Collaborative Research: Further Characterizing Active Learning Environments in Physics

该项目旨在通过改进大学物理课程的教与学来服务于国家利益。这个合作项目涉及德雷塞尔大学(应获奖-2111128)和莱特州立大学(应获奖-2111275)的研究人员。教育研究表明，使用“主动学习”方法是提高学生在STEM课堂上学习的核心。在物理中，许多不同的教学方法都属于“主动学习”的范畴，但这些方法之间有何不同的具体细节尚不清楚。所有主动学习课程都相同的一种方式是，学生之间的互动比标准课堂上的互动更多。在这个项目中，研究人员将试图通过收集学生和教师在课堂上做什么以及学生如何相互作用的数据来确定物理主动学习的重要特征。然后，他们将尝试将这些数据与改善学生的学习联系起来。这项研究将帮助教师决定哪种教学方法最适合他们的学生群体。这个项目将建立在研究人员在之前的一个项目中进行的探索性研究的基础上，该项目由美国国家科学基金会奖DUE-1711017和DUE-1712341资助，名为“合作研究：表征物理中的主动学习环境”。这项研究使用网络分析和本科生STEM课堂观察协议(COPUS)分析了主动学习环境之间的差异。重点放在少数几个网站上，这些网站代表了六种主动学习教学法的高保真、高质量实施。研究人员发现，教学中反复出现中等规模的网络结构，细粒度模型开始识别较小规模的特征。此外，通过对Copus观察使用潜在轮廓分析(LPA)，研究人员发现Copus对所考察的不同教学方法呈现出不同的轮廓。在新的项目中，调查人员将扩展试点项目的基线数据，探索相同教学的其他实施地点是否广泛重复这种模式，以及它们与学生结果的关系。特别是，调查人员将通过收集和分析来自32个不同站点的数据，并通过协调现有的网络和Copus测量与学生结果数据来扩展他们之前的工作。这项研究的主要目的将是(1)根据学生与学生之间的互动以及教师和学生在每个学习环境中的活动来描述物理中主动学习课程的实施情况，(2)调查跨主动学习环境的学生-学生网络发展的共同特征，以及(3)整合关于学生网络和COPUS档案的数据与学生成绩的关系。额外的数据和分析应该使研究人员能够确定有助于特定学生结果的积极学习环境的特定特征。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过参与的学生学习路径，该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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 teaching and learning in college and university physics courses. This collaborative project involves investigators at Drexel University (Award DUE-2111128) and Wright State University (Award DUE-2111275). Education research has shown that using an "active learning" approach is central to improving students' learning in STEM classes. In physics, many different teaching methods fall under the umbrella of "active learning," but the specifics of how the methods differ from one another are not clear. One way in which all active learning classes are the same is that the students interact more with each other than they do in standard lectures. In this project, the investigators will attempt to identify the important features of active learning in physics by collecting data on what students and instructors are doing during class and how students are interacting with each other. Then they will attempt to relate these data to improved student learning. This research will help instructors make decisions about which teaching methods are best for their population of students.This project will build on exploratory research that the investigators conducted during a previous project that was funded by NSF Awards DUE-1711017 and DUE-1712341, "Collaborative Research: Characterizing Active Learning Environments in Physics." That research analyzed differences among active learning environments using network analysis and the Classroom Observation Protocol for Undergraduate STEM (COPUS). The focus was on a small number of sites that represented high-fidelity, high-quality implementations of six active learning pedagogies. The investigators discovered recurring mid-scale network structures across pedagogies, with fine-grained models beginning to identify smaller-scale features. In addition, by using Latent Profile Analysis (LPA) on COPUS observations, the investigators found that the COPUS presents distinct profiles for the different pedagogies that were examined. In the new project, the investigators will extend the baseline data from the pilot project, exploring whether the patterns are broadly repeated at other implementation sites of the same pedagogies and how they relate to student outcomes. In particular, the investigators will extend their previous work by collecting and analyzing data from 32 different sites and by coordinating the existing network and COPUS measures with student outcome data. Key aims of the research will be (1) to characterize implementations of active learning curricula in physics in terms of student-student interactions and instructor and student activity within each learning environment, (2) to survey common features of student-student network development across active learning environments, and (3) to integrate data on student networks and COPUS profiles in relation to student outcomes. The additional data and analyses should enable researchers to identify the specific features of active learning environments that contribute to specific student outcomes. 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.