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Learner Reviews & Feedback for Designing, Running, and Analyzing Experiments by University of California San Diego

3.6
stars
506 ratings
185 reviews

About the Course

You may never be sure whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design user-centered experiments, how to run such experiments, and how to analyze data from these experiments in order to evaluate and validate user experiences. You will work through real-world examples of experiments from the fields of UX, IxD, and HCI, understanding issues in experiment design and analysis. You will analyze multiple data sets using recipes given to you in the R statistical programming language -- no prior programming experience is assumed or required, but you will be required to read, understand, and modify code snippets provided to you. By the end of the course, you will be able to knowledgeably design, run, and analyze your own experiments that give statistical weight to your designs....

Top reviews

PP
Nov 17, 2020

One of the best courses I have taken in relation to UX. Very good design, engaging lectures and examples, and well designed exams. I learned alot and enjoyed listening to Dr. Webbrock. Kudos to him.

DS
Jun 3, 2017

This was really useful. The course was well structured and provided excellent real-life examples that are easily transferrable to other scenarios. Keep it up!

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101 - 125 of 182 Reviews for Designing, Running, and Analyzing Experiments

By Shirley W

Sep 8, 2020

Indeed a tough bite!

It's a big leap into the wild sea of experiment design and analysis especially I don't have many memories of statistical analysis in university.

But the instructor has made it friendly for me to onboard and tackle the problems.

This is just a start. I think for an Interaction designer to understand the language that analyst speaks, we still got a long way to go.

By V.G.A. v d M (

Sep 8, 2016

Great course! It was difficult, but mostly due to my lack of basic knowledge about statistics. A primer lesson would have been great. But with some research on some topics on my own I could complete the course with a sufficient understanding of the concepts.

I found the lectures and assignments to be very clear and concise. Props for the professor ;)

By Luis A G

May 18, 2017

The video lectures and the r code supplied are of excellent quality, and the concepts were explained in a very simple and concise way. Despite this, the Professors' participation in the Discussion Forums was nonexistent, which in some cases was very necessary since some of the quizzes required some explanation.

By Cirus I

Apr 1, 2019

A good course providing the fundamentals for doing tests of proportions and analysis of variance. The former is well covered; the latter, being a bigger subject, in a bit less detailed manner as complexity increases. The accompanying R code provides a good basis with which to further investigate.

By Jess C

Apr 29, 2017

Tough course to get through and very different to the others in the specialisation but knowing about statistics has given me a different view of the world and I have really gained something from doing it. I can hold reasonable conversations with data analysts and the like now.

By bedo

Aug 23, 2017

Great course. The title is speaking and I found what I was looking for.

Great balance between theory (not much) and application (a bit more).

I used different statistical tools in different situation,

everything in R (you mast have a bit of knowledge of it).

Recommended.

By Holly D

May 1, 2016

This course was put together with lots of thought and care, and I appreciated the thoroughness of the files and assignments. The content was quite dry, and I'm not totally confident in my abilities to execute the tests in real life.

By Denys K

Mar 29, 2017

Some times i felt lack of explanation. Because there is a lot of math. And quizzes are too big (10 + 32 questions on Week 7). But overall i would say that this course is the only one to which i will definetly come back

By Alice

Dec 27, 2019

It's a hard course. It's better to have some statistic knowledge. I got a big picture of various methods after finishing this course and I think I need to search for more material to better understand them.

By Ram

Feb 27, 2019

Without any background in R programming and experiment design, I am able to learn a lot of useful stuff in this course. I wish the last three lessons and quizzes are a little more beginner friendly.

By Lucille

Jul 2, 2020

This course covers a very wide range of statistical methods but it could use more references to explain in more detail the different tests used. Overall this is a good overview.

By Aswin J E

Sep 9, 2020

While the course if useful as an introduction to spectrum of tests used in experiment design, heavy external reading is required to truly understand the concepts in depth

By Louis S

Nov 8, 2017

Great module but it was very difficult for me as I am a 'non-coder' and R Studio was at times very buggy, so my suggestion is to structure the course differently.

By Yao W

Jul 23, 2017

Students need to acquire additional knowledge to really understand the content.

The courses tend to deliver arcane content in a very sketchy way.

By Javier I R

Oct 20, 2020

Great course. There is some mistakes in some of the quiz. Nevertheless, the professor gives swift feedback to the questions send.

By kumku q

Oct 26, 2017

I have noticed some of the tests require knowledge that is gained in the next week. I would suggest fixing that.

By Andrea L

Jun 17, 2016

The instructor for this course was great. He was very responsive to students' questions concerns.

By Ken O

Oct 17, 2016

Designing experiments wasn't what I thought, and had a very steep learning curve.

By riley i

Mar 14, 2016

Thank you for designing a course that demonstrates that UX is not just painting!

By Vin

Jul 29, 2018

Great course, a little too long compared to other courses

By ujjwal d

Mar 23, 2019

Very very helpful for my game design project.

Thank you.

By Guyin L Y

Aug 31, 2018

More comprehensive than in-depth.

By Mohini D

Jul 11, 2020

Very analytical and challenging!

By Saira B G

Aug 19, 2016

It looks great

By Yemao

Aug 8, 2019

Although the lecturer has explained many theoretical aspects regarding experiments preparation and analysis well in the course, I honestly don't enjoy this course. The reasons are: 1. this is a stats course to a large extent. So you better have a good understanding of stats using in psychological studies. Otherwise you will GET LOST. 2. This course uses R instead of Python. If you are R novice like me, you WILL HAVE trouble installing packages, modules or using them because of non-compatible version of R etc. The lecturer sometimes will explicitly point out the "right" codes to execute, but it did not work as many other students suggested. Then you asked a question in the forum but unfortunately you still dont get any answer even after you complete this course. In my opinion this also shows poor preparation of the course materials and lack of updating teaching/exercise materials. Copy and paste code seems to become the pattern for completing course exercises, but i really doubt how much you can really apply for real-world cases. With all due respect this course shows a huge contrast with previous course in the interaction design specialisation and really make me feel a bit disappointed.