External Assessment

Standard: 92006 

Title: Demonstrate understanding of usability in human-computer interfaces.

Version: 2

Number of credits: 5 

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Questions will be in short or extended answer format. Resources will be provided within the examination, including a list of Nielsen’s heuristics. 

For 2026, examples of usability principles will be drawn from: 

• Mātāpono Māori 

• Nielsen’s usability heuristics 

• usability concepts such as internal and external consistency, and accessibility. 

Candidates will study an interface of their own choice before the assessment. 

Candidates are expected to write no more than 800–1200 words in this assessment. 

Standard: 91898

Title: Demonstrate understanding of a computer science concept 

Version: 1 

Number of credits: 3 

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Candidates will be required to respond in matching lists, short and/or extended answers (800–1500 words in total) to questions relating to their choice of ONE of the following computer science concepts: 

• computer security OR  

• encryption  

For 2026, questions on impacts will focus on human factors and social impact. 

For computer security, questions may cover any of the following: 

• Authentication,  antivirus, malware, education 

• VLANs* 

• VPNs – uses and limitations 

• School security* 

• Password management 

For encryption, questions may cover any of the following: 

• Types of encryption (symmetric, asymmetric, hashing) 

• VPNs – use of encryption 

• WPA2 / WPA3-Personal and WPA2 / WPA3-Enterprise in Wi-Fi* 

• Device encryption such as BitLocker* 

• Passwords managers 

• Digital signatures. 

Standard: 91908 

Title: Analyse an area of computer science.

Version: 1 

Number of credits: 3 

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Candidates will be required to respond in short and/or extended answers (800–1500 words in total) to questions relating to their choice of ONE of the following areas of computer science: 

• Complexity and tractability 

• Big data 

• Formal languages. 

For Complexity and tractability, questions may cover: 

polynomial and non-polynomial time complexity, Big O notations O(1), O(log n), O(n) , O(n^k), O(2^n), O(n!), and best-case, worst-case, and average-case time complexity, complexity classes (P, NP, NP-complete), solving complex problems (approximation algorithms/heuristics), algorithm design and optimisation, optimal solutions (Travelling salesman/knapsack, etc.).  

For Big data, questions may cover: 

characteristics of big data (volume, variety, velocity, etc.), generation, processing and analysing data in different formats, interpretation and representation (bias and display), tools and technologies used in big data, and big data considerations (privacy, ethics, and data governance). 

For formal languages, questions may cover: regular expressions and their use in pattern matching and validation; simple finite-state automata and their role in recognising regular languages; context-free grammars (CFGs) and their applications in programming languages; and the relationship between formal languages, compilers, and computational complexity. 

Special notes: 

Teachers are encouraged to help their students develop answering techniques to ensure that they are able to respond clearly and concisely within the total recommended word limit of 1500 words.  Teachers are strongly encouraged to prepare students to apply their understanding of computer science to unfamiliar contexts.  Teachers should prepare students to identify and articulate instances where overlap with various areas of computer science occurs, e.g. with artificial intelligence.