Questions may cover: social engineering, biometric authentication, white and black email lists, common issues, data privacy, ways individuals can protect their computers, use of computer security, and online shopping*.
Questions may cover: parity, check digits, check sums, QR codes, Read-Solomon principles, error detection/correction, scale, efficiency, network ARQ/FEC, RAID levels in data storage, and use of error control in shopping*. Note: error is not about computers checking data validity, not humans (e.g. spellchecker, debugging).
Questions may cover: machine learning, common issues, training, evaluation, Turing test relevance, adoption, policies, the use of artificial intelligence for shopping (e.g. self-checkouts), AI hallucinations, and recent developments in large language models such as ChatGPT and Google Bard.
There will be a question on “impacts” in relation to future-proofing or human factors.
* The multi-national technology corporation must be from the following list: Apple, Microsoft, Amazon, Google (including Waymo), Meta (including Facebook), Tencent (including WeChat), ByteDance (including TikTok).
Candidates can ONLY choose from the list of corporations provided. They only need to choose one corporation.
Where it is not possible to know the corporation’s policies or procedures, questions will be of the “how might / should” type.
Using information, including research and/or classwork that you have previously undertaken, you identify the computer science concept chosen from the achievement standard (see above). You will provide clarity by giving a detailed account of
identifying the computer science concept;
providing details of how the concept is used, is implemented, OR occurs;
explaining how the concept has been or could be applied to address an opportunity;
explaining relevant mechanisms that shape the concept
question on algorithms OR techniques that shape the concept
another question on protocols OR procedures that shape the concept
More Info About Standard
Questions may cover: common examples; an instance in which it makes sense for a solution not to be found; an instance of an approximate solution to an intractable problem.