Computational Thinking

What is computational thinking?

• A way to solve problems using computers by understanding the problem and possible solutions

• A type of computer programming language

• A method for building computers

• A way to memorize computer facts

Answer explanation

Computational thinking is a problem-solving process that involves understanding a problem and devising solutions, often using computer-based methods. This makes the first choice the correct answer.

Which of the following is NOT one of the four cornerstones of computational thinking?

• Decomposition

• Pattern recognition

• Abstraction

• Memorization

Answer explanation

Memorization is not one of the four cornerstones of computational thinking. The correct cornerstones are decomposition, pattern recognition, and abstraction, which help in problem-solving and algorithm development.

Fill in the blank: __________ is breaking down a complex problem or system into smaller, more manageable parts.

• Decomposition

• Iteration

• Abstraction

• Simulation

Answer explanation

Decomposition is the process of breaking down a complex problem into smaller, manageable parts, making it easier to understand and solve. This distinguishes it from other concepts like iteration, abstraction, and simulation.

Fill in the blank: __________ is looking for similarities among and within problems.

• Pattern recognition

• Abstraction

• Decomposition

• Algorithm design

Answer explanation

Pattern recognition involves identifying similarities among problems, which helps in finding solutions. This skill is crucial in problem-solving, making it the correct choice for the blank.

Fill in the blank: __________ is focusing on the important information only, ignoring irrelevant detail.

• Abstraction

• Iteration

• Compilation

• Encapsulation

Answer explanation

Abstraction is the process of focusing on the essential qualities of something while ignoring the irrelevant details. This makes it the correct choice for the blank, as it directly relates to filtering important information.

Fill in the blank: __________ is developing a step-by-step solution to the problem, or the rules to follow to solve the problem.

• Algorithms

• Databases

• Networks

• Compilers

Answer explanation

Algorithms are step-by-step procedures or rules for solving problems, making them the correct choice for the blank. Databases, networks, and compilers serve different purposes in computing.

What are the four key components of computational thinking as described in the passage?

• Decomposition, Abstraction, Pattern Recognition, Algorithms

• Addition, Subtraction, Multiplication, Division

• Input, Output, Storage, Processing

• Planning, Organizing, Leading, Controlling

Answer explanation

The correct choice, 'Decomposition, Abstraction, Pattern Recognition, Algorithms', represents the four key components of computational thinking, essential for problem-solving in computer science.

Fill in the blank: Breaking a complex problem into a series of small, more manageable problems is called __________.

• decomposition

• iteration

• abstraction

• recursion

Answer explanation

Breaking a complex problem into smaller parts is known as decomposition. This approach simplifies problem-solving by allowing us to tackle each part individually, making the overall task more manageable.

Which component of computational thinking involves focusing only on the important details and ignoring irrelevant information?

• Decomposition

• Abstraction

• Pattern Recognition

• Algorithms

Answer explanation

Abstraction is the component of computational thinking that focuses on identifying the essential details of a problem while ignoring irrelevant information, making it easier to understand and solve complex issues.

Match the following computational thinking components with their descriptions:

• A

• Designing simple steps or rules to solve problems

• B

• Focusing on important details and ignoring irrelevant information

• C

• Considering how similar problems have been solved previously

• D

• Breaking down a complex problem into smaller problems