ReproducibiliTeach: Strategies to make your research more transparent, robust & reproducible
Concerned about the reproducibility crisis? Wondering what you can do to make your research more transparent, robust & reproducible? Looking for hands-on experience and expert advice?
Participants in the hands-on ReproducibiliTeach course, offered by QUEST and NeuroCure, will learn to identify common problems that affect transparency and reproducibility and work on implementing better practices in their own research.
Each class will begin with a seminar, where participants learn about problems with common practices and explore more transparent and reproducible alternatives. Seminars will be followed by workshops, where participants implement the skills discussed by applying them directly to their own research projects. After completing the course, participants will be able to apply the skills that they have learned and practiced to other research projects.
This course is designed for biomedical researchers working on small sample size studies, including preclinical (animal) research, in vitro research, or human research with small numbers of participants. Some topics may also be relevant to researchers working with larger sample sizes.
This course is open to researchers in the biomedical or biological sciences at Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Freie Universität Berlin, or Technische Universität Berlin (30 participants).
Ten additional spaces are available to participants from the NeuroCure Cluster of Excellence. NeuroCure participants should email Dr. Bernard to register. All other participants can register through the website. Participants need to be actively working on a research project and have written a methods section, or be prepared to write a methods section, for their research project.
Tracey L. Weissgerber, Ph.D.
Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Germany
BIH QUEST Center for Responsible Research
Dr. Weissgerber is a meta-researcher at QUEST (Quality | Ethics | Open Science | Translation) in Berlin. She completed her graduate work in physiology at Queen’s University (Canada), a post-doctoral fellowship at the Magee-Women’s Research Institute (USA), and was an Assistant Professor at Mayo Clinic (USA). Her 2015 paper on bar graphs has been viewed more than 375,000 times. This paper contributed to policy changes in many journals that encourage authors to replace bar graphs of continuous data with more informative graphics (dot plots, box plots, violin plots).
Dr. Bernard is a trained pharmacist, pharmacologist, and currently works as Coordinator for Research Value and Open Science in the NeuroCure Cluster of Excellence. In addition to neuroscientific research, he worked for several years in an academica-industry collaboration and helped to develop two quality management systems designed for preclinical research. He is committed to promoting good research practice, as laid out in this open access book Good Research Practice in Non-Clinical Pharmacology and Biomedicine, to which he contributed.
ECTS & Time commitment
We will provide a signed certificate to help participants obtain ECTS credit from their institution or department. You must attend at least 7 of the 8 sessions to receive a certificate. As this course is open for participants from various programs, obtaining formal approval from each program is not feasible. Participants themselves are responsible for ensuring that they will receive credit for the course.
After completing the course, students will be able to:
- Identify the appropriate reporting guideline for their study and use that guideline as a writing guide to prepare a methods section
- Determine when blinding and randomization are needed
- Compare and contrast common techniques for blinding and randomizing experiments
- Design a flow chart to report attrition for a research study
- Explain the benefits of using research resource identifiers (RRIDs) and add RRIDs to a manuscript
- Discuss best practices for using methodological citation shortcuts
- Deposit a protocol on a public repository
- Implement sound data management principles by preparing a spreadsheet and data dictionary to record study data
- Write a data sharing statement
- Deposit a dataset in a public repository
- Identify and fix common data visualization errors, such as using bar graphs to present continuous data or creating figures that aren’t colorblind accessible
- Identify and fix common problems with statistical reporting among studies that use t-tests and ANOVA
February 17 to April 7, 2022
Course language: English
Class times: Thursdays 2:00 - 3:45pm
Homework: In addition to class time, it is estimated that students will spend, on average, 1.5 hours per week working on course activities.
The course outline can you find here!
Registration is now open.
This is a joint course from BIH-QUEST Center and NeuroCure Cluster of Excellence.
NeuroCure is funded within the Excellence Strategy by the GERMAN FEDERAL and BERLIN STATE GOVERNMENTS through DFG Grant EXC 2049 / project number: 390688087.