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Designing, Running, and Analyzing Experiments に戻る

カリフォルニア大学サンディエゴ校 による Designing, Running, and Analyzing Experiments の受講者のレビューおよびフィードバック

3.6
465件の評価
166件のレビュー

コースについて

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....

人気のレビュー

MP

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.

ZW

Jul 26, 2017

Have to watch three times to keep up because it is really hard for people without former experiences... Anyway it is worth it

フィルター:

Designing, Running, and Analyzing Experiments: 126 - 150 / 162 レビュー

by Nate L

May 24, 2017

Way to much stuff for students who haven't learned statistic before.

9 weeks are just too short for these abundant material.

by Ymmannuelle V

Jul 27, 2017

While it's a fun course (and challenging), retaining all the information could be a challenge if not put into practice.

by Candice L

May 06, 2016

Not finding it very useful, but it's good to know about the concepts and theories for each type of experiments.

by Emerson W

Mar 17, 2019

This should really be broken up into several separate classes. It is a whole lot at 1 time.

by Justina

Jul 20, 2017

I would have rather gone deeper into the tests, than quickly run through them.

by Jared B

May 16, 2016

Quite advanced in contrast to the rest of this specialization!

by 薛昭

Jun 13, 2019

It requires a lot of knowledge of R and statistic

by Varaga P

May 11, 2020

Nothing to do with the overall specialization

by XIE Y

Aug 27, 2017

Content a bit too hard

by Gloria E W

Aug 21, 2019

Very hard

by Kolesova V

Feb 16, 2017

difficult

by Sanjana J

Jun 06, 2020

This course is targeted towards a very narrow audience who are already highly familiar with R and R coding as well as related stats. It totally alienates other learners who may be coming from non stats/ non-research/ non-coding backgrounds. Given that this course is part of the larger Interaction Design Specialization that is built for all types of learners, this is a huge problem! You can't even unlock the Capstone Project until you successfully complete this 9-week, extremely difficult course. From learning about social computing you are suddenly watching a series of lecture videos where the professor is just running lines and lines of R codes that he previously wrote and talking in stats/R jargon.

They really need to restructure this course ASAP: (1) Spend more time on teaching and explaining the various stats concepts (2) Examples, exercises, quizzes that help us practice how to choose an appropriate experiment design, identify factors/levels and choose an appropriate stats test (3) Consider other stats softwares that are being used in the tech world today that are WAY more user friendly (e.g. Exploratory- that helps simplify and use R). (4) SHOW US HOW TO INTERPRET EXPERIMENT RESULTS AND APPLY THOSE RESULTS TO IMPROVE OUR DESIGN. (5) OR make this course independent and replace it with something that is actually meaningful to this specialization.

You don't need to learn R coding in order to be successful at most design job out there. If you are an amateur in stats, I would just be really cautious going into this course. It is not impossible to complete but I don't think it will improve your understanding or help you be a better designer.

by Nicholas J

Oct 21, 2017

Throwing graduate level stats and R in towards the end of this certificate is truly baffling, but that aside it was taught well given the limited time.

The course would have been best geared to more practical considerations of research design itself, like more focus on when to use each test, how to get subjects, set up usability testing, issues to look out for etc.

I'm not suggesting testing considerations like sphericity and the Kolmogorov-Smirnov test etc. shouldn't have been addressed, but I think the time would have been better spent just laying the foundation for them conceptually, as opposed to getting into the nitty-gritty all the time with R.

by Krzysztof W

May 07, 2020

Course is not well designed. It focus more on proceeding technically statistical tests than explaining why we do them and how they work. I do not mean how they work on mathematical level but on explaining how they work on data level. For example in one of the previous courses Scott explained how chi square works and it was amazing, this course should be made in the same way. People learn here how to copy code and perform tests without explanation why in this case we do them. It would be nice if cases and data were from real experiments. I dont leave this opinion because the course was difficult, it wasn't for me, I had 100% overall score.

by Parimala H

Mar 27, 2017

This is a complex course for people who don't know R Studio. While it is not very hard to learn R Studio (even for people who are not comfortable with coding), it is very difficult when people get stuck. I did not get the much needed support when my R studio installation failed or when installation of libraries failed with error messages. The instructor was good, course content is good, but the lack of a suitable support representative for such complex subjects pulls down the reputation of this course. Please provide a good support personnel to at least help with online queries.

by erin

Dec 18, 2018

i can't figure out how to contact anyone about issues with the program used for this course... i have posted in discussions and searched for ways to contact someone and found nothing. more support is needed when using a program that isn't functioning the way we are taught. i'm about to take the quiz for week 6 but 2 of the main functions used gave errors and i'm not sure how to go from there since no contact or help is found readily. this is ruining this course for me, realizing that no support is available for significant issues like this

by Juliana B

May 22, 2020

I consider that this course, although it has to do with the interaction process, should not be part of the interaction design specialization. The R Studio tool is not normally used in the field of digital design. It is too technical and does not give me the knowledge I need to say that I achieved all the knowledge. This course could be replaced by Digital Analytics or other important content in experience design. It is also very extensive.

by Mariangela

Jun 15, 2017

Quite difficult, I had to do a lot of research and figure out lots of stuff by myself that was not previously indicated. I would have also loved to have a few real scenarios / use cases on how this method comes to be implemented before we started the actual practical part. I know what I learned was useful - I don't know if I will remember it all, but certainly challenging and interesting.

by Olga S

Mar 19, 2016

Hello. Unfortunately- 2. Just my opinion - not enough information about R tests and program, what is this, basic details for testing and code, no details for Mac-users. Videos are to short to understand details and goals, what I will learn, how to use mathematic formulas? If I could - I wanna leave this course. Thanks for understanding.

by Kelly M

Oct 27, 2019

I have a programming background, so finding solutions for many of the problems that arose while navigating R & R Studio was OK, but I can see this course as being incredible frustrating for those without any programming experience. Making this the last course before the capstone in this specialization feels a bit cruel.

by Jeppe C

May 22, 2016

Very very difficult. Quizzes are quite easy to accomplish, but the practical "take-away" from each week is small. I would have preferred if the course focused on getting the results(data) and keeping the statistical analysis to a few (most common) areas.

Too academic. More focus on practice use.

by Weronika G

May 15, 2018

I have to admit, this course was quite an ordeal. I don't have a problem with statistics or maths but the way the material is presented leaves a lot to be desired. The only course in the specialization that I struggled to go through.

by Florence L

Jun 20, 2016

Very dry content and hard to retain any information presented in the course because of it. Quizzes are fairly easy to pass provided you have some programming experience.

by sara w

Dec 17, 2016

Far too advanced for a total beginner as I am, was really hard and very confusing. My industry friends said it went too far for what I need in the real world

by Almudena L

Jun 28, 2016

Despite of been a interesting course I find it really hard to pass it. In my opinion, previous knowledge or R should be required.