Chevron Left
Voltar para Idealização, Execução e Análise de Experimentos

Comentários e feedback de alunos de Idealização, Execução e Análise de Experimentos da instituição Universidade da Califórnia, San Diego

3.6
estrelas
562 classificações
214 avaliações

Sobre o curso

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....

Melhores avaliações

PP

17 de nov de 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.

MS

28 de nov de 2020

Great course.\n\nHighly recommended. It was very clear and I'm very thakful because there were many subjects I only understood partially before this course but are now very clear to me.

Filtrar por:

126 — 150 de 211 Avaliações para o Idealização, Execução e Análise de Experimentos

por Andrea L

17 de jun de 2016

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

por Ken O

17 de out de 2016

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

por riley i

14 de mar de 2016

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

por Vin

29 de jul de 2018

Great course, a little too long compared to other courses

por Ujjwal D

23 de mar de 2019

Very very helpful for my game design project.

Thank you.

por Lauren Y

31 de ago de 2018

More comprehensive than in-depth.

por Mohini D

11 de jul de 2020

Very analytical and challenging!

por Saira B G

19 de ago de 2016

It looks great

por Yemao

8 de ago de 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.

por Calogero A

22 de fev de 2022

Seeing all the negative reviews of this unit really discouraged me, but now, having completed it with full marks with zero prior experience in stastistical analysis, I think the hate is unwarranted.

I do agree that this unit feels out of place in this specialization, and I'd have preferred just a general overview of the topic. But the course is well paced, the instructor very clear, and the provided files very helpful when taking the assessments.

That said, a few of the assessments were at points frustrating and a couple questions required the wrong answer to give you the point (little tip: if you're sure you have the correct result but the quiz won't accept it, try truncating rather than approximating).

All in all I'm glad I did it and I'm sure being able to add some R experience on my CV isn't such a bad thing.

por Santiago B

24 de mai de 2019

I have to be honest, I hated this course mostly because I suffered from the start to the end, but don't get me wrong, the concepts are great and very interesting, I didn't know how much information can you get from a simple CSV file; the thing is the course is based in the RStudio tool and I struggled very much with it; missing libraries, constant crashes, and at some point I lost the thread, the concepts start to seem too complex for someone who hasn't much experience with coding so my motivation went away and at the end I was just following instructions to make it through. Maybe if the concepts stay centered on the meaning and not the tool this would be more enjoyable. But I'm very grateful because now I have the sense of data and its importance to backup important design desitions, Thanks!

por JoAnne

15 de mai de 2017

The content of this course is quite difficult, especially if you are new to R, and there are no moderators or TAs available to respond to questions or discussions about the content. Nobody replies to the students in the discussion forums. This is surprisingly inconsistent with the rest of my experience with the courses in this specialization. I would warn anyone thinking about taking this lengthy course to realize that you will be alone throughout the class and you should be ready to figure things out alone. Also, during Weeks 7-9, the quiz questions don't seem to relate to Prof. Wobbrock's lecture material at all. I took copious notes and that didn't help me identify where the quiz questions came from.

por Seetha T

20 de jun de 2017

The professor for the course was able to explain well on most of the concepts on the r programming behind the designing, running and analyzing experiments. He went a little fast on the videos but I was able to catch up by reviewing the transcripts and pausing /playing the videos. The part I was not happy about was that there was no mentor in this course who helped out the students on the discussion board in facing issues of setting up r programming and r studio and also understanding how to do r programming. I was a bit surprised that R is used in interactive design because I heard the main programming languages when it comes for UX researchers and designers are focused on java, c++, and sql.

por Jade O

17 de abr de 2022

This was a challenging course for a beginner/novice but definitelyl informative. My rating is largely due to the assessment practices. There were errors in the quizzes, and there was often questions on the quizzes that weren't covered in the lectures - in particular - questions on the week 9 quiz. If you're wanting to "extend" students knowledge, do not do it in marked assessments, rather, do it in assignments and/or practice activities. Utlimately this, along with the higher level of R-Studio knowledge that was expected, were among my biggest frustrations. Content was good, if you know R-Studio a bit, it'll be much easier to manipulate the code/formulas.

por Nicholas I

3 de nov de 2017

Great intro to R-Studio entering pre-made functions with data tables. I feel a little more familiar with basic concepts for quantitative experiments but in terms of understanding the actual statistical functions I still don't feel confident running know when and where to apply the statistical analysis to the data (Seems out of scope for this one course and I would take this course again for more practice). This was the most difficult course in the specialization. Working in R-studio is tricky because you need to know how run the correct version of R, and how to install missing packages in order to run the functions used in the quizzes.

por Matthew S

17 de jan de 2017

Interesting to try R hands on. Could have made more definitive statements on the usefulness of each test (there was lots of 'you could have a look at this analysis, or this one, or this one' without covering why each one would be particularly good for this case). Some of the later exercises also made quite of a leap in terms of what you were expected to know about R syntax, although the follow up answers were good if you didn't understand what was expected.

por Muhammad A I

16 de jul de 2017

Too technical for my taste. I understood the concepts but as we progressed, the code itself was extremely complicated with A LOT to grasp within a weeks time. I relied on the hints and code keys provided in examinations. I would highlighy recommend either rethinking if code should be part of this. Or improve how we can test/ increase the friendliness. No offence intended, just want to help :)

por michele w

12 de nov de 2016

This module took me on an interesting journey with lots of twists and turns. While I love challenges and learning otherwise I wouldn't have taken this course. I'd like to suggest the following: mentor to assist students, review of codes I found lots of glitches, one quiz rather than two, cut back on timeframe. I'd like to give more stars but am being generous with 3 stars.

por Cristine L M

12 de fev de 2019

This is a very interesting and an important area in the Interaction Design Specialisation. This should have a dedicated specialisation on its own. While the exercises and the lectures are pretty decent,I don't think it's adequate to really grasp and master this subject. However, it's still a pretty good introduction enough to give someone a basic working knowledge.

por Raluca M

7 de ago de 2019

Very, very, difficult. I'm finding myself having a harder time to pass this than structural design in architecture university, and that says a lot. At least in school we had the option to ask other students, but online, this resource is way less present. I did start getting some principles, but this needs rebalancing in my view.

por Alexa B

28 de dez de 2021

This one felt really out of place with the rest of the courses. I feel like 2-3 weeks tops would have got me the basic knowledge, I've also heard from multiple people that Python would be preferable to learn for statistic analysis over R. Overall, just SO happy to have this one done so I don't have to keep stumbling through R.

por Mirjana P

27 de abr de 2016

I was able to follow the course and keep the pace but I got lost on factorial ANOVA. The professor is great but the course feels rushed through. It would be great if more time was spent on actual explanation of main concepts, since many here are the beginners in stats. I will try again, hopefully will get it this time.

por Hossein R

14 de jun de 2017

Great overview of different analysis, however I would not be able to do the tests without trail and error, and the available codes! 9 weeks, but it went too fast through the course, i would suggest to either make the course shorter to go deep in a few concepts, OR make it much longer so learners can understand.

por Amy B

22 de jun de 2020

This came slightly unexpected, and was quite challenging which is good. It was a lot condensed into a short period. It would have been nice if it was updated as their were a few issues because of it but not a huge deal - the forums were helpful.

por Ana S R C

11 de mai de 2017

There is alot o f bugs on the exams and some questions are really confusing about what the point is about. I liked the way the professor explain every thing and theme was so simple even for someone that has not a background in coding like me.