Cambridge IGCSE Computer Science (9–1) (0984) teaches students how computer systems represent information, how hardware and software work together, and how algorithms can be designed, tested and implemented as programs. The 2026–2028 syllabus has two compulsory written papers: Computer Systems and Algorithms, Programming and Logic. Each paper contributes 50% of the final grade. Students develop computational thinking, programming, problem-solving and an understanding of the benefits and risks of technology.
The important distinction is that Computer Science is not simply learning how to use applications, repair devices or write code by copying examples. Candidates need to understand what a system is doing, explain why a particular method is suitable and develop a solution that works for a stated problem. A student may know Python syntax but struggle to design an algorithm. Another may describe a CPU but fail to explain how instructions are processed. Strong preparation connects systems knowledge, algorithms, programming, testing, data and responsible use of technology.
Quick student reference – Qualification: Cambridge IGCSE Computer Science (9–1), code 0984, examinations 2026, 2027 and 2028. – Grading: numbered grades 9–1; Cambridge states that 0984 is otherwise the same as Computer Science 0478. – Paper 1 – Computer Systems: 1 hour 45 minutes, 75 marks, 50%. Short-answer and structured questions; all compulsory; no calculator. – Paper 2 – Algorithms, Programming and Logic: 1 hour 45 minutes, 75 marks, 50%. Short-answer, structured and scenario-based questions; all compulsory; no calculator. – Availability: administrative zone 3 and centres in Oman and the UAE, in June and November. Confirm centre entry. – Core domains: data representation; data transmission; hardware; software; the internet and its uses; automated and emerging technologies; algorithm design and problem-solving; programming; databases; Boolean logic. – Programming: use the languages and pseudocode formats allowed by the 2026–2028 syllabus and question instructions. Do not copy the Python-only 2029–2031 rules into a 2026–2028 examination. – Assessment: two externally assessed papers; no coursework component in the published 2026–2028 structure.
Confirm the exact code and syllabus year
The qualification in this guide is Cambridge IGCSE Computer Science (9–1) 0984. The relevant 2026–2028 syllabus applies to examinations in those years.
Cambridge states that 0984 is graded from 9 to 1 but is otherwise the same subject content as Cambridge IGCSE Computer Science 0478. The code and grading route still matter: a school must enter the candidate for the intended syllabus and confirm that the centre can offer the 9–1 option.
The 0984 route is available in administrative zone 3 and centres in Oman and the UAE, in the June and November series. It is not universally available at every Cambridge centre. Ask the examinations officer to confirm the entry code before buying subject-specific materials.
Computer Science 0984 and Computer Science 0478
The two qualifications share the subject content and assessment structure described by Cambridge, but the grading scale and entry availability differ.
- 0984: Cambridge IGCSE Computer Science (9–1), with numbered grades.
- 0478: Cambridge IGCSE Computer Science, with A*–G grading.
A learner may use explanations or practice resources written for 0478 where the topic and syllabus year match. However, the student should check the code, paper format and permitted programming language rules for the actual examination.
The grade scale is not a casual choice to make after the examination. Entries and any changes must follow Cambridge and centre deadlines. A student should not assume that a 9–1 grade can be converted mechanically to an A*–G grade for every institution. Recognition requirements belong to the receiving school or institution.
What Computer Science actually studies
Computer Science investigates how information is represented, processed, stored and transmitted, and how problems can be solved through computational methods.
The subject includes the physical computer system, software, data representation, communication networks, internet services, automated systems, algorithms, programming and databases. It also introduces ethical, environmental and social questions associated with computing.
A complete answer often crosses several parts of the syllabus. For example, a program that processes a large data set involves input, storage, data representation, algorithms, processing and output. A networked system raises questions about transmission, security, reliability and the responsible handling of information.
Students should learn to explain both what happens and why the design is appropriate.
The two compulsory examination papers
All candidates take both papers. Each lasts 1 hour 45 minutes, carries 75 marks and contributes 50% of the qualification.
Paper 1 – Computer Systems assesses the computer system and its uses. Questions are based on Topics 1–6 of the syllabus and are compulsory. No calculator is permitted.
Paper 2 – Algorithms, Programming and Logic assesses computational thinking, algorithm design, programming and logic. Questions are based on Topics 7–10. All questions are compulsory, including the scenario-based question. No calculator is permitted.
There is no separate practical programming examination in the published 2026–2028 paper structure. Programming is assessed through the written paper, including code and algorithmic reasoning.
The two papers require different but connected forms of preparation. Paper 1 needs accurate technical knowledge and explanation. Paper 2 requires students to trace, construct and reason about algorithms and programs.
A note about the 2029–2031 syllabus change
Cambridge has published a separate 2029–2031 Computer Science syllabus. It makes substantial changes to the teaching and assessment approach, including a stronger focus on practical programming and Python 3 as the programming language for teaching, assessment and programming questions. The updated syllabus removes pseudocode and introduces additional modern computing content. Cambridge also describes a digital-only examination route under a separate code.
These changes do not automatically apply to candidates sitting the 2026, 2027 or 2028 examinations under 0984. Students must use the syllabus for the year they will actually sit.
This distinction is important when using online tutorials. A video created for the 2029 course may teach useful Python concepts, but its examination requirements cannot be assumed to match a 2026–2028 candidate’s paper.
Topic 1: Data representation
Computers store and process information using binary. Students should understand how numbers, text, images and sound can be represented as bit patterns.
A bit is a binary digit, either 0 or 1. A byte contains eight bits. Data sizes and conversions require accurate use of the units and prefixes specified by the syllabus.
The same binary pattern can represent different kinds of information depending on the agreed encoding or interpretation. Students should not assume that a sequence of bits has one universal meaning without knowing how it is being used.
Binary and denary numbers
The denary system uses base 10, while binary uses base 2. Each binary position represents a power of two.
A student should be able to convert between binary and denary, understand place values and perform the operations specified by the syllabus.
A common mistake is to read a binary number as though it were denary. Another is to forget that a leading zero may be needed when a fixed number of bits is required.
Practise conversions with working shown. Check the result by converting it back or comparing it with the largest value representable by the given number of bits.
Hexadecimal and why it is useful
Hexadecimal is base 16 and uses the symbols 0–9 and A–F. It provides a compact way of writing binary values because one hexadecimal digit corresponds to four binary bits.
Students should understand conversions between binary, denary and hexadecimal where required. Practise grouping binary digits from the correct end and retaining leading zeros when the representation requires a fixed width.
Hexadecimal is often used in computing because long binary sequences are difficult for people to read and check. The compact form makes certain values easier to communicate.
Character encoding
Text is stored using character codes. Students should understand that a computer needs a mapping between a character and a numerical code to represent written information.
The syllabus includes the relevant character-encoding concepts and the relationship between character sets and the amount of data needed to represent them.
Do not confuse a visible character with the binary code used to store it. Different encodings can represent characters differently, and an encoding needs to be agreed between systems for text to be interpreted correctly.
Image representation
A digital image can be represented as a grid of pixels. Each pixel stores information about colour, using a specified number of bits per pixel.
Students should understand how image resolution and colour depth affect file size and quality. A higher resolution usually requires more pixels; a greater colour depth allows more possible colours per pixel.
When calculating an uncompressed image size, identify the number of pixels and bits per pixel, then convert the total bits into the requested unit. Include any assumptions or overhead specified by the question.
A higher file size does not automatically mean an image looks better in every context. Display size, compression and the original image all matter.
Sound representation
Digital sound is represented through sampling. The analogue signal is measured at regular intervals, and each sample is stored as a numerical value.
Students should understand the roles of sampling rate and sample resolution. A higher sampling rate records more samples per second; a greater sample resolution provides more possible values for each sample.
These choices affect file size and the accuracy with which the stored data can represent the original signal. Questions may ask candidates to compare recordings or calculate uncompressed file sizes.
Read all the units carefully. Samples per second, bits per sample and duration are different quantities.
Compression
Compression reduces the amount of data needed to store or transmit a file. Students should distinguish lossless and lossy compression.
Lossless compression allows the original data to be reconstructed exactly. Lossy compression permanently removes some information to reduce file size, which may be suitable for certain image, audio or video uses when a controlled reduction in quality is acceptable.
A candidate should explain why a method suits the type of data and the intended use. It would not be appropriate to lose important information from a financial transaction simply to make a file smaller.
Topic 2: Data transmission
Data transmission concerns how information moves between devices and systems. Students should understand transmission methods, data packets, protocols, error detection and the factors that affect reliable communication.
A message may be broken into packets, transmitted across a network and reassembled at the destination. The packets may not all follow the same path.
Reliable communication needs agreed rules and methods for detecting errors. Students should understand the role of protocols and the difference between the data being sent and the control information used to manage transmission.
Serial and parallel transmission
In serial transmission, bits are sent one after another along a communication path. In parallel transmission, multiple bits can be sent at the same time using separate paths.
Candidates should understand the advantages and limitations of each method in the relevant context. Parallel transmission can be affected by timing differences between signals, while serial transmission can be suitable for longer-distance communication and modern high-speed connections.
Avoid claiming that parallel is always faster. The actual performance depends on the interface, distance, timing and technology.
Simplex, half-duplex and full-duplex
Simplex communication allows data to travel in one direction only. Half-duplex allows communication in both directions, but not at the same time. Full-duplex allows simultaneous two-way communication.
Examples should be used carefully. The key is to describe the communication arrangement rather than memorise a device name that may have several operating modes.
Data packets and protocols
Packets contain data and control information. The control information may include addressing, sequencing and error-checking details, depending on the protocol and network.
Protocols establish rules that devices follow so they can exchange data. Students should understand why common standards are necessary when devices are manufactured by different organisations.
A packet-based system can support efficient routing and reconstruction of a message. It also creates a need to identify missing, duplicated or corrupted packets where relevant.
Error detection
Errors can arise during transmission because of interference or other faults. The syllabus covers methods used to detect errors, including parity checks, checksums and other specified techniques.
Students should be able to explain what a method checks and what it cannot guarantee. A parity check can detect certain patterns of bit errors but does not detect every possible error.
Do not say that an error-detection method automatically corrects the data unless the method includes a correction process.
Topic 3: Hardware
Hardware is the physical equipment in a computer system. Students should understand the roles of input devices, output devices, storage devices, processors and memory.
A good answer links a device’s properties to the task. A barcode reader, microphone, sensor and keyboard all provide input, but they collect different kinds of information.
Similarly, a monitor, printer and actuator provide different types of output. Candidates should select equipment based on the situation rather than write a list of devices without explaining their suitability.
Input devices and sensors
Input devices allow data to enter a computer system. Sensors convert physical conditions such as temperature, light or pressure into signals that can be processed.
A sensor-based system can monitor conditions continuously and respond automatically when a threshold is reached. Students should understand the role of the sensor, processor and output device in a complete control system.
A common mistake is to describe the sensor as making the decision. The sensor measures or detects; the program or control system processes the information and determines the response.
Output devices and actuators
Output devices present information or produce an action. A screen displays visual output, a speaker produces sound and an actuator can cause physical movement.
In a control system, the output device should match the required action. A heater, motor, alarm and display do not perform interchangeable functions.
Explain the entire input-process-output sequence when a question describes an automated system.
The Central Processing Unit
The CPU executes instructions and coordinates processing. Students should understand the roles of the control unit, arithmetic logic unit, registers and buses at the level required by the syllabus.
The fetch-decode-execute cycle describes the repeated process through which instructions are retrieved, interpreted and carried out.
Candidates should be able to explain how registers temporarily hold data or instructions and how signals coordinate operations.
Do not describe the CPU as a storage device for all data. Main memory and secondary storage have different roles.
Primary memory and secondary storage
Primary memory is used by the computer while programs and data are being processed. RAM is volatile, while ROM is non-volatile. Cache provides fast access to frequently used data and instructions.
Secondary storage holds data over time. It includes magnetic, optical and solid-state technologies, each with particular characteristics, capacity, durability and access methods.
Students should compare devices using relevant criteria such as speed, capacity, portability, reliability and cost. The best choice depends on the task.
Virtual memory and performance
Virtual memory allows part of secondary storage to be used when the available RAM is insufficient for the active workload. It is not the same as physical RAM and is generally slower.
Students should understand how memory size and other hardware features can affect system performance. A computer may slow down when it has to move data between RAM and secondary storage frequently.
Do not assume that adding storage capacity always makes a computer process tasks faster. Capacity and processing performance are related to different components.
Topic 4: Software
Software is the set of programs and instructions that tell a computer system what to do. Students should distinguish system software from application software and understand the roles of operating systems, utilities and translators.
An operating system manages resources and provides an interface between users, applications and hardware. Utility software performs maintenance or protection tasks such as backup, compression and security scanning.
Application software helps users perform specific tasks, such as word processing, modelling or image editing.
Operating systems
An operating system manages processes, memory, files, input/output devices and user interaction. Candidates should understand why these services are important.
When multiple programs are running, the operating system manages access to processor time and other resources. It also supports file organisation, access permissions and communication with peripherals.
A strong answer links an operating-system function to a practical need rather than simply listing the feature.
Translators and programming languages
Programming languages need to be translated into machine-executable instructions. Students should understand the relevant differences between compilers, interpreters and assemblers.
A compiler translates a program into another form before execution. An interpreter translates and executes program instructions in a different way, usually as the program runs. An assembler translates assembly language into machine code.
The exact advantages and disadvantages depend on the context. Candidates should compare speed, error reporting, portability and the development process where required.
Topic 5: The internet and its uses
The internet is a global network of connected networks. Students should understand key concepts such as internet services, web addresses, browsers, servers, cloud computing and online communication.
The World Wide Web is a service that uses the internet; it is not another name for the entire internet. The distinction matters in questions about network services.
Students should understand how clients and servers communicate and why protocols and addressing are necessary.
Cloud computing
Cloud computing provides access to computing resources and services over a network. These may include storage, software and processing resources.
Advantages can include access from multiple devices, scalability and reduced need for local infrastructure. Limitations can include dependence on network access, recurring costs, privacy concerns and reliance on a service provider.
A candidate should evaluate cloud use in context. A small organisation may value reduced maintenance, while a highly sensitive system may require careful control over data location and access.
Cybersecurity and threats
Computer systems can be affected by malware, unauthorised access, social engineering, data theft and other threats.
Students should understand common threats and methods of reducing risk, including strong authentication, access controls, encryption, backups, updates, firewalls and anti-malware tools as appropriate to the syllabus.
A strong answer distinguishes prevention, detection and recovery. A backup helps recovery after data loss; it does not necessarily prevent an attack.
Topic 6: Automated and emerging technologies
Automated systems use input data, processing and output actions to perform tasks with limited human intervention. Emerging technologies create opportunities but also raise ethical, legal, social and environmental questions.
Candidates should understand examples of automation and recognise that a system’s quality depends on its design, data, testing and context.
Automation may improve consistency or speed, but errors can occur if sensors fail, assumptions are wrong or the system receives unsuitable data.
A balanced evaluation considers who benefits, who may be disadvantaged and what safeguards are needed.
Artificial intelligence and machine learning
Students should understand the basic idea of artificial intelligence and machine learning within the syllabus scope. Machine-learning systems can use data to identify patterns and make predictions or classifications.
The quality of an output depends on the training data, model design and the context in which it is used. Biased or incomplete data can produce unfair or inaccurate outcomes.
Do not treat AI as a system that automatically understands truth. A model produces outputs based on its design and information; human oversight and evaluation remain important.
Topic 7: Algorithm design and problem-solving
An algorithm is a finite sequence of steps for solving a problem. Students should learn how to analyse a problem, identify inputs and outputs, develop a solution, test it and refine it.
An algorithm should be clear, logically ordered and appropriate to the problem. It should also handle relevant boundary conditions and invalid inputs where needed.
A common error is beginning to write code before understanding the problem. First identify what the program must do and which data it needs.
Flowcharts and pseudocode
Flowcharts represent the sequence and decisions in an algorithm using standard symbols. Pseudocode expresses the logic in a structured, language-independent form.
Students should be able to interpret, complete and construct algorithms using the representations specified in the 2026–2028 syllabus and examination instructions.
Do not assume that pseudocode is identical to Python or another programming language. It describes the logic rather than requiring the exact syntax of a particular compiler.
Sequence, selection and iteration
The three fundamental control structures are sequence, selection and iteration.
Sequence runs instructions in order. Selection chooses between possible paths based on a condition. Iteration repeats a set of instructions while or until a condition is met, or for a specified number of times.
Candidates should identify which structure is suitable for the task and trace how the values change during execution.
A common error is choosing a loop that never terminates. Test the condition carefully and make sure the loop can reach an ending state.
Variables, constants and data types
Variables store values that can change during program execution. Constants represent values intended to remain fixed. Data types describe the kind of data a variable can hold, such as integer, real, Boolean or string.
Selecting suitable data types supports correct operations and avoids errors. For example, a text value should not be treated as a numeric quantity merely because it contains digits.
Students should understand scope and naming conventions as required by the syllabus and use clear identifiers in their algorithms.
Validation and verification
Validation checks whether input data is sensible and acceptable for the task. Verification checks whether data has been entered or copied accurately.
Examples of validation include range checks, length checks, presence checks and format checks. The correct method depends on the type of input and the rules of the problem.
A range check does not prove that a value is factually correct. It only verifies that the value falls within an allowed range.
Students should be able to choose a suitable validation method and explain its limitation.
Testing and debugging
Testing checks whether a program produces the expected result for selected inputs. Debugging identifies and corrects errors.
Candidates should understand syntax, logic and runtime errors and be able to identify test data that checks normal, boundary and erroneous cases.
A program may run without a syntax error and still produce the wrong answer. Logical testing is therefore essential.
Use a trace table to follow variables and decisions through an algorithm. Compare the actual result with the expected result and locate the first point where the values diverge.
Topic 8: Programming
Programming turns an algorithm into instructions in a specified language. Students should be able to write, read, trace and correct programs using the language options allowed by the 2026–2028 syllabus.
The central goal is not to memorise code fragments without context. It is to translate a problem into a working solution using input, processing, output, selection, iteration, data structures and appropriate subroutines.
Candidates should follow the language and notation permitted by the specific examination question. The programming requirements for the 2029–2031 syllabus differ, so students must not mix those new rules with the 2026–2028 assessment.
Arrays and structured data
Arrays store multiple related values under one variable name and allow elements to be accessed using an index. Students should understand how arrays support repeated processing of data.
A common error is using the wrong index or confusing the number of elements with the highest index. Trace the array carefully and check whether the indexing convention in the question begins at 0 or 1.
Where the syllabus requires records or other data structures, learn how related fields are organised and accessed.
Subroutines and modular programming
A subroutine is a named block of code that can be called from another part of a program. Procedures and functions support modular design and reduce repeated code.
Students should understand parameters, return values and the difference between a procedure and a function in the required programming model.
A well-designed subroutine performs a clear task. Its name should communicate its purpose, and its parameters should provide the information it needs.
File handling
Programs may need to read data from files or write results to files. Candidates should understand the file operations and structures included in the syllabus.
A file-processing task should consider how records are read, how the end of the file is detected and what happens when data is missing or invalid.
A program should not assume that every file contains perfect data. Input validation and appropriate error handling improve reliability.
Topic 9: Databases
Databases organise data so that it can be stored, searched, updated and retrieved efficiently. Students should understand tables, records, fields, primary keys, foreign keys and relationships.
A database table should represent a collection of related records. A field stores one attribute; a record contains the related values for one item or entity.
Keys help identify records and connect related tables. A primary key should uniquely identify each record.
Relational databases
Relational databases organise data into tables that can be linked through keys. This helps reduce duplication and maintain consistency.
Students should understand one-to-one, one-to-many and many-to-many relationships at the level required by the syllabus.
A common design problem occurs when the same information is copied into multiple records. Updating one copy but not another creates inconsistency. Relational design can reduce this problem.
Queries and data processing
A query selects or manipulates data according to specified conditions. Candidates should understand the query concepts and syntax required by the syllabus.
Read the requested output carefully. A query may require filtering, sorting, selecting fields or applying conditions. A small logical error can return too many or too few records.
Practise interpreting the query before writing it. Identify which table or fields are needed and how the conditions should be combined.
Topic 10: Boolean logic
Boolean logic works with true and false values and is used in logic gates, conditions and digital systems.
Students should understand AND, OR and NOT, and the truth tables for the relevant logic gates. Logic expressions can be evaluated using the input values and the gate relationships.
A common error is confusing AND and OR. AND is true only when all its inputs are true; OR is true when at least one input is true.
Logic gates and circuits
Logic gates perform Boolean operations on one or more binary inputs and produce an output. Students should be able to interpret gate diagrams, construct truth tables and evaluate simple logic circuits.
Follow the signal from input to output, applying one gate at a time. For a complex circuit, record intermediate results to reduce mistakes.
A logic circuit can represent the conditions under which an automated system activates. Explain the relationship between the physical situation and the Boolean expression.
Ethical, legal and environmental issues
Computer systems affect privacy, intellectual property, security, access, employment and the environment.
Students should understand responsible use of technology and the relevant legal and ethical issues in the syllabus. Examples include protecting personal data, respecting copyright, using secure systems and considering the environmental costs of manufacturing and disposing of devices.
A balanced response explains the issue and its consequences. Avoid broad claims that technology is always beneficial or always harmful.
How to prepare for Paper 1
Paper 1 needs clear understanding of systems, data and technology. Create concise notes for each topic, but use them to answer questions rather than as a substitute for practice.
Practise explaining technical terms in your own words and linking them to a practical example. Compare technologies using a consistent set of criteria.
Use diagrams for the CPU, storage, transmission and other systems where they help explain how components interact.
How to prepare for Paper 2
Paper 2 needs repeated practice with algorithms, tracing, programming and logic. Write algorithms from a problem statement, then test them using normal, boundary and invalid data.
Trace unfamiliar code line by line. Use a table to record variable values and conditions. Do not skip steps because the code looks familiar.
For programming, practise writing complete solutions with clear input, processing and output. Then test them and explain any error found.
Common Computer Science mistakes and repairs
- Hardware and software confusion: a physical device is described as a program. Repair by classifying each part of the system.
- Binary conversion errors: place values or bit groupings are wrong. Repair with written place-value tables.
- Image and sound size errors: units or bits per sample are omitted. Repair by writing the full calculation and conversion.
- Algorithm without testing: a solution is written but not traced. Repair using test tables and boundary values.
- Code memorisation: a fragment is copied into a different problem. Repair by identifying inputs, outputs and required processing first.
- Validation versus verification: the two are treated as identical. Repair with examples of acceptable range and accurate entry.
- Logic gate confusion: AND and OR are mixed. Repair by completing truth tables.
- Cybersecurity oversimplification: one tool is claimed to solve every risk. Repair by matching controls to threats.
- Syllabus-year mismatch: 2029 Python-only rules are applied to 2026–2028. Repair by checking the actual examination year.
Repair, stabilise and extend
Repair begins with binary, data representation, system components, basic algorithms and simple program tracing.
Stabilisation helps learners who know definitions but struggle with unfamiliar scenarios. Mix topics and ask students to explain why a method is suitable.
Extension develops more complex algorithms, program design, database reasoning, logic expressions and balanced evaluation of emerging technology.
A student may be strong in programming but weak in data representation, or understand the CPU but struggle to trace a loop. Diagnose these skills separately.
A four-session weekly routine
Session 1 – Computer Systems: study one system topic and explain it using a labelled diagram or comparison.
Session 2 – Algorithms: design and trace short solutions, including boundary and invalid test data.
Session 3 – Programming and databases: write or interpret code, manipulate data and practise queries.
Session 4 – Logic and examination practice: complete Boolean logic questions and mixed structured tasks, then correct the first error.
A twelve-week preparation plan
Weeks 1–2: confirm code 0984, the 2026–2028 syllabus and centre eligibility. Diagnose systems knowledge, binary and algorithmic thinking.
Weeks 3–5: consolidate data representation, transmission, hardware, software, the internet and automated systems.
Weeks 6–8: develop algorithm design, programming, data structures, database concepts and Boolean logic.
Weeks 9–10: complete timed Paper 1 and Paper 2 practice using the correct 2026–2028 question format.
Weeks 11–12: revisit recurring errors, practise complete scenario solutions and confirm examination instructions.
This is an illustrative preparation framework, not an official Cambridge teaching timetable or a grade guarantee.
Frequently asked questions
Is Computer Science 0984 the same content as 0478?
Cambridge states that 0984 is graded 9–1 but is otherwise the same as Computer Science 0478. Entry availability and grading differ.
How many papers are there?
Two compulsory papers: Computer Systems, and Algorithms, Programming and Logic. Each lasts 1 hour 45 minutes, carries 75 marks and contributes 50%.
Is there a practical computer examination?
The published 2026–2028 0984 structure has two written papers. Programming and algorithmic skills are assessed through Paper 2 questions.
Are calculators allowed?
No calculators are permitted for either Paper 1 or Paper 2 in the 2026–2028 syllabus.
Is Python the only language for the 2026–2028 examination?
No. Do not apply the later 2029–2031 Python-only update to the 2026–2028 syllabus. Follow the programming language and notation permitted in the actual syllabus and examination question.
Does the 2029 syllabus change affect students sitting in 2028?
No. Students sitting in 2028 use the 2026–2028 syllabus. The 2029–2031 requirements apply to the later syllabus period.
Where is 0984 available?
Cambridge lists administrative zone 3 and centres in Oman and the UAE, in June and November. Confirm the centre’s entry arrangements.
Official sources and related learning
Use the Cambridge IGCSE Computer Science (9–1) 0984 page and the 2026–2028 syllabus PDF. The subject page also explains the later 2029–2031 changes.
Related eduKateSG guides include How IGCSE Computer Science Works and How IGCSE ICT Works. Computer Science and ICT overlap in some areas but have distinct aims and examination requirements.
Final student checklist
- I know my code is 0984 and the examination year is 2026, 2027 or 2028.
- I have confirmed that my centre can enter the 9–1 route.
- I understand that Paper 1 and Paper 2 are both compulsory and equally weighted.
- I can explain data representation, hardware, software and data transmission.
- I can distinguish system software, applications and operating-system functions.
- I can analyse algorithms using sequence, selection and iteration.
- I can trace code and construct a working solution.
- I can use test data to find logical errors.
- I understand databases and Boolean logic.
- I can explain responsible, secure and ethical use of computer systems.
- I use the correct 2026–2028 requirements and do not mix them with the 2029–2031 changes.
IGCSE Computer Science (9–1) works when students connect computer systems, computational thinking, programming, data and responsible technology use. A strong candidate can explain how a system works, design a solution, trace it carefully and judge whether it is reliable for the problem it is meant to solve.
Official source: Cambridge IGCSE Computer Science (9–1) (0984). This eduKateSG guide is independent educational commentary, not an official Cambridge publication.
More IGCSE (9–1) Student Guides in This Batch
Explore the other eduKateSG guides in this batch. These qualifications have different syllabus years, subject content and assessment structures. Always follow the requirements for the subject code actually entered.