Home - FAIR - TU Dortmund

Location & approach

By car

The campus of the TU Dortmund University is located near the freeway junction Dortmund West, where the Sauerland line A45 crosses the Ruhr expressway B1/A40. The Dortmund-Eichlinghofen exit on the A45 leads to the South Campus, the Dortmund-Dorstfeld exit on the A40 leads to the North Campus. The university is signposted at both exits. All FAIR PIs have offices on the North Campus. FAIR's main offices will be located a bit off the North Campus on Martin-Schmeisser-Weg 17 (parking behind the building).

By train

The "Dortmund Universität" S-Bahn station is located directly on the North Campus. From there, the S-Bahn line S1 runs every 15 or 30 minutes to Dortmund main station and in the opposite direction to Düsseldorf main station via Bochum, Essen and Duisburg. In addition, the university can be reached by bus lines 445, 447 and 462. Timetable information can be found on the homepage of the Verkehrsverbundes Rhein-Ruhr, and DSW21 also offer an interactive route network map.

By plane

From Dortmund Airport, the AirportExpress takes just over 20 minutes to Dortmund main station and from there to the university by S-Bahn. A wider range of international flight connections is offered by Düsseldorf Airport, about 60 kilometers away, which can be reached directly by S-Bahn from the university's train station.

The H-Bahn

One of the landmarks of the TU Dortmund is the H-Bahn. Line 1 runs every 10 minutes between Dortmund Eichlinghofen and the Technology Center via Campus South and Dortmund University S, while Line 2 commutes every 5 minutes between Campus North and Campus South. It covers this distance in two minutes.

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Location & approach

By car

The campus of the TU Dortmund University is located near the freeway junction Dortmund West, where the Sauerland line A45 crosses the Ruhr expressway B1/A40. The Dortmund-Eichlinghofen exit on the A45 leads to the South Campus, the Dortmund-Dorstfeld exit on the A40 leads to the North Campus. The university is signposted at both exits. All FAIR PIs have offices on the North Campus. FAIR's main offices will be located a bit off the North Campus on Martin-Schmeisser-Weg 17 (parking behind the building).

By train

The "Dortmund Universität" S-Bahn station is located directly on the North Campus. From there, the S-Bahn line S1 runs every 15 or 30 minutes to Dortmund main station and in the opposite direction to Düsseldorf main station via Bochum, Essen and Duisburg. In addition, the university can be reached by bus lines 445, 447 and 462. Timetable information can be found on the homepage of the Verkehrsverbundes Rhein-Ruhr, and DSW21 also offer an interactive route network map.

By plane

From Dortmund Airport, the AirportExpress takes just over 20 minutes to Dortmund main station and from there to the university by S-Bahn. A wider range of international flight connections is offered by Düsseldorf Airport, about 60 kilometers away, which can be reached directly by S-Bahn from the university's train station.

The H-Bahn

One of the landmarks of the TU Dortmund is the H-Bahn. Line 1 runs every 10 minutes between Dortmund Eichlinghofen and the Technology Center via Campus South and Dortmund University S, while Line 2 commutes every 5 minutes between Campus North and Campus South. It covers this distance in two minutes.

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FAIR

From Prediction to Agile Interventions in the Social Sciences

What we do, how and why

Opening of the Interdisciplinary Center Agile PAIR

We warmly invite you to attend the opening ceremony of Agile PAIR on Tuesday, February 18, 2025, from 13:00 - 17:00.

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FAIR Learning Analytics Workshop at the IFS

Workshop on ‘Learning Analytics’ took place at the IFS with participants from all over Germany.

IFS contributes to the FAIR Graduate Programme for Statistical Methods

The FAIR Graduate Programme offers doctoral students in the social sciences workshops on statistical methods.

UA Ruhr-funded Civic Education Research Lab starts in October

Elisabeth Graf, Pascal Alscher und Daniel Deimel are pursuing the goal of conducting research on successful civic education with CERL.

DoDaS Guest: Arne Bathke

Prof. Dr. Arne Bathke (Paris Lodron Universität Salzburg) Inference methods for multivariate data

FAIR Workshop, September 25-27, 2024

The interdisciplinary research area FAIR organizes a three-day workshop on Learning Analytics.

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DoDaS & FAIR Guest: Chris Schwiegelshohn

Prof. Dr. Chris Schwiegelshohn (Aarhus University) Deterministic Clustering in High Dimensional Spaces: Sketches and Approximation

Successful workshop on "Digital Trace Data in Social Science Research"

From June 26 to 28, 2024, the workshop "Digital Trace Data in Social Science Research," organized by the research area FAIR, took place.

FAIR Graduate Program

The interdisciplinary research area FAIR will offer a graduate program in statistical methods starting in the summer semester 2024.

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Special talk on Non-parametric Methods, April 24, 2024

Special talk by Prof. Dr. Edgar Brunner "Missbrauch, Gefahren und Fehlinterpretationen nichtparametrischer Verfahren"

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FAIR Workshop, June 26-28, 2024

The interdisciplinary research area FAIR organizes a three-day workshop on Digital Trace Data in Social Science Research.

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DoDaS & FAIR Guest: Jeff M. Phillips

Prof. Jeff M. Phillips, Ph.D. (University of Utah) Talk title: "Ferret: Reviewing Tabular Datasets for Manipulation"

portrait of Jeff M. Philipps

Mentoring award for Prof. Dr. Sarah Weigelt

Prof. Dr. Sarah Weigelt receives the Mentoring Award of the Developmental Psychology Section of the German Psychological Society

Self-regulated learning to improve teaching in computer science

New FAIR project in collaboration with Thomas Zeuma from RUB investigates formal computer science courses to improve their quality

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Cooperation project Klett "Meister Cody Kids"

The educational game "Meister Cody Kids" is developed as part of a project funded by the Federal Ministry for Economic Affairs and Climate Action

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FAIR workshop on "Using Resampling and Simulation to Tackle Heterogeneity in Social Science Research"

FAIR workshop on "Using Resampling and Simulation to Tackle Heterogeneity in Social Science Research" took place on 22 and 25 September 2023.

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FAIR Workshop, October 11-12, 2023

The interdisciplinary research area FAIR organizes a two-day workshop on Prediction Modeling.

[Translate to English:]

FAIR Workshop, September 22 and 25, 2023

The interdisciplinary research area FAIR organizes a two-day workshop on Using Resampling and Simulation.

[Translate to English:]

Assistant professorship for Luise von Keyserlingk

Luise von Keyserlingk is Assistant Professor for Learning and Instruction at the University of Tübingen, Hector Research Institute of Education…

FAIR Graduate Program

The interdisciplinary research area FAIR will offer a graduate program in statistical methods starting in the summer semester 2023.

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FAIR Workshop, November 22-23, 2022

The interdisciplinary research area FAIR organizes a two-day workshop on Sequence and Streaming Data Analysis.

[Translate to English:]

Agile Working

On August 18th and 19th, the FAIR team attended a training on agile project management by the ibo Academy.

Welcome!

The interdisciplinary research area From Prediction to Agile Interventions in the Social Sciences (FAIR) brings together researchers from the data sciences, statistics, education sciences, psychology, rehabilitation studies, and sociology. FAIR-researchers from these different disciplines will focus on the development and application of innovative research methods from the data sciences and use them to address societal challenges in highly relevant areas such as education, health, and societal inclusiveness and participation. Increasingly larger and more complex data have become available in the social sciences that can contribute to more precise prediction models (e.g., for such outcomes as academic success, health, and well-being) and aid our understanding of cause-effect relationships. An important objective is also the development of a framework for “Agile Intervention Research” that allows for individualized, data-driven, and need-based adaptations of interventions in authentic contexts. The FAIR-researchers will use “big” (large data sets) and “small” (small case numbers) data to optimize prognostic models in the social sciences and maximize the impact of available interventions in these fields by allowing for individualized adaptations.

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FAIR Scientists

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FAIR Research

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© Erwin Wodicka/Shotshop.com

Career@FAIR

Maths Tower and dining hall at dusk in winter.

© Roland Baege/TU Dortmund

News and Workshops

Funded by the Ministry of Culture and Science of the State of Northrhine Westphalia.