Designing and Understanding Psychological Experiments
Gestalten und Verstehen von psychologischen Experimenten
6 CPirregularlyENno longer offered
Contents
As computers proliferate, it has become increasingly important for computer scientists to understand how users perceive and interpret computer graphics and computer interfaces. This course offers an accessible introduction to psychological experiments and experimental design. You will learn the major components of a perceptual experiment as well as the fundamentals of experimental design. This includes developing a research question, setting conditions and controls, balancing specificity with generality, and choosing the appropriate stimuli and task. Ethical and social aspects are addressed in this context. You will also learn statistical techniques for analyzing results, including methods specific to individual tasks. • Introduction: What Is an Experiment? • Foundations of Experimental Design • The Task • Free Description • Rating Scales • Forced Choice • Specialized Multiple Choice • Real-World Tasks • Physiology • Stimuli • Choosing Stimuli/Stimulus Databases • Presenting Stimuli: The Psychtoolbox • Data Analysis • Statistical Issues • Common Statistical Tests • Special Statistical Tests • Signal Detection Theory • Psychometric Functions
Learning outcomes
After successful completion of the course, you should be able to better understand published experiments – including spotting possible design flaws – and even design standard experiments on your own. Finally, you will understand the concepts and terminology needed to read more advanced texts and coursed on experimental design.
Assessment
• Written examination, 120 min. OR • Oral examination, 30-45 min. (with small number of participants) In the first lecture it will introduced, if the examination will organized in written or oral form.
Literature (1)
- Suggestions for literature can be found on the department's website.
Remarks
• Study programme Informatik M.Sc.: Compulsory elective module in complex „Praktische Informatik“ (level 400) • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Advanded Methods“
Source: BTU's module description · retrieved 14 Oct 2026Original