Computational Thinking

Which of the following best describes 'problem recognition' in computational thinking?

• Breaking a problem into smaller parts

• Identifying and understanding the existence of a problem

• Ignoring irrelevant details

• Testing different solutions randomly

What is 'problem decomposition'?

• Combining several problems into one

• Breaking a complex problem into smaller, more manageable parts

• Ignoring the problem entirely

• Making a problem more complicated

The 'divide and conquer' approach is best described as:

• Solving a problem by trial and error

• Dividing a problem into subproblems, solving each one, and combining the results

• Ignoring the main problem and focusing on details

• Using only one method to solve a problem

Which of the following is an example of 'abstraction' in computational thinking?

• Focusing on every single detail of a problem

• Removing unnecessary details to focus on the main idea

• Writing code without planning

• Guessing the solution

What is 'backtracking' in problem solving?

• Trying all possible solutions at once

• Reversing steps when a solution path leads to a dead end

• Ignoring failed attempts

• Solving problems without any plan

Which of the following best defines 'data mining'?

• Physically digging for minerals

• Extracting useful patterns and information from large sets of data

• Destroying data to save space

• Ignoring data that is not immediately useful

A 'heuristic' is:

• A guaranteed way to find the perfect solution

• A practical method to find a good enough solution quickly

• A way to make a problem more complex

• A method that always fails

What is the purpose of 'performance modelling' in computational thinking?

• To make a problem more difficult

• To predict how well a solution or system will perform

• To ignore the efficiency of a solution

• To randomly select a solution

'Pipelining' in computational thinking refers to:

• Performing tasks one after another, never overlapping

• Arranging tasks so that multiple steps are processed simultaneously in different stages

• Ignoring the order of tasks

• Solving only one problem at a time

How can 'visualisation' help in solving computational problems?

• By making problems harder to understand

• By representing data or processes visually to make patterns and solutions clearer

• By hiding important information

• By focusing only on text-based solutions