Computational thinking is a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science. Computational thinking is thinking in terms of abstractions, invariably multiple layers of abstraction at once. Computational thinking is about the automation of these abstractions. The automaton could be an algorithm, a Turing machine, a tangible device, a software system –or the human brain. Recursively, it could be a network of these. Computational thinking gives us the power to scale beyond our imagination.

Computational thinking is a Carnegie Mellon thing

At Carnegie Mellon, computational thinking pervades our culture. In our research, computer science interacts with almost every other discipline on campus. Computational biology, computational chemistry, computational design, computational finance, computational linguistics, computational logic, computational mechanics, computational neuroscience, computational physics, and computational and statistical learning are just a few examples of such interdisciplinary fields of study. In our education, our undergraduate computer science curriculum and our outreach programs teach students how to think like a computer scientist. Our message is that computer science is not just about programming, but about thinking. Our long-term vision is to make computational thinking commonplace for everyone, not just computer scientists.