PhD Position in Learning Analytics and Self-Regulated Learning

At the Hector Research Institute of Education Sciences and Psychology, an interdisciplinary research institute at the University of Tübingen, the following position is available from 1st January 2027:

PhD Position in Learning Analytics and Self-Regulated Learning (m/f/d, E13 TV-L, 75%)

DFG-funded project TRACE:
Trajectories of Adaptation, Disengagement, and Choice in Authentic Educational Settings

We are seeking a highly motivated PhD candidate with a background in Psychology, Empirical Educational Research, Educational Science, Data Science, Statistics, Economics, Learning Sciences, or a related field to join TRACE at the Hector Research Institute of Education Sciences and Psychology, University of Tübingen. TRACE investigates how university students regulate their learning across a semester: how they adapt their study behavior in response to performance feedback, when and why they disengage from cognitively demanding strategies such as retrieval practice, and how these processes shape their decision to sit the final exam or postpone it.

TRACE combines log data from weekly online retrieval practice exercises with weekly survey measures of motivational beliefs, achievement emotions, self-set course goals, and exam records.

The project analyses these data at three levels: micro-level adaptation of learning strategies after performance feedback; meso-level trajectories of disengagement and re-engagement across the semester; and macro-level decisions about exam participation. Methodologically, the PhD candidate will work with methods like longitudinal within-person models, discrete-time survival analysis, and/or explainable machine learning. Each of the three work packages is designed to result in one publication, together constituting a cumulative dissertation.

The PhD candidate will join a vibrant international research environment with close supervision and extensive opportunities for methodological and professional development. The PhD candidate will work closely with Dr. Jakob Schwerter, the principal investigator of TRACE.
The project is embedded in the SRL-Hub (Prof. Kou Murayama, Prof. Michiko Sakaki, and Prof. Luise von Keyserlingk) at the Hector Research Institute and supported by an advisory board: Prof. Anique de Bruin (Maastricht University), Prof. Jeff Greene (University of North Carolina at Chapel Hill), and Prof. Luise von Keyserlingk (University of Tübingen).

What We Expect from You

We are looking for a candidate with a strong quantitative background, a genuine interest in how students learn, and motivation to contribute to high-quality scientific publications. Specifically, we expect:

• An excellent academic degree (Master's or equivalent) in Psychology, Empirical Educational Research, Educational Science, Data Science, Statistics, Economics, Learning Sciences, or a related field.
• A strong interest in self-regulated learning, motivation, and achievement emotions in authentic educational settings.
• Solid training in quantitative methods and the willingness to acquire advanced longitudinal and machine-learning methods.
• Programming skills in R (or a demonstrated ability to acquire them quickly).
• An interest in working with large, real-world data from digital learning environments combined with repeated survey measures.
• A willingness to engage in interdisciplinary collaboration and teamwork.
• Proficiency in English as the working language of an international research team, the ability to work independently, and a high level of personal commitment.
• A commitment to continuous professional development in line with the project’s requirements.

In addition, the following qualifications would be considered an asset:

• Experience with longitudinal data and/or machine learning and model interpretation.
• Experience with educational log or trace data, learning analytics, or educational data mining.
• German language skills, helpful for the German-language course materials and survey instruments, but not a requirement.

What We Offer

We provide an inspiring, productive, and collaborative research environment with excellent opportunities for professional and academic development. Specifically, we offer:

• Comprehensive supervision and a wide range of training opportunities, including methodological training as part of early-career researcher support.
• The opportunity to contribute to cutting-edge research at the intersection of learning analytics, self-regulated learning and education.
• Access to rich, already collected longitudinal datasets, alongside opportunities to contribute to new data collections
• In-depth training in longitudinal modelling, survival analysis, and explainable machine learning, plus guidance in scientific publishing and in developing your own research profile.
• Funding for presenting your work at national and international conferences (e.g., GEBF, EARLI, AERA).
• Integration into the LEAD Graduate School & Research Network and into the SRL-Hub of the Hector Research Institute.

For further information about the position, please contact Dr. Jakob Schwerter at jakob.schwerter@uni-tuebingen.de , the PI of TRACE.

The Hector Research Institute of Education Sciences and Psychology is an interdisciplinary research institute at the University of Tübingen, dedicated to investigating the individual, social, and institutional determinants of learning and educational processes. Our research employs a broad range of methodological approaches, including large-scale assessments, longitudinal and laboratory studies, and randomized field experiments. We collaborate closely with schools and educational institutions to generate evidence-based insights to improve the educational landscape. Our institute is recognized as a leading center for empirical educational research both nationally and internationally. As an interdisciplinary team, we work in a well-equipped research facility, located near the historic old town of Tübingen. For more information about our work and institute, please visit hib.uni-tuebingen.de.

We hope to have sparked your interest! Please submit your complete and compelling application as a single PDF document. Your application should include a motivation letter, CV, transcripts, and the names of two academic referees. Reference "PhD TRACE" in the subject line of your email. Send your application to jobs@hib.uni-tuebingen.deby September 8, 2026. Interviews are scheduled for September 22, 2026.

Applicants with disabilities will be given preferential consideration if equally qualified. The University of Tübingen is committed to equal opportunities and diversity and takes individual life circumstances into account. The university aims to increase the representation of women in research and teaching and therefore strongly encourages qualified female researchers to apply.

The employment will be administered through the Central Administration of the University of Tübingen.