9.1 Computational Thinking Skills Cambridge iAS 9618

What is the primary purpose of abstraction in computational thinking?

• To simplify complex systems by focusing on essential details.

• To create detailed step-by-step instructions for solving a problem.

• To store large amounts of data efficiently.

• To break down problems into smaller, less complex systems.

Which of the following is a key benefit of abstraction?

• It helps manage complexity by hiding unnecessary details.

• It increases the amount of detailed information required for a system.

• It makes every part of a system visible and accessible.

• It removes the need for testing and debugging.

Which of the following is an example of abstraction in programming?

• Using a function to perform a task without worrying about its internal details.

• Writing out every line of code that a program will execute.

• Creating a detailed description of every object in a system.

• Using a variable to store every piece of information individually.

What does abstraction help a programmer focus on?

• The essential details of a problem or system.

• The minor details that don't impact system performance.

• The physical devices involved in the system.

• The specific hardware configurations of the computer.

What is an abstract model in the context of computational thinking?

• A simplified representation that includes only the relevant features of a system.

• A detailed map showing every component and interaction of a system.

• A physical prototype of a computer or machine.

• A diagram showing all potential outcomes of a program.

Which of the following would NOT be considered an abstraction?

• Writing every single step of a long calculation in code.

• Using a function to simplify a repetitive task.

• Hiding the details of how a data structure works in a program.

• Creating a class in object-oriented programming to model real-world objects.

Which of the following best describes decomposition in problem-solving?

• Breaking a problem into smaller, manageable sub-problems.

• Ignoring the complexity of a problem and solving it all at once.

• Focusing only on the final solution without considering the process.

• Combining multiple problems into a single, large problem.

Why is decomposition important in computational thinking?

• It allows complex problems to be tackled step by step.

• It leads to more complex solutions that are harder to manage.

• It discourages breaking problems into smaller parts.

• It reduces the need for problem analysis.

What is a program module in the context of decomposition?

• A separate part of a program designed to solve a sub-problem.

• The entire program that handles one large task.

• A function that performs all parts of the problem simultaneously.

• A loop that continuously solves a problem without separation.

Which of the following is an example of decomposition in programming?

• Breaking a program down into functions that each handle a specific task.

• Writing one long function that handles every part of the problem.

• Avoiding the use of functions and performing all tasks in the main program.

• Combining all program code into a single large block.