Standard difficulty · 20 questions · 40 marks · Time: 36 minutes
Show your working for Sections B and C. Answers are on the last page — try every question first!
Emerging Trends · AW-11IP-EMT-2026-V1 · For parents — fold back or tear off before handing the sheet to your child.
| Q | Answer | Working |
|---|---|---|
| 1 | (d) computers learn patterns from data and improve with experience | — |
| 2 | (a) augmented reality | — |
| 3 | (c) PaaS | — |
| 4 | (a) volume | — |
| 5 | (c) NLP | — |
| 6 | (c) 768 | 24 readings per sensor × 32 sensors |
| 7 | (c) 9 | blocks 9 to 17 |
| 8 | (d) 237 | 4,740 ÷ 20 |
| 9 | The ability of machines to do tasks that need human-like intelligence, such as recognising speech; e.g. a map app suggesting a faster route. | — |
| 10 | (a) IaaS; (b) PaaS | — |
| 11 | (a) variety; (b) veracity | — |
| 12 | 408 KB | 96 readings × 128 bytes × 34 = 417,792 bytes; ÷ 1024 |
| 13 | 4, 5 | each block holds the previous block’s hash, so the change shows up from block 4 onwards |
| 14 | (a) AR; (b) VR; (c) VR | AR adds to the real view; VR replaces it with a made-up world |
| 15 | 20 GB | 5 × 22 |
| 16 | (a) big data (b) cloud computing | — |
| 17 | Machine learning: systems learn from data and improve, e.g. a filter that learns which emails are spam. NLP: computers understand and produce human language, e.g. voice assistants, automatic translation, chatbots. | — |
| 18 | (a) 144; (b) 230,400; (c) 57,600 KB | 1,440 ÷ 10; × 1,600; × 256 ÷ 1024 |
| 19 | (a) 8; (b) 2; (c) changing one block breaks every later link, so the change is easy to detect and every copy of the ledger disagrees with it | blocks 2–9; blocks 8–9 |
| 20 | (a) 5,500; (b) 55; (c) 550 | 550 × 10; 550 ÷ 10; × 10 |