Introduction
- Computational thinking involves strategies to solve complex problems and can be applied to both humans and computers.
- The four components of computational thinking are decomposition, pattern recognition, algorithms, and abstraction.
- Computational thinking is essential for problem-solving in programming and other fields.
- Ethical considerations and human oversight are crucial in automation to avoid biases and ensure transparency.
Exercise
Computational thinking in practice
- Computational thinking involves breaking down problems, recognizing patterns, and developing algorithms.
- While programming is instructing a computer to carry out tasks, computational thinking helps decide what those tasks will be.
- Computational thinking is used in various fields, from project management to epidemiology, and even in daily tasks.
- Structure diagrams are useful tools for visually breaking down and planning problem-solving steps.
Computational thinking in programming
- Decomposition is essential for breaking down problems into discrete parts in programming.
- Computers require precise instructions, and problems must be broken down accordingly.
- Linear code runs commands in a sequence, while branching code allows for different pathways based on conditions.
- Pattern recognition helps programmers adapt existing code for new problems.
Pseudocode
- Pseudocode is a valuable tool for organizing and planning coding solutions before actual programming.
- It helps to list each step of a process logically, making it easier to translate into code.
- Loops allow the execution of repetitive tasks until certain conditions are met.
- Variables in loops can change with each iteration, demonstrating the concept of abstraction.