Introduction to Empirical Methods of Human-Centered Computing

Semester:	2025 Winter
For:	Bachelor & Master
Format:	Lecture
Credit Points:	5 CP

This lecture introduces statistical (quantitative) and qualitative empirical research methods. Students learn to apply these techniques, interpret the validity of their results, select suitable methods for concrete studies and evaluations, and discuss their advantages and disadvantages on a scientific level. The course is jointly offered by the groups Empirical Information Security (Prof. Fahl), Usable Security and Privacy (Prof. Dürmuth), Human-Computer Interaction (Prof. Rohs), and Software Engineering (Prof. Schneider).

It is recommended as preparation for Bachelor’s and Master’s theses in the area of Human-Centered Computing.

Syllabus

1. Introduction: What is empirical research? Examples from the participating groups.
2. Foundations: Research questions, hypotheses, validity, induction/deduction.
3. Working with literature: Related work, systematic literature reviews (SLR and snowballing), citing literature.
4. Qualitative data collection through interviews: Design, pretest, and execution.
5. Qualitative data analysis: Coding and thematic analysis.
6. Experiment design and evaluation of prototypes.
7. Data analysis and statistics: Simple tests, ANOVA.
8. Scientific handling of data: Collection, format, and storage.
9. Surveys: Design, pre-testing, execution, and exploratory data analysis.
10. Ethics and good scientific practice: Handling participants and data, reproducibility.
11. Pitfalls and discussion of experiences.

Some topics span more than one lecture.

Recommended Prior Knowledge

No prior knowledge is required. The Bachelor courses in Software Engineering, IT Security, and HCI prepare for this lecture.

The course is taught in German.

Exam

The course concludes with a written exam (75 minutes). The latest exam dates can be found on the faculty’s website: Exam dates.

(also see modkat)