Developing Simulations with Noise to Investigate Students' Understanding and Views of Measurement Uncertainty in Experimental Physics

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This project aims to serve the national interest by improving students' understanding of uncertainty in measurement, which is a key concept in the process of experimentation across science and engineering. Understanding measurement uncertainty is critical for evaluating experimental data and conclusions made from those data. Introductory physics lab classes are where many undergraduate STEM students are intended to learn about measurement uncertainty, but studies have shown that the learning goals around this topic are often not met. By creating computer simulations and associated course materials that are based on sound research practices, the investigators aim to improve students' learning about measurement uncertainty. The knowledge and skills will allow the students to reason better about, and make decisions with, data in their future studies and careers.To improve students' conceptual knowledge of and views about measurement uncertainty, the project team will develop and study the impact of the use of simulations (sims) with adjustable "noise." Specifically, they will add statistical (random) noise to a selection of Physics Education Technology (PhET) Interactive Simulations of common introductory lab experiments. In addition, to allow students to easily and intuitively collect and analyze data, the team will integrate the noise-enhanced PhET sims with the Common Online Data Analysis Platform (CODAP). The impact of the use of this new, integrated platform on students' understanding of measurement uncertainty and how students view measurements in experimental science will be studied in a clinical setting as well as in the classrooms of diverse partner institutions. Through this process, the project team will also develop strategies and associated curricular materials for implementing this new platform in lab courses. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.