problem solving using computational thinking coursera quiz answers

Problem Solving Using Computational Thinking Quiz Answers

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• On March 3, 2024

Get All Weeks Problem Solving Using Computational Thinking Quiz Answers

Table of contents, problem solving using computational thinking week 01 quiz answers, foundations of computational thinking practice questions answers.

Q1. In your own words, define the following aspects of computational thinking: Problem Identification, Decomposition, Pattern Recognition, and Abstraction.\

Q2. Once you’ve identified a problem that may be ‘solvable’ through computational thinking,  you need to decompose the topic further by creating sub-problems. In your own words, explain  why  we need to decompose complex problems in order for a computer to solve it.

Foundations of Computational Thinking Quiz Answers

Q1. In computational thinking terms, breaking down a complex problem into smaller, more specific sub-problems is called ___________.

Q2. True or False: Computational thinking techniques can help programmers conceptualize problems before they begin programming.

Q3. In computational thinking terms, framing a problem and determining if it can be solved by computers is known as _________.

Q4. While writing a program for building a cake, you decide that some information is less relevant for your particular program. For instance, you might decide that you don’t need to know the flavor of ice cream that the cake is being served with, and you don’t need to know what color plates the cake is being served on. In computational thinking terms, this process of ignoring or filtering out less relevant information is known as _______.

Q5. True or False: When identifying a problem for a computer to solve, it is best to identify problems that are subjective or open-ended.

Q6. True or False: Computational thinking is a linear process.

Airport Surveillance Practice Questions Set 1 Answers

Q1. As discussed in the Airport Surveillance case study, computer-based solutions require questions that are specific and quantifiable. Based on these criteria, which of the following questions is most appropriate for a computer-based solution?

Q2. True or False: Asking a computer to monitor “suspicious behavior” is a specific and quantifiable problem that is suitable for a computer-based solution.

Q3. Decomposition consists of various layers of breaking down a problem. Consider managing security at a crowded public event. How would you decompose the task of identifying suspicious behavior at a concert? In other words, which of the following are possible sub-pieces of this problem? (Select all that apply).

Q4. Consider how you would further break down the task of “identifying possible weapons carried by concert-goers.” To help with this problem, you have at your disposal surveillance video from multiple angles, handheld metal detectors, and bag X-ray scanners at the venue entrances. Which of the following are possible pieces of information you will likely need to carry out the task? (Select all that apply).

Common ways of holding handheld weapons.

The value (price) of different kinds of weapons.

What do different kinds of weapons sound like?

• What material weapons are often made of?

Airport Surveillance Practice Questions Set 2 Answers

Q1. You are currently developing a new surveillance algorithm that flags illegal substances for airport security officers. You are still early in the development process, and there are some known issues with the algorithm. Given these criteria, which of the following situations would be most appropriate for testing this new algorithm?

Q2. True or False: Machine Learning is a subset of Artificial Intelligence.

Q3. In the airport surveillance case study, what kinds of technology are needed in order to identify objects and people? Please select the best answer.

Machine Learning

Q4. To solve the problem of finding suspicious packages/luggage in an airport, which elements in the video can be ignored from video analysis?

Q5. In your own words, describe (1) what an algorithm is, and (2) what an algorithm is used for.

Airport Surveillance Case-Study Quiz Answers

Q1 .Identifying suspicious behavior at an airport is a complex problem. In this case study, what was one strategy for decomposing this problem into a smaller, more manageable problem?

Q2. When designing an algorithm that will detect unattended luggage, what kind of information would likely NOT be ​relevant to this problem?

Q3. Using the following algorithm, what would happen if the luggage in one video frame is not seen in the next frame?

Q4. Since computer-based solutions require questions that are specific and quantifiable, which one of the following questions is most appropriate for a computer-based solution?

Q5. What is an algorithm? Choose the best answer:

Week 03: Problem Solving Using Computational Thinking Quiz Answers

Epidemiology practice questions answers.

In this model, S represents the number of people susceptible to infection, b represents the rate of infection, I represents the number of people infected, r represents the recovery rate, and R represents the number of people who have recovered from infection.

Using this algorithm, what changes would we expect if people stopped washing their hands and covering their coughs during flu season?

Q2. In the epidemiology case study, what was one-way decomposition was used to identify a sub-problem?

In this expanded model, the number of vaccinations ( V ) decreases the number of people who are susceptible to infection ( S ). 

Using this model, what would we expect to happen if we increased the number of vaccinated people ( V )?

Q4. When testing a new algorithm, it’s usually best to run your algorithm on a simplified test case. For instance, in the airport surveillance case study, testing a new algorithm meant scanning video with lower resolution, or scanning shorter video clips.

Describe how you might test a new epidemiology algorithm that predicted the number of people prone to becoming infected with the flu.

Epidemiology Case-Study Quiz Answers

In this algorithm, S represents the number of people susceptible to infection, b represents the rate of infection, I represents the number of people infected, r represents the recovery rate, and R represents the number of people who have recovered from infection.

Using this algorithm, what changes would we expect if more people washed their hands and covered their coughs during flu season?

Q2. In the epidemiology case study, the SIR model accounted for the number of people susceptible to infection, the rate of infection, the number of people infected, the rate of recovery, and the number of people who recovered from the infection. If we wanted to create a more accurate model for predicting the spread of the flu, what information would be most relevant for this problem?

Q3. Predicting the number of people who will become infected with the seasonal flu can be a complex problem. In computational thinking terms, describing this complex problem in such a way that it can be solved by a computer is known as __________.

Q4. In the epidemiology case study, the SIR model utilized the following information: the number of people susceptible to infection ( S ), the rate of infection ( b ), the number of people infected ( I ), the recovery rate ( r ), and the number of people who recovered from infection ( R ). This process of focusing on relevant information and ignoring less relevant information represents what computational thinking technique?

Using this algorithm, what will happen to the number of people recovered ( R ) at the end of an epidemic if we increase V at the beginning?

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Problem Solving Using Computational Thinking Coursera Week 2

In this blog you will find the correct answer of the Coursera quiz Problem Solving Using Computational Thinking Coursera Week 2 mixsaver always try to brings best blogs and best coupon codes  

Airport Surveillance CaseStudy Quiz

1. Question 1 Identifying suspicious behavior at an airport is a complex problem. In this case study, what was one strategy for decomposing this problem into a smaller, more manageable problem?

• Design an algorithm that counts how often luggage is left unattended.
• Use machine learning to track which parts of the airport is the busiest.
• Design an algorithm that can differentiate between airport staff and travelers.
• Define a specific type of suspicious behavior in quantifiable terms.

2. Question 2 When designing an algorithm that will detect unattended luggage, what kind of information would likely NOT be ?relevant to this problem?

• The length of time luggage has been left unattended.
• Whether a piece of luggage is idle or moving.
• The distance between attended luggage and its owner.
• The types of clothing people in an airport are wearing.

3. Question 3 Using the following algorithm, what would happen if the luggage in one video frame is not seen in the next frame?

• The algorithm checks to see how long the luggage has been moving.
• The algorithm generates a warning.
• No warning is given, and the algorithm checks if there are more objects to categorize in the frame .
• The algorithm checks to see if the luggage is accompanied by a human.

4. Question 4 Since computer-based solutions require questions that are specific and quantifiable, which one of the following questions is most appropriate for a computer-based solution?

• What kind of luggage is the most aesthetically pleasing?
• What kind of behavior is suspicious?
• How many people have entered the airport in the past two hours?
• Why is flying better than driving a car?

5. Question 5 What is an algorithm? Choose the best answer:

• The process of identifying parts of a problem that can be ignored when approaching a problem.
• The process of identifying patterns that can lead you to a potential solution.
• The breaking down of a large, complex problem, into smaller more manageable problem.
• A process or defined set of rules used by a computer for solving an identified problem.

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In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program.

This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

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Computational Thinking Test Questions With Answers

. Play the amazing computational thinking test with informative questions with answers quiz. Do you know what computational thinking is or what about abstraction? There are many questions covered related to the problem-solving topics in this quiz. If you think you can analyze complex problems and provide possible solutions to those problems, then this quiz is for you. So, what are you waiting for? Start the quiz and analyze where do you stand when it comes to solving computational thinking questions.

Computational Thinking Questions and Answers

Computational thinking is.

Programming

Thinking like a computer

Logically solving problems

Rate this question:

Which of these is an example of abstraction?

Use a pre-written library of procedures and functions to perform operations such as sorting and searching.

Ignore the colour of a player token in a snakes ladder game model.

Break a complex problem into modules using top down design

Subdividing a problem into smaller tasks that different teams can work on independently.

What is _______ taking a complex problem and breaking it down into a series of small more manageable problems called?

Decomposition

Abstraction 

Pattern Recognition 

What is __________ problems looked at individually, considering how similar problems have been solved previously called?

Abstraction

Pattern Recognition

What is _______ focusing only on the important details, while ignoring irrelevant information called?

Algorithms 

What is _______ simple steps or rules to solve each of the smaller problems can be designed called?

Decomposition makes problems ___________..

Better to code 

Harder to solve

Easier to understand 

More manageable

Which of these are pillars of computational thinking?

Decomposition: Breaking down data, processes, or problems into smaller, manageable parts

Abstraction: Identifying the most important details and discarding the unimportant aspects to make the solution manageable

Functional programming - treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data

Pattern Recognition: Observing patterns, trends, and regularities in data

Algorithm Design: Developing the step by step instructions for solving this and similar problems

Pattern recognition involves finding what 2 things among small, decomposed problems?

Similarities

The more patterns we can find, the _____________ and _______________ it will be to solve our problem. (pick all correct answers).

Which of these is an example of decomposition.

Break a program into procedures and functions

The layers in a network protocol stack

Which of these are true about algorithms?

The steps/instructions can be ambiguous

Algorithms rely heavily on syntax

Python like code cannot be used to write an algorithm

The lowest level of the algorithm can be expressed any way as long as the instruction/step is clear and can be treated as a simple computational process.

Algorithms are about expressing thinking steps not syntax

Which of the following is not a component of computational thinking?

Pattern recognition/Generalising

Algorithmic thinking

Define the term abstraction within computational thinking.

Adding numbers together

Representing real world problems in a computer program, using symbols and removing unnecessary element

Taking a real world problem and designing a computer program that exactly replicates every part of that problem in the computer

Performing multiple calculations on a list of variables

What is a FLOWCHART?

A visual representation of an algorithm.

A series of shapes.

A diagram that shows abstraction.

A diagram that shows selecting a burger.

What does an arrow represent in a FLOWCHART?

A school database has lots of information on students, the data manager needs to use abstraction what data should she leave out.

Guardian's phone numbers

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Learner Reviews & Feedback for Problem Solving Using Computational Thinking by University of Michigan

About the course, top reviews.

May 19, 2021

This course is very dummy-proof. As someone who never learns about computational thinking, this course helps me to understand the materials and the cases provided in a very simple way. Thank you!

May 11, 2021

though the peer review system might trouble you but it was a great learning experience reading others graphical organizers help me understand how there can be a different outlook to same problem

1 - 25 of 358 Reviews for Problem Solving Using Computational Thinking

Feb 23, 2021

The course is made as boring as possible and absolutely does not capture. As if they were deliberately inflated with unnecessary and useless information to a certain volume.

All examples are sharply negative - terrorists, human trafficking, epidemics, natural disasters. Yes, computational thinking can help in these cases. But it also helps in emotionally positive situations. You don't need to paint a non-existent world, but keep balance.

After completing this course, I was very angry and disappointed, although I finished it in two days. There is another course here, from another university on this topic. And it gave me much more in understanding the issue and inspiration for applying the principles of computational thinking in life.

By RODRIGUEZ G C A

Feb 2, 2021

A very good course.

It really gives you a full outlook about the way you must manage a problem and possible ways to model a solution based on computational implementation.

Feb 4, 2021

This course gave me a clear idea on how to think and solve different problems before programming them. This course made me think twice and code once. Really loved the way the instructors explained the subject and thanks to coursera for making this course avaiable on your site.

By Prakhar K

May 16, 2020

It was a great experience for me and i have gain lots of knowledge through this course in a very efficient way so thankyou so much.

Jul 4, 2020

The lessons were somewhat tedious mainly because the teachers' tone of voice is monotonous and the visual support is not significant.

May 2, 2020

It's a very great course. Highly recommended for those who want to start learning about how computer works and learn programming. Thanks! University of Michigan and Prof. Chris Quintana for conducting such a great course.

By Philip R

May 31, 2021

The course is highly enlightening. It has helped me see that a lot of problems can be solved using computational thinking. I will recommend to anyone willing to gain knowledge in this area.

By Hananeel B

Jan 28, 2021

This is a very good course for everyone that intends to make his decision making smart using quantifiable terms.

By Prudhwi R K V

Jan 31, 2021

Super Course Ever I done in coursera fentastic every beginners should do this course .

By Thitiwat C

Apr 9, 2021

Highly Recommend for those who want to have better communication with your programmer

By Marisel C D

Feb 6, 2021

Excelente curso! Es una muy buena base para el trabajo en cualquier área

Good course.

By Vitthal J

Apr 23, 2021

Boring... should have animations to elaborate. Video duration could be reduced. The course should be chunked into smaller parts. No offense, but the video presenter should be energetic, dynamic and should have excitement in his voice - this is a new era of learning and recording real unenthusiastic professors in an online course is a failed strategy.

It is understandable that strategist in the university think it is best to create this courses with the professors who has knowledge in the domain, but knowledge is not enough these days.

OVERALL EXPERIENCE OF A COURSE is important, rather than reading the same old boring concepts by an unenthusiastic person. (Again no offense, it's just a feedback)

Jan 15, 2021

Not what I thought it was.

Mar 7, 2021

This course allows us to build a computational thinking process to solve problems. It helps us to build a complex problem solving skill, after the course, my thinking process is different, I will decompose a large problem into sub-problems and then figure out the most effective solution or outcome. This skill is one of the most sought after soft-skills in recent working environment.

Jan 29, 2021

Definitely Highly recommend everyone to enroll in this course certificate as it covers 3 Case Studies of Real World Applications that uses Computational Thinking to solve Problem Solving. The real world implications are astounding and you will enjoy knowing the skills you learn here will help you provide valuable solutions to complex problems.

By Olayibowale S

Apr 30, 2021

This course is a very good one for everyone because we all have one or two thinking to do! It makes one express the critical and analytical skills because you are able to choose what you want and why you want it. Thank you University of Michigan for putting up this course! It was enlightening and easy to complete!

Feb 18, 2021

I feel that I have greatly grown in confidence and I am so happy that I took this course. It really sets me up for the career I wish to attain in technology and has got me thinking differently than what I usually do.

May 26, 2021

A brilliant course. I had no idea about computational thinking and this course was an eye-opener. The instructors are top-notch and the learning is just amazing.

highly recommended!

May 1, 2021

Very informative and educational. Not just book based but it applies its lessons to real life situations which helps in understanding the lessons well and learning new information.

Jan 25, 2021

I'm very proud to be one in the family of coursera I had learned the course of computational thinking with a good material and experts in this field

By ravpreet m

a good course for beginners to start with

By Taylor C

Hmmm, I think I learn a tool that needs to be further developed. Computational thinking requires critical thinking skills, the deeper you can think, the better. Course material is easy to follow.