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

4.7
stars
1,356 ratings

About the Course

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact. 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....

Top reviews

AK

Dec 13, 2022

I recommend this course to everyone who wants to learn about Computation Thinking in an effortless manner. I am delighted with this course. Thanks to UPenn and Coursera for giving me this opportunity.

J

Dec 18, 2018

Excellent course for beginners with enough depth, programming and computational theory to increase their computer science knowledge to a higher level. It builds a good foundation of how computers work

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351 - 375 of 456 Reviews for Computational Thinking for Problem Solving

By Cleefton B

Dec 1, 2019

Excellent!

By CHIEW Z Y

Feb 27, 2023

excellent

By Pn

Aug 3, 2022

great job

By Satish v

Sep 3, 2021

excellent

By Tran N Q A

Jun 24, 2021

Very good

By Abu S M H

Jan 13, 2020

Excillent

By KSHETRASRI N

Sep 2, 2021

its good

By Gregory S

Mar 14, 2021

Great

By James L

Mar 30, 2020

GREAT

By Mohammed A M Y M

Oct 20, 2023

good

By 김동범

Nov 9, 2022

Good

By 강지희

Apr 3, 2022

good

By Trương Q T

Feb 18, 2022

Good

By SAI M K R

Sep 29, 2021

nice

By RISHI K S

Sep 14, 2021

good

By LAXMIPUNEETH K

Sep 13, 2021

nice

By Vinh N P

Aug 6, 2021

nice

By RealHuyLe

Jun 21, 2021

Good

By Tuấn T M

Jun 4, 2021

good

By Nguyên N N T

May 29, 2021

good

By Heather J P

May 30, 2023

N/A

By Krusha R

Sep 8, 2021

b

By SHUBHAM P

Sep 7, 2021

5

By Jennifer S

Jul 25, 2021

PROS: The course description appropriately targets beginners to the world of computational thinking and problem solving. The instructors provide a variety of universal examples to help students understand the step by step process leading to an introduction to python programming. The units are broken into very manageable lessons followed by quizzes and projects to assess understanding and provide an opportunity to apply what was incrementally learned.

CONS: There are jumps in content area knowledge when asked to move from instructional to mathematical logic. Personally, I had to do some googling to relearn basic mathematical skills to complete tasks successfully. It would have helped to have a transition or an example to refresh my math skills from over 40 years ago. Also, as an educator, I'm all for a peer review - especially, when peers are offering constructive criticism. Unfortunately, in this forum (not just UPenn Coursera courses), most students are just racing to get through the course and clicking on complete. I haven't any qualms with losing points to learn the error of my ways, but I lost a point to someone that commented, "Great Job!" without further explanation. With that said, there is also some discrepancy between the prompts and the rubrics. However, once you learn what to look for in the pattern of instruction and assessment, it's fairly easy to adjust.

By Kingshuk D

Jul 24, 2020

The first 3 weeks were good content and testing, though i would request more questionnaires to test all concepts introduced. though i believe the content visuals & explanations could be improved, but that generally applies to most things we do anyway. Improvisation is a continuous process.

There is something humourous about the 4th week. The content and exercises appear to have been squished in with the same amount of haste like that of a student wanting to just finish the course( I was one of the students myself , so there!). The forum response rate went down as well (understandably!). In my humble opinion, the 4th week needed to be a bit more elaborate by at least 1 more week. More exercises with smoother notching up of complexity of exercises, testing out all possible concepts so that they get embedded deeper into the students' thought process irrespective of whether they take up computing later or not.

Thank you big time, Professors! :)