Greifswald 2024 – wissenschaftliches Programm
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DD: Fachverband Didaktik der Physik
DD 10: Hochschuldidaktik – Kompetenzen
DD 10.4: Vortrag
Dienstag, 27. Februar 2024, 12:00–12:20, ELP 1: SR 3.25
Integrating data analysis in Python into an introductory physics laboratory course — Eugenio Tufino1, Stefano Oss1, and •Micol Alemani2 — 1Department of Physics, University of Trento, 38123 Trento, Italy — 2Institute for Physics and Astronomy, University of Potsdam, 14476 Potsdam, Germany
In all fields of experimental science and in industry, the rate at which data is being generated is accelerating, and the use of robust tools for data analysis and interpretation has become a necessity. There is thus a growing need to teach computational skills in the physics laboratory courses (PLC), a step away from the conventional use of spreadsheets and integrated mathematical computing packages typically found in those settings. In this presentation, we describe how we introduced data analysis in Python in the first year PLC for physics major students at the University of Potsdam using an active learning type of approach. We carefully developed Jupyter notebooks with exercises and applied physics examples to guide students through the fundamentals of data handling and analysis in Python. Students engage in data analysis actively in the course and use the teaching materials independently and collaboratively, applying the learned techniques and skills in subsequent experiments. The effectiveness of the intervention was evaluated on the basis of qualitative empirical studies. They provide information on students' initial preparation, expectations, and learning.