Design Analytics

In this elective, students will gather tools and acquire knowledge to critically evaluate (interactive and intelligent) technological prototypes and set the stage for the next iteration of the design phase by eliciting actionable design guidelines based on comprehensive empirical analysis. The technological component of this course is demonstrated by the strong focus on the improvement of IPSS (intelligent products, services, and systems) such as, conversational assistants, wearables, etc.

Instead of examining the complete design cycle, students will focus solely on the quantitative assessment of IPSS and examine their cognitive, perceptual, and experiential effects. To this end, students will learn and add skills to their methodological toolkit, which will enable them to a) design sound experiments (with Control and Experimental groups), b) use sensing technologies (e.g., eye-tracking) and adapt existing data-acquisition tools (e.g., NASA TLX, MSLQ), c) identify the right statistical tests (descriptive vs. inferential; comparison vs. regression), d) discriminate correlation from causation and identify confounding factors, and e) understand the proper means of communicating their quantitative analysis and results.

The content of this course is relevant for students because they learn how to systematically assess their designs with standardized practices and communicate their findings with multiple stakeholders and a broader design-research community. In this way, this course offers an essential ingredient in students transformation from a UX Designer to a UX Researcher.

In this course, the student will become familiar with the 5-stage Design Analytics Process (DAP) i.e., design diagnostics, study design synthesis, experimentation, data analysis, and design prescription.