Rasch analysis in physics education research: Why measurement matters

by Maja Planinic (Faculty of Science, University of Zagreb, Zagreb, Croatia)

Thursday 28 May 2026, 16:00 → 17:00 Europe/Zurich

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From the big bang to black holes, from elementary particles and the fundamental interactions that govern our universe to the world's largest and most complex scientific instruments, our knowledge of the world builds on modern physics. To make our current-best understanding available to all, we need to invest in educational research and bridge the gap between those who know science, those who teach science, and those who learn science. 

This month, we will discuss a paper by Maja Planinic, William J. Boone, Ana Susac, and Lana Ivanjek about Rasch modelling in Physics Education Research.

Abstract: 

The Rasch model is a probabilistic model which describes the interaction of persons (test takers or survey respondents) with test or survey items and is governed by two parameters: item difficulty and person ability. Rasch measurement parallels physical measurement processes by constructing and using linear person and item measures that are independent of the particular characteristics of the sample and the test items along a unidimensional construct. The model’s properties make it especially suitable for test construction and evaluation as well as the development and use of surveys. The evaluation of item fit with the model can pinpoint problematic items and flag idiosyncratic respondents. The possibility of determining sample—independent item difficulties makes it possible to use the Rasch model for linking tests and tracking students’ progression. The use of the Rasch model in PER is continuously increasing. We provide an overview and examples of its use and benefits, and also outline common mistakes or misconceptions made by researchers when considering the use of the Rasch model. We focus in particular on the question of how Rasch modeling can improve some common practices in PER, such as test construction, test evaluation, and calculation of student gain on PER diagnostic instruments.

Paper:

Planinic, M., Boone, W. J., Susac, A., & Ivanjek, L. (2019). Rasch analysis in physics education research: Why measurement matters. Physical Review Physics Education Research, 15(2), 020111. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111