Design Analytics | BSc | 5 ECTS
In this introductory HCI course, students 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 based on a strong focus on the improvement of IPSS (intelligent products, services, and systems) such as conversational assistants, wearables, etc.
Rather than studying the full human-centric design cycle, students focus solely on the quantitative evaluation of IPSS, examining their cognitive, perceptual, and experiential effects. To this end, students will learn and add skills to their methodological toolkit that 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 collection tools (e.g., NASA TLX, MSLQ), c) identify the appropriate statistical tests (descriptive vs. inferential; comparison vs. regression), d) distinguish correlation from causation and identify confounding factors, and e) understand the appropriate means of communicating their quantitative analyses and results.
In this course, the student will become familiar with the 5-step Design Analytics Process (DAP), i.e., design diagnosis, study design synthesis, experimentation, data analysis, and design prescription.
Empirical Design Research | MSc | 5 ECTS
This course provides students with a foundation in mixed methods design research and a framework of theoretical concepts and paradigms for rationalizing, designing and conducting high quality empirical research, from instrumental research (for design) to scientific research (about/for/with design).
In the course, the students evaluate and discuss the appropriateness of various research methods in relation to the underlying research question, context, or objective. In addition, students learn to combine quantitative and qualitative approaches to meaningfully plan and conduct research to examine evidence, test hypotheses, or develop theory appropriate to a given context, design stage, and research question.