Learner Reviews & Feedback for Designing, Running, and Analyzing Experiments by University of California San Diego

Great course, a little too long compared to other courses

Very very helpful for my game design project.

Thank you.

More comprehensive than in-depth.

Very analytical and challenging!

It looks great

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.

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!

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.

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.

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.

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.

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 :)

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.

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.

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.

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.

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.

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.

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.

I think the course requires some basic statistic knowledge which I do not know anything about, it is tough to keep out. If providing some basic reading or keynote before hand would be really helpful!

I​ would give it a 3.5 if there were half scores. This course requires way too much time and is quite tedious, however, the instructor explains the somewhat "dry" material very well.

it's a little too much materials. I wish the course materials are less dense, though I really appreciate the efforts of the instructors creating this course

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.