Prof. Dr. Peter Edelsbrunner

• Short CV and research statement:

I am passionate about quantitative methods in educational, psychological, and developmental research.

My background is in Psychology (2012, University of Graz) and I completed my PhD in 2017 in Learning and Instruction at ETH Zurich, where I have been active in teacher education for over a decade.

My methodological research examines questions in applied statistics that are of high relevance to applied researchers: How can we establish evidence for the absence of effects, when is it adequate to use factor analysis or sum scores, and how can we model the dependence of intervention effects on characteristics of the participants?

Methodological research areas and interests: Mixture modeling (latent class-, profile-, and transition analysis), Bayesian statistics, causal inference, statistical meta-theory.

My substantive research is concerned with the development, pedagogical support, and statistical modeling of scientific thinking throughout the life-span: How do children learn to engage in reliable processes of knowledge construction, what do youth think about Science, and how do adults perceive and interpret scientific information and build up scientific knowledge?

Focal substantive research areas: Epistemic beliefs and cognition, knowledge construction and development, learning transfer and dynamics.

I am a member of the LMU Open Science Center, where I am particularly interested in the didactics of open science and research methods.

Detailed Curriculum Vitae (PDF) (PDF, 382 KB)

In case of interest please contact me via peter.edelsbrunner@psy.lmu.de.

Further information and possible thesis topics (in German language, PDF) (PDF, 151 KB)

• Edelsbrunner, P. A., Simonsmeier, B. A., & Schneider, M. (2025). The Cronbach’s Alpha of Domain-Specific Knowledge Tests Before and After Learning: A Meta-Analysis of Published Studies. Educational Psychology Review, 37(1), Article 4. Link pdf data/scripts
• Edelsbrunner, P. A., & Thurn, C. (2024). Improving the Utility of Non-Significant Results for Education: A Review and Recommendations. Educational Research Review, 42, Article 100590. Advance online publication. Link pdf data/scripts
• Edelsbrunner, P. A.*, Flaig, M.*, & Schneider, M. (2023). A Simulation Study on Latent Transition Analysis for Examining Profiles and Trajectories in Education: Recommendations for Fit Statistics. Journal of Research on Educational Effectiveness, 16(2), 350-275. Materials and preprint available from https://psyarxiv.com/bqc94/ Link *Authors contributed equally pdf data/scripts
• Edelsbrunner, P. A. (2022). A Model and its Fit Lie in The Eye of the Beholder: Long Live the Sum Score. Frontiers in Psychology, 13. Link
• Tetzlaff, L. * Edelsbrunner, P. A.*, Schmitterer, A., Hartmann, U., & Brod, G. (2023). Modeling interactions between multivariate learner characteristics and interventions: A person-centered approach. Educational Psychology Review, 35(4), Article 112. Link *Authors contributed equally pdf data/scripts
• Schiefer, J.*, Edelsbrunner, P. A.*, Bernholt, A., Kampa, N., & Nehring, A. (2022). Profiles of epistemic beliefs in science: An integration of evidence from multiple studies. Educational Psychology Review, 34, 1545-1575. Link *Authors contributed equally. pdf/materials