Technology Applications Concepts and Skills
Core content
Expect durable concepts, not product menus. Data representation (bit vs byte, binary, ASCII/Unicode, RGB color depth); hardware and operating-system roles (RAM is volatile working memory, storage persists); network vocabulary (LAN vs WAN, bandwidth vs latency, IP vs MAC addressing, DNS, HTTP/HTTPS); file-size math; spreadsheet references (relative A1 vs absolute $A$1); sorting (reorders rows) vs filtering (hides rows); database anatomy (field, record, primary key, query). Know file formats: lossy (JPEG, MP3) permanently discards data; lossless (PNG, FLAC) preserves it; vector graphics scale without pixelation. Computational thinking appears as decomposition, pattern recognition, abstraction, and algorithm design-an algorithm is a finite, ordered procedure, not merely a program listing.
Traps to expect
Items pair adjacent-but-different ideas: bandwidth with latency, "the internet" with "the web," a domain name with an IP address, sorting with filtering, RAM speed with permanent storage. Another trap is the plausible-but-wrong tool-using a spreadsheet where a query is needed, or enlarging a raster image and expecting no quality loss. Distractors also assert that converting to PDF, encrypting, or password-protecting a file makes content confidential forever or automatically attributes authorship.
Worked example
A 1,024 × 768 image at 24-bit color: 24 bits = 3 bytes per pixel, so 1,024 × 768 × 3 = 2,359,296 bytes; divide by 1,048,576 for roughly 2.25 MB before compression. Rule of thumb: convert bits to bytes first, divide by 1,024 for KB and 1,048,576 for MB, and confirm whether a format is lossless before predicting compression effects.