You will never know whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design experiments, how to run 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 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.
By the end of the course, you will be able to knowledgeably design, run, and analyze your own experiments for putting empirical and statistical weight behind your designs.
Week 1: Basic Experiment Design Concepts
Week 2: User Preferences: Tests of Proportions
Week 3: Website A/B Tests: The T-Test
Week 4: Validity in Design and Analysis
Week 5: Task Completion in Authoring Tools: One-Factor Between-Subjects Experiments
Week 6: Human Search Performance: One-Factor Within-Subjects Experiments
Week 7: Smartphone Text Entry: Factorial Experiment Designs
Week 8: Generalizing the Response
Week 9: The Power of Mixed Effects Models
You will learn how to design technologies that bring people joy, rather than frustration. You'll learn how to generate design ideas, techniques for quickly prototyping them, and how to use prototypes to get feedback from other stakeholders like your teammates, clients, and users. You'll also learn principles of visual design, perception, and cognition that inform effective interaction design.