WS24/25: Ethics and best practices in experimental research and data analyses

Course description

During experimental research and data analyses, we often encounter issues regarding what the best and most ethical practices are, from the moment we design a study, analyze the data, until we interpret the results. Design issues involve reliability and validity of the tasks, data collection, and participant recruitment. Issues during the execution of the experiment encompass the order and cognitive load of the tasks, and the number of sessions. Data analysis challenges include data cleaning, handling missing data, transforming variables, and addressing multicollinearity and convergence in models. Crucially, decisions made by researchers impact both the results and their interpretation. This seminar will review literature on common experimental and statistical challenges, discussing various approaches, their rationales, and the overall best ethical practices.

taught by:  Dr. Laura Pissani
start date: tba
time: tba
located in:tba
credits:4 CP (presentation only), 7 CP (presentation + final paper/project)
Grade breakdown:
•    4 CP (presentation only): 70% Presentation, 30% homework and contribution to discussion
•    7 CP (presentation + term paper or project): 40% Presentation, 40% Final paper/project, 20% homework and contribution to discussion
suited for:  B.Sc. in Computational Linguistics
B.Sc. in Language Science and Technlogy
M.Sc. in Computational Linguistics
M.Sc. in Language Science and Technology
more details:tba