. You need to identify how the four main topics of Theme A are hidden within the text. For a refresher on how to read the scenario document itself, see the chapter "Reading and analysing the case study scenario".

1. Applying A.1 Computer Fundamentals

This topic is about the "nuts and bolts" of a system. When reading the case study, ask yourself:

  • Hardware: What devices are mentioned? If the case study is about a "Smart City," the "hardware" includes sensors, cameras, and central servers.
  • Software: Is there a specific app or operating system mentioned? Think about whether it is custom-written software or "off-the-shelf."
  • System Behavior: How do the components interact? For example, if a sensor detects motion, what is the input-process-output cycle?

Quick Tip: Don't just say "they use a computer." Be specific! Is it a micro-controller with limited RAM, or a powerful server with multiple CPU cores? The case study will usually give you clues about the constraints of the system.

2. Applying A.2 Networks

Almost every modern case study involves communication. To apply A.2 concepts, look for the "connections":

  • Type of Network: Are the devices connected via a local LAN (like inside a single office) or a WAN (across a whole country)?
  • Transmission: Are they using wires (fiber optics) or wireless (Wi-Fi, 5G, Satellite)? Why did they choose one over the other? (e.g., "They used satellite because the farm is in a remote area.")
  • Security: How is the data protected as it travels? Mentioning encryption or firewalls in the context of the case study's specific data (like medical records or banking info) shows deep understanding.

Analogy: Think of the network as the "nervous system" of the case study scenario. How does the "brain" (the server) tell the "fingers" (the remote devices) what to do?

3. Applying A.3 Databases

If the case study mentions "storing records," "searching for users," or "keeping track of inventory," you are in A.3 Databases territory.

  • Data Organization: How is the information structured? You might need to suggest why a relational database is better for the scenario than a simple flat file.
  • Querying: Think about what the users need to find. If the case study is about a library, the "query" might be \(Search \space by \space ISBN\).
  • Privacy and Ethics: This is huge in the new syllabus. Who owns the data in the case study? Is it stored securely?

Did you know? Under the 2025 syllabus, databases are now "core" content. This means you must be able to discuss them in relation to the case study, whether you are an SL or HL student!

4. Applying A.4 Machine Learning (ML)

This is the newest part of the curriculum. If the case study mentions "prediction," "automated decisions," or "pattern recognition," look for ML opportunities.

  • The Training Data: Where does the system get its data to learn? If it's a self-driving car case study, the data comes from cameras and sensors.
  • The Model: Is the system making a classification (e.g., "Is this a weed or a crop?") or a regression (e.g., "What will the temperature be tomorrow?")?
  • HL Perspective: HL students need to look much deeper into the ethics of the ML model. Is the data biased? What happens if the machine makes a mistake in the case study scenario?

Step-by-Step: Connecting Concepts to the Text

Don't worry if this seems tricky at first. Follow these three steps when practicing with a case study:

  1. Highlight Keywords: Read a paragraph of the case study. Highlight any word related to "storing," "sending," "calculating," or "learning."
  2. Label the Topic: Next to the highlight, write A.1, A.2, A.3, or A.4.
  3. Ask "So What?": Ask why that concept matters to the people in the story. "They are using a WAN (A.2). So what? This means they need to worry about latency and data encryption over long distances."
Common Mistake to Avoid:

The "Generic Answer": Avoid giving definitions without mentioning the case study.
Wrong: "A database is an organized collection of structured information."
Right: "The database in this scenario allows the hospital to link patient IDs to their medical history efficiently."

Summary and Key Takeaways

Key Takeaway 1: Paper 1 questions on the case study require you to apply Theme A concepts (Fundamentals, Networks, Databases, Machine Learning) to a specific, unfamiliar situation.

Key Takeaway 2: Focus on constraints. If the case study mentions a remote location, connect it to Network (A.2) challenges. If it mentions high-speed processing, connect it to CPU/Hardware (A.1) requirements.

Key Takeaway 3: Always link your technical knowledge back to the stakeholders (the people) in the case study. How does the technology help or hurt them?

Next Step: Move on to "Paper 1 question skills: computing systems" to learn how to structure your written answers based on these connections!