Computer 9th Chap 2 : Topic 2.9 - Maryam Publications

Computer Chapter 2 : Topic 2.9

Solve simple and complex problems computationally.

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Which action best represents applying computational thinking when defining a complex problem in computer science systems analysis?

A) Writing program code before understanding requirements

B) Selecting a programming language first

C) Ignoring problem constraints and focusing only on output

D) Breaking the problem into smaller, understandable components logically

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How does abstraction help in refining a computational problem during system design and analysis?

A) By eliminating the output requirement completely

B) By adding unnecessary implementation details

C) By replacing the need for input data

D) By focusing only on essential information and removing irrelevant details

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Which computational thinking principle is most useful when identifying patterns in a problem to refine its structure?

A) Compilation

B) Debugging

C) Encryption

D) Pattern recognition

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What is the main purpose of decomposition when refining a poorly defined computational problem?

A) To merge all parts into a single solution

B) To increase program complexity

C) To remove the need for logical thinking

D) To divide the problem into smaller sub-problems for easier handling

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Why is iterative refinement important in computational thinking during problem-solving?

A) It avoids analyzing the problem completely

B) It eliminates debugging processes

C) It allows continuous improvement of problem definition and solution design

D) It removes the need for algorithms

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Which step best shows applying computational thinking to refine a problem definition?

A) Writing final code immediately

B) Selecting hardware components

C) Revisiting and improving understanding of inputs, processes, and outputs

D) Ignoring system requirements

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How does logical thinking contribute to refining a computational problem?

A) By adding random conditions to the system

B) By removing all input data

C) By avoiding structured analysis

D) By evaluating facts and improving decision accuracy

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Which of the following best describes pattern recognition in problem refinement?

A) Writing random solutions without structure

B) Increasing system randomness

C) Finding similarities between current and previously solved problems

D) Identifying hardware faults in a system

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What is the correct order of applying computational thinking principles in problem refinement?

A) Compilation → Execution → Storage → Output

B) Output → Input → Process → Testing

C) Algorithm design → Input → Output → Abstraction

D) Decomposition → Pattern recognition → Abstraction → Algorithm design

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Why is defining a problem correctly important before applying computational thinking techniques?

A) It removes need for algorithms

B) It ensures correct identification of inputs, outputs, and constraints

C) It allows skipping analysis completely

D) It replaces debugging

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Which example best shows abstraction in refining a real-world computational problem?

A) Ignoring user requirements completely

B) Writing code without planning

C) Focusing only on essential features of a banking system like account balance and transactions

D) Including every irrelevant detail of a system

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What role does algorithm design play in refining a computational problem?

A) It increases system randomness

B) It removes need for input data

C) It eliminates logical thinking

D) It creates step-by-step instructions for solving the refined problem

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Which situation best demonstrates refining a computational problem using decomposition?

A) Ignoring system requirements

B) Writing final output directly

C) Dividing a school management system into attendance, grading, and fee modules

D) Treating the entire system as one large task

14 / 14

How does computational thinking improve accuracy in problem definition?

A) By eliminating logic

B) By avoiding analysis

C) By ignoring constraints

D) By systematically analyzing inputs, outputs, and processing requirements

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