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

It's really interesting to learn it but it's not easy at all. Maybe you will need an statistic professor to understand it perfectly.

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

9 weeks are just too short for these abundant material.

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

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

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

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

Quite advanced in contrast to the rest of this specialization!

It requires a lot of knowledge of R and statistic

Nothing to do with the overall specialization

Content a bit too hard

Very hard

difficult

I was looking forward to learning [R] Studio. I thought the classes in this course were definitely on the tougher side but for the most part I found the lessons relatively easy to follow if you take notes and I thought the professor's presentation was understandable. It was the quizzes that I take real issue with. Firstly, many of the packages were outdated and I saw numerous comments within the forum about students unable to install or run the packages required for the assessments. Professor Wobrock does mention this in his "readme" doc but that is assuming all students know to read this or to access the forum at all. Additionally, I found that there were many instances when the first quiz for each assessment (covering the concepts) would ask questions about material we had not yet learned. I often flagged this within the coursework when it would appear in the following week's content but there is little sign of any moderator or support for this course since 2019. Additionally, I found that we were being quizzed about a deeper level of interpreting the data than what we actually learned in class. It is one thing to follow along on R while watching the professor do it. There was not enough explanation of WHY we would progress from one line of code to the next, of when to use certain tests or packages over the other. When I did check the forum comments, I noticed professor Wobbrock's tone is rude and condescending. If a majority of students in this course are struggling, that is an issue with the professor, the content, the way the content is being delivered, or all three. It is appalling to me that he repeatedly mentions that the "code is right, the problem must be you" within several of his scant responses on the forum. Lastly, my biggest issue with this course is that we learned how to copy some R code in order to run experiments and analyze data for the specific examples we discussed while following along with the lectures but there was not enough discussion about WHY the lines of code were written the way they were, such as for an interaction plot, this is where the X variable goes, this is where the trace goes etc. Much of the knowledge we are supposed to obtain is possible because of Google. I really object to a professor repeatedly saying "if you want to know more about this, you can Google it." It is not that I even want to know R inside and out, I just want to understand WHY the code is written in the way it was so that I can better replicate the experiments in the future, as well as knowing WHEN to use them. The professor repeatedly says you do not need R experience to take this course but it is my opinion that those who endeavor to complete it would really benefit from beginner knowledge at least OR the materials should be revised to address beginners specifically. I finished this course with a very high average (96%) but I do not feel like I am prepared to use R in a meaningful way. Perhaps I'll "Google it."

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.

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.

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.

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

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.

This course was NOT appropriate for the Interaction Design Specialization. It was far too detailed, complex, in depth and advanced! To say a person can take this course without any R or advanced statistics is crazy. It was a real struggle. The teacher obviously knows what he's talking about, so don't want to take away from his skills/abilities...it was just a complete mismatch for my goal.

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.

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.

This is NOT an entry-level course!!! Can not stress this enough! This should not be advertised as a beginner's course! I honestly can't tell how good it was because I had no idea what I was doing the whole time! I am sure the instructor is knowledgeable but it's way too complicated. I am very glad I am done with this one!

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.

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.

The content of the course is definitely top notch. But the way it is structured can be improved manyfold. It is packed with knowledge to be covered in a very short span of time. It touches a lot of various statistical tests without going into much detail of what, why and how.