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Prof. Dr. Sven Hilbert

Professor

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Vice Dean of the Faculty of Human Sciences

Speaker of the Research College

Scientific Director of the Center for Didactics of Higher Education and Science 

E-Mail: sven.hilbert@ur.de

University of Regensburg - Sedanstr. 1, Room 138A (1st floor)

Office hours: Wednesday, 2 - 3 p.m. (by appointment only via email)

Profile: ORCID


CV

Since 2023 W3-Professor for Educational Data Science, University of Regensburg
2017 - 2023   W2-Professor for Methods of Empirical Educational Research, University of Regensburg
2022 Promotion to W3 Professorship for Educational Data Science, University of Regensburg
2017          Promotion to W2-Professorship for Life for Methods of Empirical Educational Research, University of Regensburg
2016 - 2017        Substitute Professor, Methods of Empirical Educational Research, University of Regensburg
2017 Postdoctoral degree, Ludwig-Maximilians-Universität, Munich
2015 - 2016 Research Associate, Chair of Psychological Methodology and Diagnostics Ludwig-Maximilians-University, Munich
2014 - 2016 Master's degree program of Statistics (Degree: Master of Science), Ludwig-Maximilians-University, Munich
2014 - 2015 Substitute Professor, Chair of Psychological Methodology, Humboldt University Berlin
2011 - 2014  Research Associate, Chair of Psychological Methodology and Diagnostics Ludwig-Maximilians-University, Munich
2011  Research Associate, Chair of Psychological Diagnostics, Karl-Franzens University, Graz
2011 Research Associate, Humboldt-Innovation GmbH, Berlin
2010 - 2013  Doctorate in Psychology, Ludwig-Maximilians-University, Munich
2008 - 2010

Master's degree program Neuro-Cognitive Psychology (Degree: Master of Science), Ludwig-Maximilians-University, Munich

2007 - 2008  Psychologie License 3, Université de Nantes
2005 - 2010  Psychology, (Degree: Diploma) Ludwig-Maximilians-University, Munich

Teaching

  • Research colloquia for doctoral and postdoctoral students
  • Advanced Statistics
  • Basics of Statistics
  • Statistical Analysis with R
  • Machine Learning

Research

  • Questionnaire items
  • Structural Equation Models
  • Mixed Models
  • Working Memory
  • Cognitive Strategies
  • Mathematical Learning

Publications

Recent publications:

Himi. S., Stadler, M., von Bastian, C., Bühner, M. & Hilbert, S. (in print). Limits of Near Transfer: Content- and Operation-Specific Effects of Working Memory Training. Journal of Experimental Psychology: General.

Hilbert, S., Coors, S., Kraus, E. B., Bischl, B., Frei, M., Lindl, A., ..., & Stachl, C. (2021). Machine Learning for the Educational Sciences. Review of Education, 9, e3310.

Hilbert, S., Stadler, M., Lindl, A., Naumann, F. & Bühner, M. (2019). Analyzing longitudinal intervention studies with linear mixed models. Testing, Psychometry, Methodology in Applied Psychology, 26, 101–119.

Hilbert, S., Nakagawa, T. T., Puci, P., Zech, A. & Bühner, M. (2015). The Digit Span Backwards Task: Verbal and Visual Cognitive Strategies in Working Memory Assessment. European Journal of Psychological Assessment, 31(3), 174–180.

Heene, M., Hilbert, S., Draxler, C., Ziegler, M. & Bühner, M. (2011). Masking Misfit in Confirmatory Factor Analysis by Increasing Unique Variances: A Cautionary Note on the Usefulness of Cutoff Values of Fit Indices. Psychological Methods, 16(3), 319–336.

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Presentation slides

Educational Data Science

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To fit is to overfit

Link to PDF

Model validity

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Open Science against the background of the replication crisis

Link to PDF

Big Data and Machine Learning in Psychology

Link to PDF



Contact Information Educational Data Science

E-Mail: eds@ur.de


Administration Office

Ms. Lessel-Schuler
sekretariat.hilbert@ur.de
Phone: 0941/943-3783
Fax: 0941/943-4989