11509 - Designing and Understanding Psychological Experiments Modulübersicht

Module Number: 11509
Module Title:Designing and Understanding Psychological Experiments
  Gestalten und Verstehen von psychologischen Experimenten
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr. habil. Cunningham, Douglas
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: On special announcement
Credits: 6
Learning Outcome: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.
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. You will also learn statistical techniques for analyzing results, including methods specific to individual tasks.
  1. Introduction: What Is an Experiment?
  2. Foundations of Experimental Design
  3. The Task
    • Free Description
    • Rating Scales
    • Forced Choice
    • Specialized Multiple Choice
    • Real-World Tasks
    • Physiology
  4. Stimuli
    • Choosing Stimuli/Stimulus Databases
    • Presenting Stimuli: The Psychtoolbox
  5. Data Analysis
    • Statistical Issues
    • Common Statistical Tests
    • Special Statistical Tests
    • Signal Detection Theory
    • Psychometric Functions
Recommended Prerequisites:None
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Design project / 60 Hours
  • Self organised studies / 60 Hours
Teaching Materials and Literature:Suggestions for literature can be found on the department's website.
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:
  • 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.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • Master (research-oriented) / Artificial Intelligence / PO 2022
  • Master (research-oriented) / Informatik / PO 2008 - 2. SÄ 2017
  • Master (research-oriented) / Informations- und Medientechnik / PO 2017
  • Master (research-oriented) / Kultur und Technik / PO 2017
  • Master (research-oriented) / Künstliche Intelligenz Technologie / PO 2022
Remarks:
  • Study programme Computer Science M. Sc.: Compulsory elective module in complex "Practical Computer Science" (level 400).
  • Study programme Information and Media Technology M. Sc.: Compulsory elective module in "Cognitive Systems".
Module Components:Lecture: Designing and Understanding Psychological Experiments  
Accompanying exercises
Components to be offered in the Current Semester:
  • no assignment