During the last years questions have been raised about the validity empirical research. How can we tell if the research we’re reading and doing is rigorous and reproducible?  In this course, we will discuss the controversy around and the replicability of behavioral results. Get to know about advancements in the fields of methods and design to maximize the reproducibility of your own scientific work. These tools include pre-registration, open sharing of data and materials, new models of scientific publishing, large-scale open collaborations, and statistical reform. The course will involve hands-on practice implementing cutting-edge tools for conducting open and reproducible research in empirical science.  The course will thereby go through the entire research process and identify places in which long-term reproducible research can be created with minor changes. Practical examples, but also problems will be critically discussed.

The aim of the course is to (1) develop an awareness for the practises that affect the rigor and reproducibility of their own and others´ research, (2) inform students about current opportunities on the topic of open and reproducible science and (3) implement these innovations in their own scientific workflow.

For this lecture participation is obligatory. Students are allowed to miss a maximum of 20%

Introduction of concepts of open science and reproducibility through presentation. Hands on practise through exercises and checklists for efficient project management in the scientific life cycle of a project. Direct feedback through the instructor and peers.

Class evaluation consists of three parts: