| name | computational-literacy |
| description | Understanding how digital systems actually work -- hardware, operating systems, networks, and information representation -- at a depth sufficient to reason about them rather than just use them. Covers CPU/RAM/storage/GPU roles, what an OS does, how packets travel the internet, and how computers represent numbers, text, images, and sound as binary. Use when a learner needs to build a mental model of computing rather than memorize menu paths. |
| type | skill |
| category | digital-literacy |
| status | stable |
| origin | tibsfox |
| modified | false |
| first_seen | "2026-04-12T00:00:00.000Z" |
| first_path | examples/skills/digital-literacy/computational-literacy/SKILL.md |
| superseded_by | null |
Computational Literacy
Computational literacy is not coding. It is the capacity to reason about how digital systems work at a level sufficient to understand their behavior, diagnose their failures, and evaluate claims made about them. A computationally literate person does not need to write Python, but they should know why a computer slows down when RAM is full, why the internet works when no one is in charge of it, and why an image "looks different on different screens" is actually a statement about color spaces and pixel encoding. This skill covers the core mental models: hardware, operating systems, networks, and information representation.
Agent affinity: rheingold (practical fluency), ito (connected learning framing), jenkins (literacy across media)
Concept IDs: diglit-hardware-components, diglit-operating-systems, diglit-networks-internet, diglit-information-representation
Hardware: What the Boxes Actually Do
A computer is a coordinated set of specialized parts. Understanding their roles is the fastest path to understanding why things behave the way they do.
CPU (Central Processing Unit)
The CPU executes instructions. It reads a stream of operations (arithmetic, comparisons, memory access, jumps) from RAM and performs them one (or several) at a time. Modern CPUs have multiple cores -- effectively multiple workers sharing the same workspace -- and run at clock speeds measured in gigahertz (billions of cycles per second).
The practical consequence: CPU-bound tasks (calculations, compression, encryption) are bounded by clock speed and core count. If your computer feels slow during video editing, the CPU is often the bottleneck.
RAM (Random Access Memory)
RAM is the workspace where active programs live. It is fast -- nanoseconds to access any location -- but volatile: turning off the power erases it. RAM is measured in gigabytes (8 GB, 16 GB, 32 GB are typical in 2026).
The practical consequence: When you open too many browser tabs and the computer starts swapping to disk, you are watching RAM exhaustion. The operating system is moving inactive memory to storage, which is thousands of times slower. The only cures are closing programs or adding RAM.
Storage (SSD, HDD, NVMe)
Storage is where data lives when the power is off. SSDs (Solid State Drives) have no moving parts and access any block in microseconds. NVMe SSDs are faster still -- nearly as fast as RAM for large sequential reads. HDDs (traditional spinning disks) are slower but cheaper per gigabyte.
The practical consequence: Boot time, application launch time, and "where did that file go?" speed are all storage-bound. Upgrading from HDD to SSD is the single most impactful upgrade for an older computer.
GPU (Graphics Processing Unit)
