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

该项目旨在通过提高学生对测量不确定性的理解来服务于国家利益，这是科学和工程实验过程中的一个关键概念。了解测量不确定度对于评估实验数据和从这些数据得出的结论至关重要。介绍性物理实验室课程是许多本科STEM学生打算学习测量不确定性的地方，但研究表明，围绕这一主题的学习目标往往得不到满足。通过创建基于良好研究实践的计算机模拟和相关课程材料，研究人员旨在提高学生对测量不确定性的学习。这些知识和技能将使学生能够在未来的学习和职业生涯中更好地推理数据并做出决策。为了提高学生对测量不确定性的概念性知识和观点，项目团队将开发和研究使用具有可调“噪声”的模拟（西姆斯）的影响。“具体来说，他们将添加统计（随机）噪声到一系列物理教育技术（PhET）交互式模拟常见的入门实验室实验。此外，为了让学生能够轻松直观地收集和分析数据，该团队将把噪声增强的PhET西姆斯与通用在线数据分析平台（CODAP）集成在一起。使用这个新的综合平台对学生理解测量不确定性以及学生如何看待实验科学测量的影响将在临床环境以及不同合作机构的课堂上进行研究。通过这一过程，项目团队还将制定战略和相关的课程材料，在实验室课程中实施这一新平台。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.