Conducting Open and Replicable Experimental Research in Psychology
- Become familiar with basic research practices that lead to a more open and reproducible scientific process
- Discuss the replication crisis and current “best practices” suggested by the open science community
- Learn to pogramme an experiment using PsychoPy, analyze the resulting data using R, and present the results using ggplot2 and RMarkdown
- Programme – The course is taught in English (4 ECTS)
- Requirements – Students from Psychology and the Behavioural Sciences
Programme fee – tba. (includes all study materials, transcript of records, and health, liability and accident insurance as well as a public transportation ticket within Frankfurt).
- Application deadline – tba.
The replication crisis shook many scientific disciplines – especially in the social and behavioral sciences – and has led to a call for more open and replicable research practices. Many of these practices focus on gathering, organizing, analyzing, and reporting empirical data.
This module will give a small group of students a practical introduction into some of the basic research practices, which can lead to a more open and reproducible scientific process. We will begin with an overview of the replication crisis and the current “best practices” suggested by the open science community, before putting these suggestions to use in a specific example derived from experimental psychology. This entails programming an experiment using PsychoPy, analyzing the resulting data using R, and presenting these results using ggplot2 and RMarkdown. Throughout the entire module, special attention will be paid to steps and actions, which should be taken to ensure reproducibility and openness of process (e.g. using git, pre-registering an experiment).
The course comprises 28 contact hours (8*3.5 hours). Upon successful completion, 4 ECTS (European Credit Transfer System) points will be awarded for the module. A single ECTS point is defined as the equivalent of 25 to 30 hours of student workload. This includes class hours, additional preparations for class activities, readings, assignments as well as final assessments.
Attendance: Participants have to attend at least 80 % of the classes.
Participants should have basic knowledge about descriptive statistics and statistical inference. Having some prior experience with programming and data handling will be advantageous. The substantive background of the experiment will be from psychology, but participants from all behavioral and social sciences are welcome.
Participants should bring their own laptop with a current version of PsychoPy, R, and RStudio already installed. In case participants lack prior programming experience, online resources and links to tutorials to acquire this knowledge autodidactically will be provided prior to the summer school.
I am a PhD student in the Scene Grammar Lab, located in the Department of Psychology at the Goethe University. My research focuses on the question to which extent classical findings of visual scene perception hold true in an ecologically more valid environment, e.g., in virtual reality. When I’m not in the lab, I am passionately organizing stuff for our local Open Science Initiative.
I am a doctoral candidate at the Fiebach Lab for Cognitive Neuroscience at the Goethe University Frankfurt. I am working on a project investigating psychological flexibility and its neuronal underpinnings using fMRI. Besides my day-to-day work, I passionately like to help Julia organizing stuff for our local Open Science Initiative.
I am a doctoral candidate at the Fiebach Lab for Cognitive Neuroscience at the Department of Psychology. I am working on a project on cognitive biases and their neural mechanisms using methods like fMRI and eye tracking.
Dr. Benjamin Gagl
I am a Post-doc at the Fiebach Lab in Frankfurt and interested in Neuro-cognitive processes during reading and visual word recognition in beginning, dyslexic and adult readers.
I am a PhD student in the „psychological methods with interdisciplinary focus“ division in the Department for Psychology at the Goethe University. My day-to-day work consists of teaching and researching statistical methods using R with focus on network analysis.
Dr. Thomas Lösch
I am part of the academic staff in the team Research Data in Education at the DIPF Leibniz Institute for Research and Information in Education in Frankfurt. I am working as an advisor for research data management and study how researchers in education do open science.