Question 1

Which of the following is a fundamental concept of computational thinking that is essential for developing intelligent systems?

Accepted Answer

Decomposition

Answer

Algorithm design

Answer

Data visualization

Answer

Critical thinking

Question 2

In computational thinking, what does the term 'abstraction' refer to?

Accepted Answer

Simplifying complex reality by modeling it

Answer

Visualizing data patterns

Answer

Collecting data from various sources

Answer

Implementing machine learning algorithms

Question 3

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

Accepted Answer

Identifying trends or regularities in data

Answer

Creating new algorithms from scratch

Answer

Generating random solutions

Answer

Ignoring anomalies in data

Question 4

What role does 'algorithm design' play in computational thinking related to intelligent systems?

Accepted Answer

Creating step-by-step instructions to solve problems

Answer

Testing software for bugs

Answer

Gathering user requirements

Answer

Designing user interfaces

Question 5

Which process in computational thinking involves evaluating the effectiveness of a solution?

Accepted Answer

Testing and debugging

Answer

Pattern recognition

Answer

Data collection

Answer

Abstraction

Question 6

In the context of intelligent systems, what does 'data representation' involve?

Accepted Answer

structuring data in a way that can be easily analyzed and processed

Answer

Creating algorithms without data

Answer

Visualizing data without context

Answer

Randomly generating data sets

Question 7

Which of the following best defines 'iterative improvement' in the context of developing intelligent systems?

Accepted Answer

A process of refining solutions through repeated testing and adjustments

Answer

Documenting the development process thoroughly

Answer

The initial creation of a solution without further changes

Answer

Gathering user feedback without changes to the solution

Question 8

What is the primary purpose of using 'models and simulations' in the development of intelligent systems?

Accepted Answer

To predict behavior and test solutions in a controlled environment

Answer

To gather real-world data without constraints

Answer

To avoid understanding the underlying system

Answer

To eliminate the need for algorithms

Question 9

In computational thinking, why is 'iteration' important when working on intelligent systems?

Accepted Answer

It allows for continuous refinement and improvement of solutions

Answer

It disregards user input in the development process

Answer

It simplifies problem-solving by ignoring complexities

Answer

It focuses on the initial design without changes

Question 10

What is the significance of 'team collaboration' in computational thinking for intelligent systems?

Accepted Answer

It combines diverse skills and perspectives to enhance problem-solving

Answer

It slows down the development process unnecessarily

Answer

It focuses solely on individual contributions instead of group efforts

Answer

It limits innovation by sticking to one approach

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