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Avis et commentaires pour l'étudiant pour Concevoir, éxecuter et analyser des expériences par Université de Californie à San Diego

427 notes
156 avis

À propos du cours

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....

Meilleurs avis


Jun 04, 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!


Jul 17, 2019

Very difficult content of the module, but the teacher explained the issues clearly. Tests were also helpful in understanding and mastering the material.

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1 - 25 sur 151 Examens pour Concevoir, éxecuter et analyser des expériences

par Jared G

Mar 07, 2019

I feel like the course overall was important. I'm glad I have the basic idea of how I can crunch research data using R. However, the course could be difficult and perhaps a bit deep for many people looking toward UX design. The instructor suffers from the academia cliche of having so much knowledge and skill that he can't always help students on a very introductory level. Case in point reading the class notes (a task usually unimportant and ignored by most users) is required, and yet even those notes are written from a perspective of knowledge of the subject. It's a bit like coming into a Spanish 1 class, looking to learn a bit about Spanish and the professor hands you a syllabus of which parts are written in Spanish. While I recovered from this shock, I think for many this snowballs into growing frustration and failure.

Add to this the complexity of coding across different computer operating systems and versions. There are times when you get an error and you don't know why. In a classroom the professor might tell you, "oh you forgot to _______". Here you can ask and you might get a response days or weeks later. It could also get so complex that even the professor is not sure what is going on. I had an error and there was no resolution, I had to google and solve it myself.

Overall, I'm glad I took the course. I had some really painful moments but I also solved problems and completed complex tasks, which felt rewarding. I definitely appreciate the approach of the professor, splitting time between lecture and hands on and having hands on assessment at the end.

par Richard H

Dec 21, 2018

I liked the professor. He explained things well. My concern with this course it the understanding of it. I can do command line commands but figuring out which commands to use for each quiz question is complicated. The first few weeks I figured out which sections of the coursera.R file to use. Later weeks were more complicated. Perhaps files with commands and comments on a per week basis would be best. Not giving the answers to the student, but at least giving more context per file would be very helpful.

par Audree L

Aug 11, 2018

I was enthusiastic about this class but it ended up being useless to me. While the structure allowed me to jump right in R, I felt like without any prior knowledge of statistics, I was just copy pasting without really understanding the tests, and why to use one rather than another. I guess going deeper into what things mean, or adding more context to the tests would help for designers with little background of stats. For example, even though it was explained, it would have been nice that every time we had a new dataset, to take the time to explain what type of survey it was, vs the previous ones, and to map it to the grid. This was assumed as a given, but I feel I would still have trouble figuring out which test to use on my own. So overall this was a good class but missing some content for the beginners.

par Jon M

Feb 04, 2018

The instructor and Teaching Aids haven't participated in the learning Forums for over a year- this is the most difficult course in the Specialization however there is little to no support for the students. I have a background in engineering so I faired well in the course, but for many- not so much! Course would also benefit from a more robust intro to R Programming. Thank you so much for the course , I really appreciate it! I'm only sending these criticisms in order to help - I personally did very well in the course.

par Sourav C

Apr 29, 2019

The worst course of this specialisation. Instead of emphasising on the principles of statistical methods, this course forces you to use R and RStudio.

par Ingvar K

Nov 14, 2017

I've been going through "Interaction Design" courses from University of California, San Diego since course one in order to get the specialisation. And each course was interesting, insightful, challenging. I really want to get the specialisation and I worked hard to get to this point. In total it took me around two years with pauses and breaks.

However, the last course called "Designing, Running, and Analyzing Experiments" is something different and makes it impossible for me and many others to finish. Because it requires programming and statistical skills. So for it to be finished I need to take a separate course on R language. I'm not willing to give up, but this particular course requires special skills which not everyone has. I'm not sure if this R language will be in the capstone project as well but it's just impossible to finish. Moreover, if you go to the discussion forums not only you will see that people can't finish even second week but also that many students can't even install the software that they don't know how to use. I suggest all the R language materials, assignments, quizzes, videos to be removed from this specialisation. Because it requires a special preparation and skills in programming and statistical analysis which this course wasn't meant to require from students.

It's like if I would be doing a course on Microsoft Paint and the last course would be to create a 3D model of a dinosaur in Maya assuming after learning Microsoft Paint we're able to take on the Maya 3D in no time.

I was forced to study something separately just to finish this course. And I'm not planning to use the knowledge from this course. This should be a completely discreet course not related to the specialisation.

par Adolfo R

Sep 23, 2017

It's true that I've learned a lot and will never see experiments the same way again. I have new-found respect for conducting even the most simple surveys. BUT this course goes way too deep into the math and code under the hood. It's absolutely ridiculous. I almost dropped out so many times. I had to invest hours of my scarce time to complete tasks that aren't suited for an Interaction Designer, but rather for a mathematician. I'd rather spend more time analysing results and optimising the design of experiments than figuring what on earth I'm being "explained" about a bunch of intricate formulas. The analysis got completely LOST in that jungle of numbers, weird names and math jargon. Wouldn't recommend.

par Maria K

Jun 24, 2018

A tough course, especially for those who do not code. Thus, lots of work required. Sometimes there were way too many tasks (32). I gave this course 5 stars as it was a very challenging, but lots of different approaches and tests you can learn more and in depth.

par Julie B

Oct 17, 2018

This course was extremely helpful in understanding which statistical test to use when, with applications specifically for interaction design, which is what I need :) I appreciated the clear relationship between the lectures and the quizzes & assignments. The lectures also were clear. The course was broken up into doable chunks that made it easy to take while still having a full-time job.

par Alfredo H

Jan 12, 2019

This had been the hardest class ever. I don't even know how I passed but also I don't see how I can remember to use Rcode for future work within HCI

par AMIR R A

Dec 26, 2017

At first I should thank Dr,Wobbrock for his efforts. He teaches the course materials well but I think the this course is not well-balanced. Statistics is very wide concept and R Studio is big too. Although the course is longer than other courses of this specialization , i dont think it has the same output.

I become familiar with R.

I become familiar with distributions.

I know some of tests but if I want do a real world experiment I dont't know how can i start it now.

I think this course should get redesigned.

par Wilame L S J V

Jun 05, 2018

Too technical, with lots of hard concepts to assimilate in a very small time. Exercises are too hard.

par Alejandro N

Apr 04, 2019

This course is not amazing at all. It takes so much time to complete plus you do not learn much. You learn to pretty much replace some parts of a code it's already done in R. So you work with code but you don't learn how to code either. I give this course 1 star.

par Tamella H

Oct 23, 2017

I reviewed all previous courses with 5 stars but I had to give 1 star to this course Not because of the instructor and not because of the importance of the material but because of the level it os not well thought through. As a beginner designer information given here without clear explanation of how those studios and softwares work you would be a big problem for anyone who just started getting into this field. Giving us basic skills of using those tools would be more helful rather than asking us to solve problems. I finished all previous courses in less than a month and obtained so many skills and information. I am very frastrated because I was looking forward to finish this specialization.

par Stephen B

Sep 20, 2017

This course assumes too much knowledge about both programming and statistics. The tone of the instructor makes it seem like its an introductory course, but he does not provide an introduction to the concepts and methods that would give the student a proper grounding to successfully advance through the course.

Yes, this is not an intro stats course, and yes, it is not an intro R course. But what is it actually, particularly in terms of UX?

par Jacky ( H Z

Feb 10, 2019

Great course. You explained the topics very clearly!

par Faraz A K

Mar 10, 2019

as a first introduction to the analytical side of quantitative/ qualitative experimentation amazing course, pulls you in... it is tough and requires more time than what is mentioned... but totally worth it.

par Noor S R

Aug 01, 2018

Should cover how to select sample for experiments and perform experimental design test

par Maisa D

Aug 09, 2018

Really hard, but really great!

par Sharath K P

Mar 24, 2016

This course is good.

par Juliana E R

Jun 07, 2017

I could immediatly implement the concepts and instruments provided in this course to my professional activity. I must say that I have a poor training in statistics and a superficial knowledge of R, but I needed to implement more professional usertests (I'm an instructional designer with a background on education).

I really enjoyed the clear explanations; above all, how the concepts where linked to R practice, which was thrilling to me.

Thanks to the team! Great course!


par Parul K

Jul 19, 2017

Great course, easy to comprehend various tests/models and their usage! Definitely recommend to anyone running A/B tests. Would be nice to have a short video on which tests are related to multivariate testing.

par Yiqi H

Oct 24, 2016

Love it! A lot of important concept, algorithm and codes learned.

par yashar k s

Oct 04, 2016

Best Course

par Carlos M D

Sep 23, 2016

Amazing class. Covers a great deal of statistical methods and explains them in a plain/clear/accessible way with good examples.

It cuts through the chase and gives you what you need to know (the real essentials) from a practical standpoint. You will not get a lot of theory (for that, there are plenty additional courses) but you will get enough theory to select the right method for each scenario.

It will not teach you to program in R from zero (for that there are many other courses) but it will jump start you with snippets of code that you can read, understand, modify, and use.

Real useful stuff... done the proper way...