WJEC Computer Science KO - Computational Thinking

WJEC Computer Science KO - Computational Thinking

11th Grade

8 Qs

quiz-placeholder

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WJEC Computer Science KO - Computational Thinking

WJEC Computer Science KO - Computational Thinking

Assessment

Quiz

Computers

11th Grade

Medium

Created by

ICT Pentrehafod

Used 3+ times

FREE Resource

8 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the definition of computational thinking?

The reduction of a sub-problem to its simplest set of characteristics that are most relevant to producing a solution.

Memory locations used to store data that can change during program execution.

Methods and techniques for analyzing a problem aimed at producing a solution that can be developed as a computer program.

Identifying how similar problems have been solved previously.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the term 'decomposition' refer to in the context of problem solving?

The step-by-step design of a solution to a sub-problem.

The technique of breaking down a large program into a series of more manageable sub-problems.

Memory locations used to store data that does not change during program execution.

Recognizing patterns in complex problems to solve them more efficiently.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which term describes the process of identifying how similar problems have been solved previously?

Abstraction

Algorithm

Pattern recognition

Variables

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is meant by 'abstraction' in problem solving?

The list of steps that need to be taken to solve the problem.

The reduction of a sub-problem to its simplest set of characteristics that are most relevant to producing a solution.

Methods and techniques for analyzing a problem aimed at producing a solution.

Memory locations used to store data that can change during program execution.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an algorithm?

A variable declared in the main program that can be accessed from all parts of the program.

A memory location used to store data that does not change during program execution.

The step-by-step design of a solution to a sub-problem, or the rules to follow to solve the sub-problem.

The technique of breaking down a large program into a series of more manageable sub-problems.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What distinguishes a 'local variable' from a 'global variable'?

A local variable is stored in a location in memory and has a lifespan that lasts the entire time that program is running, while a global variable does not.

A local variable can be accessed from all parts of the program, while a global variable cannot.

A local variable is assigned a new location in memory each time it is declared, while a global variable is not.

A local variable is declared in a sub-procedure and can only be accessed from within that sub-procedure, while a global variable is declared in the main program and can be accessed from all parts of the program.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the difference between static variables and dynamic variables?

Static variables are assigned a new location in memory each time they are declared, while dynamic variables are not.

Static variables are used to store data that does not change during program execution, while dynamic variables store data that can change.

Static variables have a lifespan that lasts the entire time that program is running, while dynamic variables have a lifespan that ends when the sub-procedure ends.

Static variables are declared in the main program, while dynamic variables are declared in sub-procedures.

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are constants in the context of programming?

Memory locations used to store data that can change during program execution.

Memory locations used to store data that does not change during program execution and should be given identifiers in UPPERCASE.

The step-by-step design of a solution to a sub-problem.

The technique of breaking down a large program into a series of more manageable sub-problems.