computational

The word "computational" refers to anything involving computation: using clear steps (often called algorithms) and, in modern contexts, computers to solve problems or work with data. It’s a broad term used across many disciplines, often pointing to a shift toward data-driven work and methods you can run and test repeatedly.

Originally, "computational" was closely tied to mathematics and physics, describing methods for performing complex calculations. However, its meaning has expanded dramatically with the rise of computer science. Now, you'll find "computational" attached to fields like chemistry ("computational chemistry," using computers to model molecules), economics ("computational economics," building economic models that can be simulated on a computer), and even journalism ("computational journalism," using data analysis to uncover stories).

"Computational thinking" is a key concept, emphasizing problem-solving skills applicable beyond just coding. It involves breaking down complex problems into smaller, manageable steps; recognizing patterns; abstracting important information; and designing algorithms—step-by-step instructions for solving the problem.

While anything done on a computer isn't necessarily "computational," the term implies a deliberate focus on the underlying process: the calculations, rules, and choices that produce the result. A simple word-processing task is not computational, but designing a method to automatically summarize large documents is. You may also see it in phrases like "computational cost" or "computationally expensive," meaning a task takes a lot of time, memory, or processing power to run.