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GESIS Training
GESIS - Leibniz-Institute for the Social Sciences

GESIS Training News

December 2024

Spring Seminar | Summer School | Fall Seminar | Workshops

As we approach the end of another year, we would want to sincerely thank you for your continued support, valuable input, and collaborative engagement throughout 2024.

Looking ahead to 2025, we are excited to offer a cutting-edge training portfolio designed to meet your evolving needs. We can’t wait to welcome you to our events—whether online or in person in Cologne or Mannheim.

We wish you a joyful and relaxing holiday season, and may the coming year bring happiness, health, and success to you and your loved ones.

Your GESIS Training team

Table of Contents

GESIS Workshops 2025 – Tailored to Your Needs

Where are your research subjects right now? What websites are they browsing? How do they move through physical and digital spaces? The answers to these questions hold unprecedented potential for understanding human behavior—if you know how to capture, analyze, and integrate diverse data sources effectively. GESIS is here to help you navigate through this evolving research landscape with a series of workshops on 🗺️ spatial, 🌐 web, and 📱 mobile data sources and methods.

The spatial dimension of social phenomena comes alive in our Introduction to Geospatial Techniques workshop, in which you can explore the fundamentals of acquiring, handling, and visualizing geospatial data. For those ready to push methodological boundaries, Advanced Geospatial Data Processing will take your spatial data skills to the next level. Geodata and Spatial Regression Analysis completes the journey, offering tools to unravel the complex interplay between geography and social processes.

Moving deeper into the digital realm, Preprocessing and Analysing Web Tracking Data introduces you to state-of-the-art routines for processing and evaluating web browsing behavior, whereas in Design and Methods for Mobile Data Collection, you can get your hands on conducting mobile, intensive-longitudinal survey studies. If you are more generally interested in harnessing the potential of large amounts of data, consider Applied Machine Learning with R to learn how to build, evaluate, compare, and tune predictive models.

But that is not all – we have an exciting new lineup of workshops on the horizon:

Finally, we have important updates to our previously announced program:

For additional details, registration, and our complete workshop program, visit our workshop website or have a look at the complete program below. Do not miss this opportunity to unlock new insights in your research!

GESIS Spring Seminar 2025 – Experimental Designs in the Social and Behavioral Sciences – Register Now!

The Spring Seminar offers high-quality training in state-of-the-art techniques in quantitative data analysis taught by leading experts in the field. It is designed for advanced graduate or PhD students, post-docs, and senior researchers. In 2025, all courses will deal with "Experimental Designs in the Social and Behavioral Sciences".

Extensive hands-on exercises and tutorials complement lectures in each course. The Spring Seminar will take place onsite at GESIS Cologne, Germany, from 17 March to 04 April 2025.

This year's courses:

Week 1 (17–21 March)

Field Experiments

Johanna Gereke (University of Mannheim), Nicole Schwitter (University of Mannheim)    

Week 2 (24–28 March)

Laboratory Experiments

Florian Heine (Vrije Universiteit Amsterdam), Eve Ernst (Teaching Assistant)

Week 3 (31 March–04 April)

Multifactorial Survey Experiments

Ulf Liebe (University of Warwick), Jürgen Meyerhoff (Berlin School of Economics and Law)    

Courses must be booked separately – whether you wish to attend one, two, or all three. There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. Thanks to our cooperation with the Cologne Graduate School in Management, Economics, and Social Sciences at the University of Cologne you can obtain three ECTS credit points per one-week course. More information is available here.

For detailed information, please visit our website.

KODAQS Data Quality Academy launch

The KODAQS Data Quality Academy Certificate Program has officially kicked off! 🎉 The 20 participants of the first cohort gathered in Mannheim for a day of networking, a panel discussion, and a workshop exploring experiences and challenges of data quality. This marks the beginning of their six-month journey to becoming certified Data Quality Stewards. KODAQS is a partnership between GESIS, the University of Mannheim, and LMU Munich. To learn more about the KODAQS Academy, visit our website.

If you're interested in joining the next cohort, keep an eye out for the next call for applications in summer 2025.

A Look Back – GESIS Fall Seminar in Computational Social Science 2024

From 30 August to 27 September 2024, the GESIS Fall Seminar in Computational Social Science took place in Mannheim and online. For the first time, it offered not only live courses but also two courses in our brand new blended learning format. Overall, participants could choose from nine introductory and advanced courses on computational social science methods and techniques. [Continue reading]

If you could not make it this fall, please save the date for the next edition:

01 to 26 September!

We will announce the full program in Spring 2025. For more information on the Fall Seminar, visit our website.

Stay tuned!

Interview with Johanna Gereke (University of Mannheim) & Nicole Schwitter (University of Mannheim)

Urban

Johanna Gereke is a postdoctoral fellow at the Mannheim Centre for European Social Research (MZES), University of Mannheim. Her research focuses on intergroup relations, economic and political sociology, as well as trust and cooperation in modern societies. Her interdisciplinary work employs a wide range of experimental and quasi-experimental methods, including lab-in-the-field, survey, and field experiments. She has published widely in leading sociology, political science, economics, and psychology journals.

Feuchter

Nicole Schwitter is a postdoctoral researcher at the Mannheim Centre for European Social Research (MZES), University of Mannheim, and an honorary research fellow at the University of Warwick. In her research, she mainly employs computational and (quasi-)experimental methods to address questions regarding social groups and pro-/antisocial behavior.

They will teach the Spring Seminar course "Field Experiments". The onsite course will take place on 17–21 March 2025.

How did you become interested in your subject?

Johanna: My interest in experimental social science began during my PhD studies at the European University Institute, where I was supervised by Diego Gambetta and took courses in behavioral economics. I was drawn to experimental methods for their ability to rigorously test causal explanations, which I view as the gold standard in social science research. Field experiments are particularly compelling to me, as they allow for unobtrusive experimentation in real-world settings. This is especially valuable when studying phenomena where social desirability bias might otherwise influence participants’ responses – such as research on discrimination.

Nicole: I first became interested in experimental methods during my BA at the University of Bern where I took several hands-on courses that sparked my curiosity. In these courses, we worked in groups to design our own experiments, collect data, and analyze the results (quick shoutout: one of those courses was taught by Ulf Liebe, who will be teaching in the third week of this spring camp!). What has always fascinated me about field experiments, in particular, is how a clever and well-crafted design can yield powerful insights with relatively simple means—offering answers to questions that might otherwise be difficult to investigate.

What lessons can participants draw from your GESIS course?

Johanna & Nicole: Participants in our GESIS course will come away with both practical skills and deeper insights into designing and conducting field experiments. They will learn how to create experiments that are not only methodologically and ethically sound but also feasible in real-world settings, following current state-of-the-art practices. By the end of the course, participants should feel confident in setting up their own field experiments and applying these methods to investigate causal relationships in their areas of interest.

What do you enjoy most about being a social scientist?

Johanna: What I enjoy most about being a social scientist is the creativity involved in designing and conducting experimental research. It’s fun to develop studies that uncover new insights and often surprising patterns about the social world. My research allows me to continually learn and deepen my understanding of human behavior in ways that both challenge and inspire me.

Nicole: There are many aspects I enjoy about being a social scientist, but today, let’s focus on teaching—especially since I’m looking forward to the GESIS Spring School! What really excites me is seeing students' curiosity in action—how their different ideas and interests challenge me to think in new ways. It’s rewarding to guide them through tough concepts and watch their own research ideas take shape.

What do you think is the most exciting recent development in your field?

Johanna: In my view, the most exciting recent development in field experiments is the combination of field experiments with other methods, such as using registry data to select experimental locations and replicating studies across different settings. This approach allows us to explore how context influences social behavior, leading to a more nuanced understanding of generalizability of social theories and experimental results.

Nicole: I think one of the most exciting recent developments is the rise of digital field experiments in online environments. Particularly when collaborating with platforms (like LinkedIn, Facebook, and others), researchers can often work with massive datasets—sometimes millions of observations—enabling high-powered tests of causality on an unprecedented scale. These digital experiments can come with their pitfalls, but they allow us to study real-world behaviors in real time, opening up new possibilities for understanding complex social dynamics with greater precision and reach.

We thank Johanna & Nicole for their insights and look forward to their course in March.

GESIS Workshops in English

16–20/12/24OnlineCausal Mediation Analysis
(Felix Thoemmes)
16–17 & 23–24/01/25OnlineIntroduction to R
(Emilia Kmiotek-Meier, Anna Herdick (Teaching Assistant))
27–30/01/25MannheimDecomposition Methods in the Social Sciences
(Johannes Giesecke, Ben Jann)
11–14/02/25OnlineApplied Machine Learning with R
(Paul C. Bauer)
18–19/02/25OnlinePropensity Score Matching: Computation and Balance Estimation for two and more groups in R
(Julian Urban, Markus Feuchter)
24–26/02/25OnlineApplied Multiverse Analysis with Stata and R
(Maximilian Brinkmann, Johanna Pauliks, Reinhard Schunck)
11–13/03/25OnlineCollecting and Analyzing Longitudinal Social Network Data
(Lars Leszczensky, Sebastian Pink)
19–21/03/25OnlineIntroduction to Bayesian Statistics
(Denis Cohen)
31/03–02/04/25OnlineDesign and Methods for Mobile Data Collection
(Lukas Otto)
08–10/04/25OnlineAggregating Evidence Across Multiple Studies
(Jessica Daikeler, Rebecca Kuiper)
09–10/04/25CologneIntroduction to Geospatial Techniques for Social Scientists in R
(Stefan Jünger, Anne-Kathrin Stroppe)
14–16/04/25CologneLatent Class Analysis
(Daniel Oberski)
28–29/04/25OnlineAdvanced Geospatial Data Processing for Social Scientists
(Dennis Abel, Stefan Jünger)
07–08/05/25HybridPreprocessing and Analyzing Web Tracking Data
(Frank Mangold, Helena Rauxloh, Sebastian Stier)
15–16/05/25OnlineTime Series Analysis for Modeling Intensive Longitudinal Data
(Noémi Schuurman)
20–22/05/25OnlineAdvanced Bayesian Statistical Modeling in R and Stan
(Denis Cohen)
09–11/07/25MannheimGeodata and Spatial Regression Analysis
(Tobias Rüttenauer)
21–23/10/25MannheimData Management, Advanced Programming and Automation using Stata
(Daniel Bela)
19–20 & 26–27/11/25OnlineSequence Analysis in the Social Sciences
(Emanuela Struffolino, Marcel Raab)

GESIS Workshops in German

12–13/02/25CologneEinführung in Ideen der qualitativen Sozialforschung
(Katharina Leimbach, Nicole Bögelein)
24–25/02/25OnlineGrounded-Theory-Methodologie
(Günter Mey, Paul Sebastian Ruppel)
12–14/03/25CologneDurchführung qualitativer Interviews
(Katharina Leimbach, Nicole Bögelein)
12–14/03/25OnlineEinführung in Strukturgleichungsmodellierung
(Marie-Ann Sengewald)
13–15/05/25CologneEinführung in Gruppendiskussionen
(Thomas Kühn)
21–23/05/25CologneExpert*inneninterviews
(Laura Behrmann, Nicole Bögelein)
26–27/05/25OnlineEinführung in die Mehrebenen-Strukturgleichungsmodellierung
(Theresa Rohm)
23–24/06/25MannheimEinführung in die Längsschnittliche Datenanalyse
(Marco Giesselmann)
11–12/09/25CologneEinführung in die qualitative Inhaltsanalyse
(Markus Janssen, Christoph Stamann)
24–26/09/25CologneMehrebenenanalyse mit Stata and R
(Hermann Dülmer, Heike Krüger(Teaching Assistant))
07–09/10/25CologneQualitative Netzwerkanalyse
(Markus Gamper, Laura Behrmann
Contact:
GESIS – Leibniz Institute for the Social Sciences, Department Knowledge Exchange & Outreach, GESIS Training, P.O. Box 12 21 55, 68072 Mannheim, training@gesis.org
Visit us at training.gesis.org
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