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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

3.7
438件の評価
157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

DS

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!

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.

フィルター:

Designing, Running, and Analyzing Experiments: 126 - 150 / 152 レビュー

by Wendy B

Mar 24, 2016

Not recommended. Not clear why we need to use R and learn all this statistics. Not practical for use in UX design.

by Jorge E

Apr 04, 2016

Disappointed ... very technical course and not so practical for today's world, there is a lot of terms and subjects that you require a good background in statistics analysis to understand well. It is a shame that this take part of the specialization program.

by Erica F

Sep 02, 2016

Much more emphasis on statistical analysis than on experimental design. Seems out of place with the rest of the specialization in terms of both length and subject matter. Course assessments seem to test in-depth knowledge of coding in R (which isn't gone over in sufficient detail in lectures, rather students are told to look it up in more detail on their own; however, the class is already longer and more in-depth than all the others in the specialization!) more so than experimental design or statistics. Should be less detailed, or split into multiple courses, or at least should have an introductory lesson(s) or prerequisite course on basics of how R works - I found it extremely frustrating trying to learn about and conduct statistical analyses in a system of which I had only minimal working knowledge.

by Muhammad Q

Oct 19, 2017

not helpful , extremely difficult for non programming background people , out of context of the course , bad teaching material and approach

by Orit S

Apr 11, 2017

Too much statistics, too much coding and inadequate instruction. This is not a coding specialization and if I wanted to learn coding I would have taken a coding course! This 9 weeks course has been a nightmare!

by Miryana T

Jun 25, 2016

This was the most arduous undertaking I have ever been through. My frustration is not with professor Wobbrock, who is obviously an expert in his field (though sometimes I felt like he's speaking in "High Valyrian" and not English). My disappointment lies with UCSD which included the course of such depth of information and a strong requirement for understanding R, without much thought on whether students will be able to follow. I feel that going through this course was largely pointless, because I'm not going to retain much of the depth of the material in the long run.

Based solely on this experience, I'm NOT going to be recommending this specialization to anyone.

by Harold B

Apr 03, 2016

If you do not know R studio or R programming this course will be very difficult for you. The fact that they state you dont need to know this program and then require you to use it to complete tests is unacceptable. Week 2 test onward requires you to modify code or program code in order to get statistics required to answer the questions. Their helpful hints cause errors when used mainly because you must know the correct syntax or placement of the code to get the correct answer.

I'm very disappointed in this class and probably will not pass because I do not have the time to figure out how to program in R.

by Agnes K

Aug 22, 2016

Neither statistics nor R was covered in any meaningful way. At the end of the course, you are left with frustration for having to jump through the loops, but no understanding of the principles. I am a college instructor for Statistics, having graduated from a PhD program - even with that background I could not follow the instructor.

The course designer never considered the audience, and never identified the goals of this course. The instructor was lost between teaching R and teaching stats, so in the end he did neither. Worst course I have ever taken, both online and face-to-face.

by Daryna A

Dec 16, 2016

Too much theory less practical things.

by Jessie S

Apr 24, 2016

I think the intention behind including this course was probably well meaning. I think it was a punishing course to get through for those of us who had no background in statistics, scientific studies, or programming. While I was able to fail my way forward through it, it was completely overwhelming, and overly painful. I really think the expectation should be set before students sign on to the specialization, as was I wonder how many students gave up on the whole Interaction Specialization after this course. Prof. Wobbrock was great, but I think there was a lot of vocabulary assumed to be known to us that just wasn't. I felt like I had been dropped down on Mars.

by Elizabeth B

Jan 12, 2018

This class needs to be structured way differently. There are too many opportunities for error with R Studio. The files should be separated out by weeks and the R file should correspond with each week. It's too difficult on the little viewer to see the code easily. Out of all the courses in this specialization this one was the toughest, mainly because of the organization. I understand there is a lot of detail to the calculations, but students shouldn't be looked down upon because they just don't understand it. The professor is super knowledgeable about the topic, it just was hard to follow along at times. Lastly, estimated quiz time is way off, the required amount of time is much greater.

by Andrew J

May 09, 2016

As a stand-alone course this would be very good. The presenter is engaging and clearly knowledgeable, and the treatment of the course subject is thorough and well-designed. Grounding UX design in rigorous statistical analysis is important.

BUT as a component of the Interaction Design specialisation it was much too long (nine weeks, as long as the previous three courses combined) and the coursework was un-interesting (long sequences of statistical tests with strange names) and very different to the creative and interactive assignments in the other courses. It very quickly turned into a demoralising "death march" for me.

As part of the specialisation, this course needs to be slimmed-down radically, and perhaps complemented by other analytical approaches to UX and interaction design. In its current form, the inclusion of this course in the Interaction Design specilisation is represents an error of judgement.

by Gabriella F

Apr 06, 2017

This is the specialisation that sucks all joy out of the entire course. 6 month on and I am still on week 2. The software and the provided files are not fully working, something is always missing, constant error messages... If you don't have background in statistics, you will have a very difficult time.

by Diego R

Apr 03, 2016

i'm loosing my mind :(

by Katie T

Jun 03, 2017

This class was terrible. The homework took significant leaps beyond the in-class exercises, it was hard to follow, and definitely overwhelming for someone without R, programming, or statistics experience.

by Fernando B G

Apr 22, 2018

Needed to much knowledge of the R language and has little to do with design

by Keenan W

Mar 20, 2016

Little to no use for me. Should not be included in the specialization... I didn't sign up for a data class...

by Tania C

Jan 09, 2017

NOT FOR PEOPLE WHO DON'T KNOW R TOOL!

This course needs an interesting approach to keep students wanting to study. The teaching method was boring. The professor was reading things from the screen 90% of the times (he looked bored himself). The topics covered in this course need more time for students to understand 10 weeks are insufficient.

by Jayneil D

Nov 06, 2017

The course content is really valuable but the follow up exercises are really difficult to solve on your own. There is not enough explanation given in the lectures by the professor and its really difficult. Some of the answers are incorrect yet no explanation is given.

by Mariana M O C

May 06, 2016

I took up to week 2 and, so far, this course assumes statistics knowledge. I expected it would provide a background on the rather than just run a code and show the results.

by Sandy B

Apr 14, 2016

I'm really sorry to give this rating, but I have no choice. The course was horrendously boring, and so far removed from the interesting and interactive work that we had done in the previous sections of the Specialisation. This is such an unfortunate course to have as a requirement to complete the Specialisation, and especially the final hurdle to get into the Capstone. Moreover it was the longest of all the courses. Thus the least interesting and also the longest - makes little sense!

As I said, I'm sorry to give this rating, but it needs to be said. The teacher seems like a great guy. And I'm sure he's killing it teaching statistics and R Studio at Uni, but using R studio to such a standard just doesn't seem like the everyday work an HCI designer would do. A statistician or data specialist yes, but a UI designer?

Perhaps you could make the course higher level, avoid the indepth R Studio, and make it 3-4 weeks like all of the other courses.

by Igor I

Oct 25, 2016

Way to technical

by Rory O

Sep 05, 2017

A terrible course for a beginner in statistics. I cannot believe I have completed the first six courses in this specialization, only to be met by a course that moves so quickly through very complex information, that i will never be able to pass the overall specialization. I am so disappointed. AVOID THIS COURSE. I will be writing to coursera to ask for a refund.

by Ryan S

Jun 30, 2016

Omigod! You're kicking this off in R-studio and teaching the whole course from this interface? Could you at least use a pen with ink that we can read when you're not in R?!

This might be the last straw for me in this specialization. Nothing about this subject matter is easily digestible for a designer, and I'm okay with that. (I'm also a web/js developer, so I'm used to intense struggles with really abstract stuff.)

What I can't get over is that this is part of an interaction design specialization that teaches design concepts, but whose instructors almost never practice those concepts in their pedagogy. "Do as I say, not as I do" seems to be the prevailing MO. The whole effort seems totally half-baked, and nowhere more so than in this course.

I might not be so harsh if there weren't such great examples of well designed pedagogy elsewhere in Coursera, and for material that's at least as dry as statistics.

by Anastasiya S

Oct 23, 2017

I have no statistics background so I'm struggling to make any sense out of this course. I wish I could skip it but it is mandatory to proceed to capstone project of the specialization.