Computational Thinking – Quick Reference

Computational Thinking – Definition
  • Formulate problems as algorithms for computer execution.
  • Core components: Abstraction, Decomposition, Pattern Recognition, Algorithm Design.
Algorithm Basics
  • Algorithm = sequence of step-by-step instructions.
  • Central to all computer-based problem solving and many real-world applications.
Course Topics Overview
  • Programming foundations: program structure, flowchart, pseudocode, data types, variables, selection, iteration, recursion.
  • Programming languages: machine language → high-level (C, C++, Python, Java).
  • Computer internals: microprocessor performs rapid arithmetic & Boolean operations.
  • Computational thinking process (see Definition).
  • Algorithm complexity: Big  O\text{Big\;O} notation; scalability with input size.
  • Current computing trends and technological evolution.
Intended Learning Outcomes
  1. Explain basic microprocessor operations and program execution cycle.
  2. Write simple programs in Python.
  3. Describe and apply each step of the computational thinking process.
  4. Formulate problems so they can be solved by a computer.
  5. Employ computational thinking within your discipline.