About this course: 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.
Who is this class for: This class is at the level of advanced undergraduates or first-year graduate students in fields related to human-computer interaction, computer science, interaction design, user experience design, user-centered design, or human-technology behavior studies.
Taught by: Scott Klemmer, Associate Professor
Cognitive Science & Computer Science
Taught by: Jacob O. Wobbrock, Associate Professor
The Information School
| Basic Info |
Course 7 of 8 in the
Interaction Design Specialization.
|
| Commitment | 9 weeks, 3-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
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| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
I could immediatly implement the concepts and instruments provided in this course to my professional activity. I must say that I have a poor training in statistics and a superficial knowledge of R, but I needed to implement more professional usertests (I'm an instructional designer with a background on education).
I really enjoyed the clear explanations; above all, how the concepts where linked to R practice, which was thrilling to me.
Thanks to the team! Great course!
Juliana
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!
This course was a hard course, probably the hardest from the whole specialization. Very technical, sometimes even troubleshooting R Studio would take an hour of researching through online forums to try to get the right plugins and work random issues with the software and follow along. Stats background and coding background were really helpful personally, I'm not sure if I could have completed it without that. Definitely needs dedication and extra hours a week to complete. Aside from that, the professor is clear and knowledgeable, and the tests are directly extracted from the materials reviewed each week. I suggest taking notes while watching the video to refer back during the tests.
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JS
A very complete tour of methods for analyzing experimental results using R. Its more about practice than theory, but it filled in crucial gaps in my knowledge and I expect what I learned will be very valuable moving forward.