Open Science: Toward Robust Behavioral Research

What it is about

You learn about the background and causes of the replication crisis in empirical disciplines and analyze why important findings are difficult to reproduce. In the end you can recognize problematic research practices and know methods and practices (e.g. preregistration, Open Science, Bayesian analysis) that increase robustness, replicability and transparency.

What you will be able to do

• Identify questionable research practices (e.g. p-hacking, HARKing)
• Understand systemic problems of the publication system (e.g. publication bias)
• Plan and create a preregistration
• Implement Open Science practices (open data, open analysis code)
• Apply robust analysis methods (e.g. Bayesian statistics)

What the module consists of

• PresentationsStudents present empirical investigations and analyses that shape the discussion
• Group discussionsAnalysis of seminal articles and discussion of improvement methods for robustness and transparency
• Small-group exercisesPractical exercises on preregistration and preparation of repositories for data and code

Teaching method

• Short lecturesto briefly present central empirical findings and arguments
• Group discussionto critically analyze and discuss methods for improvement
• Practical exercises in small groupsto learn practical skills such as preregistration and repository preparation