Integrating noise into PhET simulations to promote student learning of measurement uncertainty

TL;DR

This work addresses the persistent challenge of teaching measurement uncertainty in physics labs by introducing a noise-enhanced PhET simulation, Projectile Data Lab (PDL), and integrating it with the CODAP platform to support data analysis. The authors ground the design in constructivist theory and three guiding principles—open-ended exploration, scaffolding, and contrasting cases—and implement four interconnected screens to progressively build understanding of variability, uncertainty sources, and data interpretation. They also develop three instructional lab activities that leverage the PDL+CODAP platform to foster practical skills in measuring and analyzing uncertainty, validated through student interviews and designed for flexible use in courses. The contributions offer a scalable model for incorporating authentic noise and data fluency into physics education, with implications for broader adoption across disciplines and potential expansion into a suite of Data Lab simulations.

Abstract

Understanding concepts and practices of measurement uncertainty is a core competency of physicists and engineers, and many physics lab courses aim to have students learn these ideas. However, there is strong evidence that these goals are often not met. To address the challenge of improving students' proficiency with measurement uncertainty concepts and practices, we designed and developed a new PhET simulation, Projectile Data Lab (PDL), featuring statistical noise and measurement tools in the context of projectile motion. We integrated this simulation into the Common Online Data Analysis Platform (CODAP), creating an instructional platform for collecting and analyzing data from the simulation, and designed three simulation-based instructional activities for instructors to use in their lab courses. We describe the pedagogical design of the new simulation, the PDL+CODAP instructional platform, and the associated instructional activities. We highlight how the targeted learning goals guided the pedagogical design, as well as how these three instructional tools (the simulation, the PDL+CODAP platform, and the lab activity) work together and leverage the affordances of each to scaffold learning. The goal of this work is to provide a model of how noise-enhanced simulations and activities can be designed to enhance student learning of measurement uncertainty.

Figures (5)

• Figure 1: Percent of physics lab courses (N = 136) for which the surveyed instructors identified the importance of each targeted learning goal as a major goal (dark green), minor goal (green), not a goal (lime green), and future goal (light green). The items are listed in the same order as they appear in Fig. \ref{['fig2']}.
• Figure 2: Targeted learning goals, along with associated capabilities and design features of the PDL simulation, CODAP platform, and lab activities that support these learning goals. If the target learning goal is one of the SPRUCE assessment objectives, the corresponding label is included in parenthesis with an asterisk marked at the end geschwind2024using.
• Figure 3: The 'Measures' Screen of the Projectile Data Lab PhET simulation. Students can choose from six different launchers with varying amounts of statistical noise in their launch speed and angle. The variation in the projectiles' horizontal distances can be visualized in the histogram panel. The interval tool allows the students to quantify the amount of data in a particular range.
• Figure 4: An example interface of the integrated PDL+CODAP instructional platform. Students can choose the setup and select the data they wish to collect. As they launch projectiles in the simulation, the selected data automatically populates in a table. Using a simple drag-and-drop interface, students can plot variables and explore relationships. CODAP also enables comparisons between distributions and provides tools for calculating statistics across selected variables.
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