Netherlands VWO 6 (eindexamenjaar) Computer Science
Chapters: 14
1. Architecture
Decomposition · Security (technical)
- Computer Architecture – Computer architecture is the design of how a computer's parts work together. Most computers follow the von Neumann model: a CPU and one main memory that stores both the program and its data, joined by the address, data and control buses. The CPU repeats the fetch-decode-execute cycle using special registers (PC, MAR, MDR, CIR, ACC), a control unit and an ALU. Speed depends on clock speed, number of cores and cache size. Instructions are machine code (binary); assembly gives them short names. Designs vary: Harvard (separate memories), RISC vs CISC, and small embedded systems.
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
2. Interaction
Usability · Social aspects · Privacy · Security (socio-technical)
- UI and UX Design: Making Screens Easy and Pleasant to Use – Interface design is planning the screens people use on phones, computers, ATMs and machines. UI (user interface) is what you see and touch: buttons, icons, text, colours and layout. UX (user experience) is how the whole task feels: quick or slow, clear or confusing. Good interfaces put important things first (hierarchy), keep buttons big enough to tap (about 9 mm or 48 px), use strong colour contrast, stay consistent, give feedback after every action and need few steps. Designers study users, draw wireframes, build clickable prototypes and test them with real people, then improve.
- Data Privacy: Who Gets Your Data and How to Protect It – Personal data is any information that can point to you. Apps and websites collect it all the time. Privacy means you control who sees it and how it is used. Fair rules say data must be used for a clear purpose, kept small, kept safe and deleted when done. You have rights over your data, and simple habits keep you safe.
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
3. Elective theme: Algorithms, computability and logic
Complexity of algorithms · Computability · Logic
- Computational Complexity: Easy, Hard and Impossible Problems – Complexity measures how the number of steps grows as the input size n grows. Polynomial algorithms (n, n², n³) are tractable; exponential (2ⁿ) and factorial (n!) ones become hopeless very fast, so such problems are intractable. Some problems are easy to check but hard to solve (NP). Some, like the halting problem, cannot be solved by any algorithm at all.
- Computability: Turing Machines and the Limits of Computing – A Turing machine is a simple model of any computer: an endless tape of cells, a head that reads and writes one cell at a time, a finite set of states and a table of transition rules. Anything an algorithm can compute, a Turing machine can compute (Church–Turing thesis). A universal Turing machine reads another machine's rules from its tape and runs it. Some problems, like the halting problem, can never be solved by any algorithm: they are non-computable (undecidable).
- Propositional Logic: From Statements to Valid Arguments – Propositional logic studies statements that are either true or false and the words that join them: not (¬), and (∧), or (∨), if…then (→) and if and only if (↔). A truth table lists every possible combination of truth values. An argument is valid when no row makes all premises true and the conclusion false. Valid forms such as modus ponens and modus tollens become inference rules for natural deduction.
4. Elective theme: Databases
Information modelling · Database paradigms · Linked data
- Relational Databases: Tables, Rows, Columns and Keys – Keeping data in many separate files leads to repeated data, mismatched copies and hard searching, so we use a database managed by a DBMS. In the relational model data sits in tables called relations. A column is an attribute, a row is a tuple, and the set of allowed values for a column is its domain. The number of columns is the degree; the number of rows is the cardinality. A candidate key is any column (or set) that can identify every row uniquely; the one chosen is the primary key and the others are alternate keys. A foreign key is a column in one table that refers to the primary key of another table, linking them.
- Database Concepts: DBMS, Relations and Keys – Keeping data in separate files causes duplication, inconsistency and poor security. A database stores related data in one organised place, and a DBMS (like MySQL) is the software that manages it. In the relational model, data is kept in tables (relations) made of columns (attributes) and rows (tuples); a domain is the set of allowed values of a column. A candidate key uniquely identifies each row; one is chosen as the primary key and the others are alternate keys.
5. Elective theme: Cognitive computing
Intelligent behaviour · Features of cognitive computing · Applying cognitive computing
- Artificial Intelligence: How Machines Learn to Think – Artificial intelligence (AI) is the skill of a computer system to do tasks that normally need human thinking: seeing, understanding speech, deciding and learning. An AI system is an agent that senses, thinks and acts. Old AI followed rules written by people. Modern AI mostly uses machine learning: it finds its own rule from many labelled examples (data). Neural networks are layers of simple units whose link strengths (weights) change during training. AI is used in maps, translation, health, farming and games. It can be wrong or unfair when its data is one-sided (bias), so people must check it, protect privacy and stay responsible.
- Machine Learning – Machine learning (ML) is a way for computers to learn a rule from examples instead of being told the rule. We give data made of features (inputs) and, in supervised learning, labels (answers). The machine fits a model: regression predicts a number, a decision tree asks yes/no questions to pick a class, and k-means clustering groups unlabelled data. We train on most of the data, test on data it never saw, and measure accuracy or error. A model that only memorises (overfits) fails on new data.
6. Elective theme: Programming paradigms
Alternative paradigm · Choosing a paradigm
- Programming Paradigms: Imperative, Functional and Object Style – A programming paradigm is a style of thinking about how to build a program. Imperative programs give ordered commands that change variables. Functional programs pass data through functions and change nothing in place. Object-oriented programs are made of objects that keep their own data and send messages. Declarative programs (like SQL) state what is wanted, not how. To choose, weigh the problem, the team and the tools.
7. Elective theme: Computer architecture
Boolean algebra · Digital circuits · Machine language · Variation in architecture
- Boolean Logic – Boolean logic works with only two values: 1 (true) and 0 (false). Logic gates act on them: NOT flips a value; AND gives 1 only if all inputs are 1; OR gives 1 if any input is 1; NAND and NOR are the opposites of AND and OR; XOR gives 1 when inputs differ. A truth table lists the output for every input combination (2ⁿ rows for n inputs). De Morgan's laws: (A·B)' = A' + B' and (A + B)' = A'·B'. Gates joined together form logic circuits that match Boolean expressions.
- Computer Architecture – Computer architecture is the design of how a computer's parts work together. Most computers follow the von Neumann model: a CPU and one main memory that stores both the program and its data, joined by the address, data and control buses. The CPU repeats the fetch-decode-execute cycle using special registers (PC, MAR, MDR, CIR, ACC), a control unit and an ALU. Speed depends on clock speed, number of cores and cache size. Instructions are machine code (binary); assembly gives them short names. Designs vary: Harvard (separate memories), RISC vs CISC, and small embedded systems.
8. Elective theme: Networks
Network communication · Internet · Distribution · Network security
- How Networks Grew and How Data Travels – A computer network is a group of connected devices that share data. Networking began with ARPANET (1969), grew into NSFNET (1980s) for universities, and joined with other networks to become the Internet, a network of networks. Every data communication has five parts: sender, receiver, message, communication media and protocol. Bandwidth is the range of frequencies a channel can carry (in Hz); data rate is how many bits travel per second (bps). Every device on a network has an IP address. Data can move by circuit switching (a fixed path is booked first) or packet switching (data is cut into packets that travel on their own).
- Distributed Systems: Sharing Work and Data in a Network – A distributed system is many computers in a network working together as one service. They share the work (many servers, a load balancer) and the data (copies or pieces on different machines). This makes a service faster and able to survive a failure, but needs care to keep the copies in step.
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
9. Elective theme: Physical computing
Sensors and actuators · Developing physical computing systems
- Physical Computing: Making Code Sense and Move – Physical computing joins code to the real world. Sensors measure something (light, temperature, distance, button presses) and turn it into a number. A microcontroller runs a program that decides what to do with that number. Actuators (LEDs, buzzers, motors, screens) act on the world. This input–process–output cycle runs again and again in a loop. Using thresholds, conditions and feedback, we build night lights, smart plant waterers, wearables and interactive art.
10. Elective theme: Security
Risk analysis · Measures
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
11. Elective theme: Usability
User interfaces · User research · Interface design
- UI and UX Design: Making Screens Easy and Pleasant to Use – Interface design is planning the screens people use on phones, computers, ATMs and machines. UI (user interface) is what you see and touch: buttons, icons, text, colours and layout. UX (user experience) is how the whole task feels: quick or slow, clear or confusing. Good interfaces put important things first (hierarchy), keep buttons big enough to tap (about 9 mm or 48 px), use strong colour contrast, stay consistent, give feedback after every action and need few steps. Designers study users, draw wireframes, build clickable prototypes and test them with real people, then improve.
12. Elective theme: User experience
Analysis · Design
- UI and UX Design: Making Screens Easy and Pleasant to Use – Interface design is planning the screens people use on phones, computers, ATMs and machines. UI (user interface) is what you see and touch: buttons, icons, text, colours and layout. UX (user experience) is how the whole task feels: quick or slow, clear or confusing. Good interfaces put important things first (hierarchy), keep buttons big enough to tap (about 9 mm or 48 px), use strong colour contrast, stay consistent, give feedback after every action and need few steps. Designers study users, draw wireframes, build clickable prototypes and test them with real people, then improve.
13. Elective theme: Social and individual impact of computing
Social impact · Legal aspects · Privacy · Culture
- Law and Computing: Rules for Using Computers and Data – Laws protect people when they use computers. Copyright protects the maker of a work, privacy (data protection) law protects information about you, computer misuse law protects computers from unauthorised access, and contract law makes online agreements binding. Details differ by country, but the ideas of permission, consent and fair use are shared.
- Data Privacy: Who Gets Your Data and How to Protect It – Personal data is any information that can point to you. Apps and websites collect it all the time. Privacy means you control who sees it and how it is used. Fair rules say data must be used for a clear purpose, kept small, kept safe and deleted when done. You have rights over your data, and simple habits keep you safe.
14. Elective theme: Computational science
Modelling · Simulation
- Computer Simulation – A model is a simplified description of a real system that keeps only what matters. A computer simulation runs that model step by step in time to see what would happen. It has variables (the state), rules (how the state changes), parameters (numbers we can set) and often randomness, so we repeat runs and average. We check a simulation against real data (validation). Simulations are used for weather, traffic, disease spread, flight training and design, because they are cheaper, safer and faster than real tests, but they are only as good as their model and data.